#744 by GitHub stars
matlab/matlab-agentic-toolkit
The MATLAB Agentic Toolkit brings proven MATLAB capabilities to AI agents, making engineering and scientific workflows agent-ready.
History
Review weekly changes to SKILL.md before updating. Dates mark the weeks in which we observed each version; checks apply to the recorded commits.
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skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md
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skills-catalog/aerospace/matlab-convert-aerospace-coordinates/SKILL.md
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skills-catalog/ai-and-statistics/matlab-analyze-reliability/SKILL.md
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skills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md
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skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/SKILL.md
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skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/SKILL.md
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skills-catalog/ai-and-statistics/matlab-fit-curve/SKILL.md
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skills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md
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skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model/SKILL.md
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skills-catalog/ai-and-statistics/matlab-train-network/SKILL.md
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skills-catalog/ai-and-statistics/matlab-use-experiment-manager/SKILL.md
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skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps/SKILL.md
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skills-catalog/automotive/matlab-cosimulate-sumo-simulink/SKILL.md
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skills-catalog/automotive/matlab-import-driving-data/SKILL.md
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skills-catalog/automotive/matlab-use-ncap-protocol/SKILL.md
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skills-catalog/automotive/matlab-use-scenario-builder/SKILL.md
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skills-catalog/automotive/roadrunner-asset-mapping/SKILL.md
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skills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md
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skills-catalog/automotive/roadrunner-convert-lanelet2-to-rrhd/SKILL.md
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skills-catalog/automotive/roadrunner-core/SKILL.md
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skills-catalog/automotive/roadrunner-import-scene/SKILL.md
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skills-catalog/automotive/roadrunner-rrhd-authoring/SKILL.md
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skills-catalog/automotive/roadrunner-scenario-authoring/SKILL.md
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skills-catalog/automotive/roadrunner-scenario-simulating/SKILL.md
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skills-catalog/cloud-solutions/matlab-share-content/SKILL.md
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skills-catalog/code-generation/matlab-deploy-ai-model/SKILL.md
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skills-catalog/code-generation/matlab-deploy-embedded-code/SKILL.md
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skills-catalog/code-generation/matlab-generate-code/SKILL.md
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skills-catalog/code-generation/matlab-optimize-gpu-codegen/SKILL.md
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skills-catalog/code-generation/matlab-review-fi-object-code/SKILL.md
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skills-catalog/computational-biology/simbiology-build-model/SKILL.md
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skills-catalog/computational-biology/simbiology-fit-model/SKILL.md
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skills-catalog/computational-biology/simbiology-simulate-model/SKILL.md
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skills-catalog/computational-finance/matlab-access-datafeed/SKILL.md
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skills-catalog/computational-finance/matlab-optimize-portfolio/SKILL.md
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skills-catalog/computational-finance/matlab-price-instrument/SKILL.md
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skills-catalog/computational-finance/matlab-use-spreadsheet-link/SKILL.md
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skills-catalog/control-systems/matlab-extract-battery-features/SKILL.md
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skills-catalog/control-systems/matlab-extract-rotating-machinery-features/SKILL.md
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skills-catalog/control-systems/matlab-identify-linear-system/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-analyze-spectral-images/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-display-image/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-display-volume/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-model-optics/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-process-images/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-read-write-point-cloud-file/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-recognize-text/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-register-point-clouds/SKILL.md
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skills-catalog/image-processing-and-computer-vision/matlab-use-visual-inspection/SKILL.md
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skills-catalog/math-and-optimization/matlab-solve-optimization/SKILL.md
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skills-catalog/math-and-optimization/matlab-solve-pde/SKILL.md
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skills-catalog/math-and-optimization/matlab-use-symbolic-math/SKILL.md
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skills-catalog/matlab-app-building/matlab-apply-theme/SKILL.md
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skills-catalog/matlab-app-building/matlab-build-app/SKILL.md
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skills-catalog/matlab-app-building/matlab-build-chart/SKILL.md
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skills-catalog/matlab-core/matlab-create-live-script/SKILL.md
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skills-catalog/matlab-core/matlab-debug-code/SKILL.md
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skills-catalog/matlab-core/matlab-install-products/SKILL.md
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skills-catalog/matlab-core/matlab-list-products/SKILL.md
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skills-catalog/matlab-core/matlab-read-documentation/SKILL.md
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skills-catalog/matlab-core/matlab-review-code/SKILL.md
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skills-catalog/matlab-data-import-and-analysis/matlab-analyze-data/SKILL.md
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skills-catalog/matlab-data-import-and-analysis/matlab-choose-big-data-solution/SKILL.md
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skills-catalog/matlab-data-import-and-analysis/matlab-import-export-data/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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skills-catalog/matlab-data-import-and-analysis/matlab-secure-credentials/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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skills-catalog/matlab-external-language-interfaces/matlab-call-python/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/matlab-external-language-interfaces/matlab-upgrade-mex-ic/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/matlab-programming/matlab-validate-function-arguments/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-configure-toml-project/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-instrument-opentelemetry-tracing/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-modernize-code/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-optimize-memory/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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skills-catalog/matlab-software-development/matlab-optimize-performance/SKILL.md
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No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-package-toolbox/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-run-tests/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-use-package-manager/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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skills-catalog/matlab-software-development/matlab-write-help/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-write-performance-tests/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/matlab-software-development/matlab-write-tests/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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No earlier version was observed for comparison.
skills-catalog/parallel-computing/matlab-diagnose-parfor/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/parallel-computing/matlab-discover-clusters/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/parallel-computing/matlab-set-up-worker-state/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/parallel-computing/matlab-setup-gpu/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/parallel-computing/matlab-use-thread-pool/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/radar/matlab-design-radar/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/radar/matlab-design-radar-waveform/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/radar/matlab-import-tracking-data/SKILL.md
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No earlier version was observed for comparison.
skills-catalog/radar/matlab-simulate-radar-detections/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/reporting-and-database-access/matlab-connect-databricks/SKILL.md
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No earlier version was observed for comparison.
skills-catalog/reporting-and-database-access/matlab-generate-report/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/reporting-and-database-access/matlab-use-database/SKILL.md
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No earlier version was observed for comparison.
skills-catalog/reporting-and-database-access/matlab-use-duckdb/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-analyze-ams-waveform/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-analyze-antenna-structures/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-analyze-em/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-analyze-pcb-pdn/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-assemble-pcb-layout/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-design-antenna/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-coupler/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-filter/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-passive/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-transmission-line/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-export-session-script/SKILL.md
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-integrate-antenna/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-integrate-pcb-circuit/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-manage-pcb-material/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-model-ams-systems/SKILL.md
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-model-rf/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-model-via/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-optimize-pcb-design/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-read-pcb-layout/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/rf-and-mixed-signal/matlab-write-pcb-layout/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/robotics-and-autonomous-systems/matlab-compute-gnss-position/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/robotics-and-autonomous-systems/matlab-connect-mavlink/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/robotics-and-autonomous-systems/matlab-create-uav-scenario/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
No earlier version was observed for comparison.
skills-catalog/robotics-and-autonomous-systems/matlab-fuse-inertial-sensors/SKILL.md
Week of Nov 2, 2026 · +0 / −0 lines
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Week of Oct 26, 2026 · Line counts unavailable
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First observation → 032b4b605999
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skills-catalog/robotics-and-autonomous-systems/matlab-model-robot-kinematics/SKILL.md
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skills-catalog/robotics-and-autonomous-systems/matlab-plan-robot-motion/SKILL.md
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skills-catalog/signal-processing/matlab-analyze-spectrum/SKILL.md
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skills-catalog/signal-processing/matlab-analyze-time-frequency-content/SKILL.md
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skills-catalog/signal-processing/matlab-configure-scope-object/SKILL.md
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skills-catalog/signal-processing/matlab-design-adaptive-filter/SKILL.md
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skills-catalog/signal-processing/matlab-design-digital-filter/SKILL.md
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skills-catalog/signal-processing/matlab-design-dsphdl-ddc/SKILL.md
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skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/SKILL.md
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skills-catalog/signal-processing/matlab-extract-signal-features/SKILL.md
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skills-catalog/signal-processing/matlab-play-record-audio/SKILL.md
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skills-catalog/signal-processing/matlab-prepare-signal-data/SKILL.md
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skills-catalog/signal-processing/matlab-process-streaming-audio/SKILL.md
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skills-catalog/signal-processing/matlab-write-audio-plugin/SKILL.md
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skills-catalog/test-and-measurement/matlab-build-industrial-hmi/SKILL.md
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skills-catalog/test-and-measurement/matlab-call-nidaqmx/SKILL.md
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skills-catalog/test-and-measurement/matlab-connect-arduino/SKILL.md
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skills-catalog/test-and-measurement/matlab-connect-bluetooth-low-energy-device/SKILL.md
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skills-catalog/test-and-measurement/matlab-create-custom-arduino-library/SKILL.md
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skills-catalog/test-and-measurement/matlab-discover-hardware/SKILL.md
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skills-catalog/test-and-measurement/matlab-enhance-camera-image/SKILL.md
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skills-catalog/test-and-measurement/matlab-find-pi-assets/SKILL.md
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skills-catalog/test-and-measurement/matlab-import-export-vehicle-data/SKILL.md
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skills-catalog/test-and-measurement/matlab-modernize-daq/SKILL.md
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skills-catalog/test-and-measurement/matlab-use-cameras/SKILL.md
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skills-catalog/test-and-measurement/matlab-use-opcua-client/SKILL.md
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skills-catalog/test-and-measurement/matlab-use-vehicle-network/SKILL.md
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skills-catalog/wireless-communications/matlab-add-awgn/SKILL.md
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skills-catalog/wireless-communications/matlab-design-ofdm-system/SKILL.md
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skills-catalog/wireless-communications/matlab-detect-capture-usrp/SKILL.md
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skills-catalog/wireless-communications/matlab-generate-5g-waveform/SKILL.md
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skills-catalog/wireless-communications/matlab-generate-ble-waveform/SKILL.md
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skills-catalog/wireless-communications/matlab-generate-gnss-waveform/SKILL.md
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skills-catalog/wireless-communications/matlab-generate-wlan-waveform/SKILL.md
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skills-catalog/wireless-communications/matlab-set-up-usrp-radio/SKILL.md
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skills-catalog/wireless-communications/matlab-simulate-bluetooth-network/SKILL.md
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skills-catalog/wireless-communications/matlab-simulate-wireless-network/SKILL.md
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skills-catalog/wireless-communications/matlab-transmit-capture-usrp/SKILL.md
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View on GitHubAdd to my skills
Verified commit 032b4b605999b1f4adecaac1efa1c9faad41adf6
git clone --filter=blob:none --no-checkout https://github.com/matlab/matlab-agentic-toolkit.git .hotskills/matlab-matlab-agentic-toolkit && git -C .hotskills/matlab-matlab-agentic-toolkit checkout --detach 032b4b605999b1f4adecaac1efa1c9faad41adf6
# Copy each selected skill directory from .hotskills/matlab-matlab-agentic-toolkit into .claude/skills/<skill-name>/git clone --filter=blob:none --no-checkout https://github.com/matlab/matlab-agentic-toolkit.git .hotskills/matlab-matlab-agentic-toolkit && git -C .hotskills/matlab-matlab-agentic-toolkit checkout --detach 032b4b605999b1f4adecaac1efa1c9faad41adf6
# Copy each selected skill directory from .hotskills/matlab-matlab-agentic-toolkit into .gemini/skills/<skill-name>/1.3kGitHub stars
36stars in 7 days
156skills in this repository
13commits in 30 days
Heat
7.2- Star growth, last 7 daysAhead of 94% of tracked repositories
- Star growth, last 24 hoursAhead of 96% of tracked repositories
- Rank movement, last 7 daysAhead of 48% of tracked repositories
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Individual skills in this repository
- matlab-compute-aerospace-environment
skills-catalog/aerospace/matlab-compute-aerospace-environment - matlab-convert-aerospace-coordinates
skills-catalog/aerospace/matlab-convert-aerospace-coordinates - matlab-analyze-reliability
skills-catalog/ai-and-statistics/matlab-analyze-reliability - matlab-classify-tabular-data
skills-catalog/ai-and-statistics/matlab-classify-tabular-data - matlab-deploy-embedded-ai
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai - matlab-engineer-tabular-features
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features - matlab-fit-curve
skills-catalog/ai-and-statistics/matlab-fit-curve - matlab-import-external-ai-model
skills-catalog/ai-and-statistics/matlab-import-external-ai-model - matlab-interpret-machine-learning-model
skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model - matlab-train-network
skills-catalog/ai-and-statistics/matlab-train-network - matlab-use-experiment-manager
skills-catalog/ai-and-statistics/matlab-use-experiment-manager - matlab-use-machine-learning-apps
skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps - matlab-cosimulate-sumo-simulink
skills-catalog/automotive/matlab-cosimulate-sumo-simulink - matlab-import-driving-data
skills-catalog/automotive/matlab-import-driving-data - matlab-use-ncap-protocol
skills-catalog/automotive/matlab-use-ncap-protocol - matlab-use-scenario-builder
skills-catalog/automotive/matlab-use-scenario-builder - roadrunner-asset-mapping
skills-catalog/automotive/roadrunner-asset-mapping - roadrunner-build-scenario-from-osc
skills-catalog/automotive/roadrunner-build-scenario-from-osc - roadrunner-convert-lanelet2-to-rrhd
skills-catalog/automotive/roadrunner-convert-lanelet2-to-rrhd - roadrunner-core
skills-catalog/automotive/roadrunner-core - roadrunner-import-scene
skills-catalog/automotive/roadrunner-import-scene - roadrunner-rrhd-authoring
skills-catalog/automotive/roadrunner-rrhd-authoring - roadrunner-scenario-authoring
skills-catalog/automotive/roadrunner-scenario-authoring - roadrunner-scenario-simulating
skills-catalog/automotive/roadrunner-scenario-simulating - matlab-share-content
skills-catalog/cloud-solutions/matlab-share-content - matlab-deploy-ai-model
skills-catalog/code-generation/matlab-deploy-ai-model - matlab-deploy-embedded-code
skills-catalog/code-generation/matlab-deploy-embedded-code - matlab-generate-code
skills-catalog/code-generation/matlab-generate-code - matlab-optimize-gpu-codegen
skills-catalog/code-generation/matlab-optimize-gpu-codegen - matlab-review-fi-object-code
skills-catalog/code-generation/matlab-review-fi-object-code - simbiology-build-model
skills-catalog/computational-biology/simbiology-build-model - simbiology-fit-model
skills-catalog/computational-biology/simbiology-fit-model - simbiology-simulate-model
skills-catalog/computational-biology/simbiology-simulate-model - matlab-access-datafeed
skills-catalog/computational-finance/matlab-access-datafeed - matlab-optimize-portfolio
skills-catalog/computational-finance/matlab-optimize-portfolio - matlab-price-instrument
skills-catalog/computational-finance/matlab-price-instrument - matlab-use-spreadsheet-link
skills-catalog/computational-finance/matlab-use-spreadsheet-link - matlab-extract-battery-features
skills-catalog/control-systems/matlab-extract-battery-features - matlab-extract-rotating-machinery-features
skills-catalog/control-systems/matlab-extract-rotating-machinery-features - matlab-identify-linear-system
skills-catalog/control-systems/matlab-identify-linear-system - matlab-analyze-spectral-images
skills-catalog/image-processing-and-computer-vision/matlab-analyze-spectral-images - matlab-display-image
skills-catalog/image-processing-and-computer-vision/matlab-display-image - matlab-display-volume
skills-catalog/image-processing-and-computer-vision/matlab-display-volume - matlab-integrate-pytorch-vision
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision - matlab-model-optics
skills-catalog/image-processing-and-computer-vision/matlab-model-optics - matlab-process-images
skills-catalog/image-processing-and-computer-vision/matlab-process-images - matlab-read-write-point-cloud-file
skills-catalog/image-processing-and-computer-vision/matlab-read-write-point-cloud-file - matlab-recognize-text
skills-catalog/image-processing-and-computer-vision/matlab-recognize-text - matlab-register-point-clouds
skills-catalog/image-processing-and-computer-vision/matlab-register-point-clouds - matlab-use-visual-inspection
skills-catalog/image-processing-and-computer-vision/matlab-use-visual-inspection - matlab-solve-optimization
skills-catalog/math-and-optimization/matlab-solve-optimization - matlab-solve-pde
skills-catalog/math-and-optimization/matlab-solve-pde - matlab-use-symbolic-math
skills-catalog/math-and-optimization/matlab-use-symbolic-math - matlab-apply-theme
skills-catalog/matlab-app-building/matlab-apply-theme - matlab-build-app
skills-catalog/matlab-app-building/matlab-build-app - matlab-build-chart
skills-catalog/matlab-app-building/matlab-build-chart - matlab-create-live-script
skills-catalog/matlab-core/matlab-create-live-script - matlab-debug-code
skills-catalog/matlab-core/matlab-debug-code - matlab-install-products
skills-catalog/matlab-core/matlab-install-products - matlab-list-products
skills-catalog/matlab-core/matlab-list-products - matlab-read-documentation
skills-catalog/matlab-core/matlab-read-documentation - matlab-review-code
skills-catalog/matlab-core/matlab-review-code - matlab-analyze-data
skills-catalog/matlab-data-import-and-analysis/matlab-analyze-data - matlab-choose-big-data-solution
skills-catalog/matlab-data-import-and-analysis/matlab-choose-big-data-solution - matlab-import-export-data
skills-catalog/matlab-data-import-and-analysis/matlab-import-export-data - matlab-secure-credentials
skills-catalog/matlab-data-import-and-analysis/matlab-secure-credentials - matlab-call-python
skills-catalog/matlab-external-language-interfaces/matlab-call-python - matlab-upgrade-mex-ic
skills-catalog/matlab-external-language-interfaces/matlab-upgrade-mex-ic - matlab-validate-function-arguments
skills-catalog/matlab-programming/matlab-validate-function-arguments - matlab-configure-toml-project
skills-catalog/matlab-software-development/matlab-configure-toml-project - matlab-instrument-opentelemetry-tracing
skills-catalog/matlab-software-development/matlab-instrument-opentelemetry-tracing - matlab-modernize-code
skills-catalog/matlab-software-development/matlab-modernize-code - matlab-optimize-memory
skills-catalog/matlab-software-development/matlab-optimize-memory - matlab-optimize-performance
skills-catalog/matlab-software-development/matlab-optimize-performance - matlab-package-toolbox
skills-catalog/matlab-software-development/matlab-package-toolbox - matlab-run-tests
skills-catalog/matlab-software-development/matlab-run-tests - matlab-use-package-manager
skills-catalog/matlab-software-development/matlab-use-package-manager - matlab-write-help
skills-catalog/matlab-software-development/matlab-write-help - matlab-write-performance-tests
skills-catalog/matlab-software-development/matlab-write-performance-tests - matlab-write-tests
skills-catalog/matlab-software-development/matlab-write-tests - matlab-diagnose-parfor
skills-catalog/parallel-computing/matlab-diagnose-parfor - matlab-discover-clusters
skills-catalog/parallel-computing/matlab-discover-clusters - matlab-set-up-worker-state
skills-catalog/parallel-computing/matlab-set-up-worker-state - matlab-setup-gpu
skills-catalog/parallel-computing/matlab-setup-gpu - matlab-use-thread-pool
skills-catalog/parallel-computing/matlab-use-thread-pool - matlab-design-radar
skills-catalog/radar/matlab-design-radar - matlab-design-radar-waveform
skills-catalog/radar/matlab-design-radar-waveform - matlab-import-tracking-data
skills-catalog/radar/matlab-import-tracking-data - matlab-simulate-radar-detections
skills-catalog/radar/matlab-simulate-radar-detections - matlab-connect-databricks
skills-catalog/reporting-and-database-access/matlab-connect-databricks - matlab-generate-report
skills-catalog/reporting-and-database-access/matlab-generate-report - matlab-use-database
skills-catalog/reporting-and-database-access/matlab-use-database - matlab-use-duckdb
skills-catalog/reporting-and-database-access/matlab-use-duckdb - matlab-analyze-ams-waveform
skills-catalog/rf-and-mixed-signal/matlab-analyze-ams-waveform - matlab-analyze-antenna-structures
skills-catalog/rf-and-mixed-signal/matlab-analyze-antenna-structures - matlab-analyze-em
skills-catalog/rf-and-mixed-signal/matlab-analyze-em - matlab-analyze-pcb-pdn
skills-catalog/rf-and-mixed-signal/matlab-analyze-pcb-pdn - matlab-assemble-pcb-layout
skills-catalog/rf-and-mixed-signal/matlab-assemble-pcb-layout - matlab-design-antenna
skills-catalog/rf-and-mixed-signal/matlab-design-antenna - matlab-design-pcb-coupler
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-coupler - matlab-design-pcb-filter
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-filter - matlab-design-pcb-passive
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-passive - matlab-design-pcb-transmission-line
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-transmission-line - matlab-export-session-script
skills-catalog/rf-and-mixed-signal/matlab-export-session-script - matlab-integrate-antenna
skills-catalog/rf-and-mixed-signal/matlab-integrate-antenna - matlab-integrate-pcb-circuit
skills-catalog/rf-and-mixed-signal/matlab-integrate-pcb-circuit - matlab-manage-pcb-material
skills-catalog/rf-and-mixed-signal/matlab-manage-pcb-material - matlab-model-ams-systems
skills-catalog/rf-and-mixed-signal/matlab-model-ams-systems - matlab-model-rf
skills-catalog/rf-and-mixed-signal/matlab-model-rf - matlab-model-serdes-systems
skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems - matlab-model-via
skills-catalog/rf-and-mixed-signal/matlab-model-via - matlab-optimize-pcb-design
skills-catalog/rf-and-mixed-signal/matlab-optimize-pcb-design - matlab-read-pcb-layout
skills-catalog/rf-and-mixed-signal/matlab-read-pcb-layout - matlab-write-pcb-layout
skills-catalog/rf-and-mixed-signal/matlab-write-pcb-layout - matlab-compute-gnss-position
skills-catalog/robotics-and-autonomous-systems/matlab-compute-gnss-position - matlab-connect-mavlink
skills-catalog/robotics-and-autonomous-systems/matlab-connect-mavlink - matlab-create-uav-scenario
skills-catalog/robotics-and-autonomous-systems/matlab-create-uav-scenario - matlab-fuse-inertial-sensors
skills-catalog/robotics-and-autonomous-systems/matlab-fuse-inertial-sensors - matlab-model-robot-kinematics
skills-catalog/robotics-and-autonomous-systems/matlab-model-robot-kinematics - matlab-plan-robot-motion
skills-catalog/robotics-and-autonomous-systems/matlab-plan-robot-motion - matlab-analyze-spectrum
skills-catalog/signal-processing/matlab-analyze-spectrum - matlab-analyze-time-frequency-content
skills-catalog/signal-processing/matlab-analyze-time-frequency-content - matlab-configure-scope-object
skills-catalog/signal-processing/matlab-configure-scope-object - matlab-design-adaptive-filter
skills-catalog/signal-processing/matlab-design-adaptive-filter - matlab-design-digital-filter
skills-catalog/signal-processing/matlab-design-digital-filter - matlab-design-dsphdl-ddc
skills-catalog/signal-processing/matlab-design-dsphdl-ddc - matlab-evaluate-acoustic-metrics
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics - matlab-extract-signal-features
skills-catalog/signal-processing/matlab-extract-signal-features - matlab-play-record-audio
skills-catalog/signal-processing/matlab-play-record-audio - matlab-prepare-signal-data
skills-catalog/signal-processing/matlab-prepare-signal-data - matlab-process-streaming-audio
skills-catalog/signal-processing/matlab-process-streaming-audio - matlab-write-audio-plugin
skills-catalog/signal-processing/matlab-write-audio-plugin - matlab-build-industrial-hmi
skills-catalog/test-and-measurement/matlab-build-industrial-hmi - matlab-call-nidaqmx
skills-catalog/test-and-measurement/matlab-call-nidaqmx - matlab-connect-arduino
skills-catalog/test-and-measurement/matlab-connect-arduino - matlab-connect-bluetooth-low-energy-device
skills-catalog/test-and-measurement/matlab-connect-bluetooth-low-energy-device - matlab-create-custom-arduino-library
skills-catalog/test-and-measurement/matlab-create-custom-arduino-library - matlab-discover-hardware
skills-catalog/test-and-measurement/matlab-discover-hardware - matlab-enhance-camera-image
skills-catalog/test-and-measurement/matlab-enhance-camera-image - matlab-find-pi-assets
skills-catalog/test-and-measurement/matlab-find-pi-assets - matlab-import-export-vehicle-data
skills-catalog/test-and-measurement/matlab-import-export-vehicle-data - matlab-modernize-daq
skills-catalog/test-and-measurement/matlab-modernize-daq - matlab-use-cameras
skills-catalog/test-and-measurement/matlab-use-cameras - matlab-use-opcua-client
skills-catalog/test-and-measurement/matlab-use-opcua-client - matlab-use-vehicle-network
skills-catalog/test-and-measurement/matlab-use-vehicle-network - matlab-add-awgn
skills-catalog/wireless-communications/matlab-add-awgn - matlab-design-ofdm-system
skills-catalog/wireless-communications/matlab-design-ofdm-system - matlab-detect-capture-usrp
skills-catalog/wireless-communications/matlab-detect-capture-usrp - matlab-generate-5g-waveform
skills-catalog/wireless-communications/matlab-generate-5g-waveform - matlab-generate-ble-waveform
skills-catalog/wireless-communications/matlab-generate-ble-waveform - matlab-generate-gnss-waveform
skills-catalog/wireless-communications/matlab-generate-gnss-waveform - matlab-generate-wlan-waveform
skills-catalog/wireless-communications/matlab-generate-wlan-waveform - matlab-set-up-usrp-radio
skills-catalog/wireless-communications/matlab-set-up-usrp-radio - matlab-simulate-bluetooth-network
skills-catalog/wireless-communications/matlab-simulate-bluetooth-network - matlab-simulate-wireless-network
skills-catalog/wireless-communications/matlab-simulate-wireless-network - matlab-transmit-capture-usrp
skills-catalog/wireless-communications/matlab-transmit-capture-usrp
How it works
matlab-compute-aerospace-environment
When your agent uses it
Compute aerospace environment properties including atmosphere (ISA, COESA, NRLMSISE-00, non-standard, CIRA), gravity (spherical harmonic, WGS84, zonal, centrifugal), horizontal wind (HWM), magnetic field (WMM, IGRF), geoid height, geocentric radius, space weather data, planetary ephemeris, Earth orientation (polar motion, nutation, delta-UT1, CIP). Use when computing atmospheric density, temperature, pressure, gravity vectors, wind profiles, magnetic field components, geoid undulation, solar flux indices, planet positions, or Earth orientation parameters for aerospace vehicle analysis, spacecraft environment modeling, or navigation corrections.
What it loads into context
Frontmatter
203 tokensAlways available to the agent
SKILL.md
5,077 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Decision Table
- Patterns
- Common Mistakes
- Conventions
Files
../../../.claude-plugin/marketplace.jsonasset14,011 bytesSKILL.mdcore16,806 bytesmanifest.yamlasset525 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-convert-aerospace-coordinates
When your agent uses it
Perform aerospace unit conversions, time conversions, coordinate frame transformations, and rotation representations using Aerospace Toolbox. Use when converting units (length, velocity, angle, acceleration, angular velocity, force, mass, pressure, temperature, density), computing Julian dates or decimal years, transforming between coordinate frames (ECEF, ECI, LLA, flat Earth, geodetic/geocentric, NED, body, wind, stability), or working with rotation representations (Euler angles, DCM, quaternion, Rodrigues vector). Also use when the user asks about aerospace coordinate systems, reference frames, or rotation conventions.
What it loads into context
Frontmatter
184 tokensAlways available to the agent
SKILL.md
5,625 tokensWhen the skill is activated
Reference documents
5,321 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- Gimbal Lock
- References
Files
SKILL.mdcore17,665 bytesmanifest.yamlasset499 bytesreferences/coordinate-systems.mddoc6,943 bytesreferences/rotation-conventions.mddoc9,130 bytesreferences/unit-conversion-guide.mddoc3,809 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-reliability
When your agent uses it
Use this skill when fitting accelerated life models, computing mean time to failure (MTTF), B10 life and similar quantities, fitting life distributions like Weibull for reliability analysis, comparing distribution fits, computing confidence intervals on reliability quantities with bootstrapping, performing lifetime prediction, computing failure rates, plotting Kaplan-Meier curves, computing survival functions, or doing reliability analysis.
What it loads into context
Frontmatter
120 tokensAlways available to the agent
SKILL.md
3,065 tokensWhen the skill is activated
Reference documents
343 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Functions
- Conventions
Files
SKILL.mdcore12,886 bytesmanifest.yamlasset473 bytesreferences/distribution-methods.mddoc1,470 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-classify-tabular-data
When your agent uses it
Use this skill to classify tabular data end-to-end in MATLAB — load a dataset, prepare and clean it, select promising classifiers, train them, and compare accuracies with cross-validation, holdout, or hyperparameter optimization plus statistical tests. TRIGGER when: user asks to classify tabular data, pick classifiers for a dataset, compare classifier accuracy, run cross-validation or a holdout evaluation, or find the best model with statistical uncertainty. DO NOT TRIGGER when: user has non-tabular inputs (images, sequences, time series), wants a regression model, is training a specific neural network architecture (use matlab-train-network), or wants cost-sensitive learning or an arbitrary class-prior vector (this skill only supports the built-in uniform-prior toggle for imbalanced data).
What it loads into context
Frontmatter
220 tokensAlways available to the agent
SKILL.md
9,141 tokensWhen the skill is activated
Reference documents
10,767 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Running MATLAB
- Communication style while running this skill
- Before Writing Code
- Step 1: Load data
- Step 2: Analyze and clean data
- Step 3: Choose evaluation strategy
- Step 4: Ask about interpretability
- Step 5: Select and define model templates
- Step 6: Get baseline accuracy estimates
- Step 7: Choose the statistical comparison method
- Step 8: Run the comparison
- Step 9: Visualize
- Step 10: Boosting learning curve
- Step 11: Hyperparameter optimization (optional)
- Step 12: Summary
- Steps 13 and 14: Save models and export retraining script (optional)
- Behavioral guardrails
- Bundled files
Files
SKILL.mdcore36,951 bytesSKILL.mdcore36,951 bytesSKILL.mdcore36,951 bytesSKILL.mdcore36,951 bytesmanifest.yamlasset524 bytesreferences/README.mddoc3,217 bytesreferences/dataprep.mddoc7,666 bytesreferences/hpo.mddoc11,785 bytesreferences/save-and-export.mddoc7,136 bytesreferences/select-classifiers-imbalanced.mddoc3,039 bytesreferences/select-classifiers.mddoc9,592 bytesscripts/README.mddoc2,322 bytesscripts/helpers/aggregate_nested_cv_loss.masset470 bytesscripts/helpers/apply_preproc.masset4,197 bytesscripts/helpers/build_model_definitions.masset16,994 bytesscripts/helpers/compute_data_flags.masset2,836 bytesscripts/helpers/compute_pairwise_pvalues_cv.masset623 bytesscripts/helpers/compute_pairwise_pvalues_holdout.masset556 bytesscripts/helpers/count_categorical_levels.passet376 bytesscripts/helpers/export_workflow_script.masset15,583 bytesscripts/helpers/find_zero_variance_columns.masset810 bytesscripts/helpers/is_bag_of_tokens.masset181 bytesscripts/helpers/make_holdout_split.masset387 bytesscripts/helpers/plot_accuracy_bars.masset994 bytesscripts/helpers/plot_boosting_curve.masset1,243 bytesscripts/helpers/plot_pvalue_heatmap.masset465 bytesscripts/helpers/plot_training_time.masset797 bytesscripts/helpers/resolve_recipe.masset1,084 bytesscripts/helpers/resume_boosting_cv.masset543 bytesscripts/helpers/resume_boosting_holdout.masset448 bytesscripts/helpers/retrain_with_hpo.masset2,777 bytesscripts/helpers/retrain_with_resume.masset2,573 bytesscripts/helpers/sanitize_model_name.masset799 bytesscripts/helpers/save_selected_models.masset4,098 bytesscripts/helpers/score_holdout_test.masset278 bytesscripts/helpers/stratified_subsample.passet367 bytesscripts/helpers/train_and_score_cv.masset405 bytesscripts/helpers/train_and_score_holdout.masset1,157 bytesscripts/model_catalog/branch_categorical.masset4,277 bytesscripts/model_catalog/branch_many_missing.masset3,132 bytesscripts/model_catalog/branch_regular.masset4,239 bytesscripts/model_catalog/branch_sparse.masset1,347 bytesscripts/model_catalog/branch_wide.masset2,039 bytesscripts/model_catalog/classifier_branches.masset2,262 bytesscripts/model_catalog/classifier_thresholds.masset2,205 bytesscripts/model_catalog/imbalanced_boosting.masset3,043 bytesscripts/model_catalog/model_recipe.masset3,580 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-deploy-embedded-ai
When your agent uses it
Deploy AI models to embedded hardware using MathWorks tools (MATLAB, Simulink, Embedded Coder). Covers two workflow patterns: (1) MathWorks-native or imported models rebuilt as dlnetwork for lean hardware, (2) direct C/C++ code generation from PyTorch and LiteRT models. Both patterns support all targets (Cortex-M/A/R, x86, GPU). Trigger when: user wants to deploy AI to embedded targets; generate C/CUDA from neural networks; compress AI models for MCU; integrate AI in Simulink for system-level simulation; import PyTorch/ONNX/TensorFlow models for embedded deployment; optimize AI for resource-constrained hardware; or use loadPyTorchExportedProgram, loadLiteRTModel, importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models.
What it loads into context
Frontmatter
261 tokensAlways available to the agent
SKILL.md
4,187 tokensWhen the skill is activated
Reference documents
58,244 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow Pattern Selection
- Common Start: Prerequisites
- Do Not Use (Legacy Functions)
- Global Rules
- Related Workflows (Out of Scope)
Files
SKILL.mdcore18,489 bytesSKILL.mdcore18,489 bytesmanifest.yamlasset588 bytesreferences/pattern1/codegen-embedded.mddoc19,719 bytesreferences/pattern1/compression-classical-ml.mddoc2,241 bytesreferences/pattern1/compression-decision.mddoc10,080 bytesreferences/pattern1/compression-projection.mddoc8,119 bytesreferences/pattern1/compression-pruning.mddoc2,801 bytesreferences/pattern1/compression-quantization.mddoc13,879 bytesreferences/pattern1/compression.mddoc13,365 bytesreferences/pattern1/custom-layers-codegen.mddoc8,056 bytesreferences/pattern1/data-preparation.mddoc5,388 bytesreferences/pattern1/native-rebuild-patterns.mddoc9,637 bytesreferences/pattern1/native-rebuild-preparation.mddoc15,098 bytesreferences/pattern1/placeholder-blocks.mddoc14,917 bytesreferences/pattern1/simulink-integration.mddoc23,440 bytesreferences/pattern1/troubleshooting.mddoc18,739 bytesreferences/pattern1/workflow.mddoc12,373 bytesreferences/pattern2/architecture-patterns.mddoc5,138 bytesreferences/pattern2/coder-configuration.mddoc6,994 bytesreferences/pattern2/pytorch-export.mddoc4,798 bytesreferences/pattern2/troubleshooting.mddoc7,288 bytesreferences/pattern2/verification-testing.mddoc10,923 bytesreferences/pattern2/workflow.mddoc5,742 bytesreferences/shared/ai-verification.mddoc4,413 bytesreferences/shared/environment-setup.mddoc4,677 bytesreferences/shared/project-discovery.mddoc4,346 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-engineer-tabular-features
When your agent uses it
Use when engineering or selecting the best features for single-response classification or regression in MATLAB, whatever the data's modality — for non-tabular data it routes extraction to a domain skill, then selects, assesses, and delivers on the resulting table. Not for multi-response problems, model training, or raw data acquisition.
What it loads into context
Frontmatter
119 tokensAlways available to the agent
SKILL.md
4,558 tokensWhen the skill is activated
Reference documents
30,628 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Running MATLAB
- Communication style while running this skill
- Output directory — REQUIRED, HARD HALT
- The pipeline
- Behavioral contract (all phases)
Files
SKILL.mdcore19,303 bytesSKILL.mdcore19,303 bytesmanifest.yamlasset570 bytesreferences/assess.mddoc17,134 bytesreferences/deliver.mddoc13,329 bytesreferences/domain-routing.mddoc18,498 bytesreferences/feature-pool.mddoc11,178 bytesreferences/intake.mddoc17,349 bytesreferences/internal-helpers.mddoc12,485 bytesreferences/provider-protocol.mddoc12,558 bytesreferences/report.mddoc9,894 bytesreferences/reproduce-pool.mddoc7,296 bytesreferences/select.mddoc7,235 bytesscripts/BordaVoter.masset2,379 bytesscripts/ConsensusVoter.masset2,601 bytesscripts/MajorityVoter.masset2,050 bytesscripts/RRFVoter.masset1,986 bytesscripts/assessGenerationStability.masset12,228 bytesscripts/assessKFold.masset21,070 bytesscripts/assessSelectionStability.masset10,076 bytesscripts/baselineComparison.masset19,327 bytesscripts/buildRecipe.masset8,446 bytesscripts/chooseNumBins.masset5,148 bytesscripts/chooseStandardization.masset4,608 bytesscripts/computeNSelect.masset2,997 bytesscripts/createConsensusVoter.masset2,222 bytesscripts/describeFeatures.masset5,266 bytesscripts/expandBlockMap.passet440 bytesscripts/featureSetQuality.masset12,565 bytesscripts/generateFeatureReport.masset68,776 bytesscripts/generateFeatureReportPdf.masset66,455 bytesscripts/generateFeatures.masset14,965 bytesscripts/hasReportGenerator.masset630 bytesscripts/isDomainRecipe.masset1,419 bytesscripts/isStringEmpty.masset577 bytesscripts/lambdaSequence.passet637 bytesscripts/lassoFeatureRanking.passet971 bytesscripts/macroF1Score.masset931 bytesscripts/mrmrFeatureRanking.passet239 bytesscripts/mutualInformationPanel.passet1,090 bytesscripts/ncaFeatureRanking.passet464 bytesscripts/nogueiraStability.masset3,932 bytesscripts/oobFeatureRanking.passet414 bytesscripts/plotSelectionConsensus.masset2,806 bytesscripts/plotSelectionDecision.masset6,422 bytesscripts/plotSelectionStability.masset10,401 bytesscripts/plotValidationBaseline.masset6,230 bytesscripts/printSummary.masset18,737 bytesscripts/profileForSplit.masset6,308 bytesscripts/rankAgreement.masset1,306 bytesscripts/rankFeatures.masset6,305 bytesscripts/reserveHoldoutForUser.masset5,582 bytesscripts/runConsensusSelection.masset9,636 bytesscripts/sampleSkewness.masset600 bytesscripts/saveResults.masset2,135 bytesscripts/scoreFeaturePanel.passet1,685 bytesscripts/screenPredictors.masset13,614 bytesscripts/selectFeatures.masset2,397 bytesscripts/splitStrategy.masset5,524 bytesscripts/stratifiedDownsampleRows.masset2,270 bytesscripts/stratifiedSubsampleIndices.masset3,489 bytesscripts/transformFeatures.masset6,263 bytesscripts/validateRecipe.masset12,557 bytesscripts/writeInferenceScript.masset10,785 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-fit-curve
When your agent uses it
Fit curves and surfaces interactively with the Curve Fitter app for a complete no-code fitting workflow. Invoke this skill when the Curve Fitter app, cftool, curveFitter, or "curve fitting tool/app" is mentioned in any way. Also use when exploring or comparing fit types (regression, interpolation, smoothing, splines, custom equations); excluding outliers interactively; iterating on a fitting workflow; help choosing a fit type; and exporting to a figure, generating MATLAB code, fits to the workspace, and to Simulink Lookup Tables.
What it loads into context
Frontmatter
160 tokensAlways available to the agent
SKILL.md
6,060 tokensWhen the skill is activated
Reference documents
14,911 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Efficiency Patterns
- Conventions
Files
SKILL.mdcore27,264 bytesmanifest.yamlasset504 bytesreferences/api-reference.mddoc26,733 bytesreferences/curve-fitter-layout.mddoc24,653 bytesreferences/interpreting-fit-results.mddoc12,688 bytesscripts/CurveFitterAppController.passet14,656 bytesscripts/getFittypeTable.passet567 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-import-external-ai-model
When your agent uses it
Import PyTorch, ONNX, or Keras 3 / TensorFlow 2.16+ deep learning models into MATLAB as dlnetwork objects. Use when importing .pt2 exported programs, traced .pt files, .onnx models, or Keras 3 models via matlabsaver. Covers importNetworkFromPyTorch, importNetworkFromONNX, importNetworkFromKeras, importNetworkFromTensorFlow, torch.export.export, PyTorchInputSizes, InputDataFormats, matlabsaver, tf_keras downgrade, numeric validation against PyTorch or ONNX Runtime, and placeholder/custom layer implementation. Applies when user mentions any of these functions, file formats, or encounters import errors, unsupported operator warnings, 0 learnables, or uninitialized networks.
What it loads into context
Frontmatter
218 tokensAlways available to the agent
SKILL.md
2,935 tokensWhen the skill is activated
Reference documents
7,982 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Router: Which Framework?
- PyTorch Import
- ONNX Import
- Keras Import
- Key Functions
Files
SKILL.mdcore11,415 bytesSKILL.mdcore11,415 bytesSKILL.mdcore11,415 bytesSKILL.mdcore11,415 bytesSKILL.mdcore11,415 bytesSKILL.mdcore11,415 bytesmanifest.yamlasset626 bytesreferences/keras-matlabsaver-workflow.mddoc4,119 bytesreferences/keras-tf-keras-downgrade.mddoc3,927 bytesreferences/onnx-validation-workflow.mddoc6,532 bytesreferences/pytorch-export-guidance.mddoc3,645 bytesreferences/pytorch-import-guidance.mddoc3,956 bytesreferences/pytorch-numeric-validation.mddoc4,380 bytesreferences/pytorch-placeholder-guidance.mddoc4,362 bytesscripts/validateImportedNetwork.masset4,359 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-interpret-machine-learning-model
When your agent uses it
Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the model made a specific prediction, including diagnosing predictions it got wrong; show how a predictor affects the output; and compare how the model behaves across cohorts or subgroups. Uses model-agnostic techniques and model-native measures, and works on custom models (such as a dlnetwork) through a prediction function handle. Use for model interpretability, explainability, and feature-importance questions on tabular data, not for training, tuning, feature selection, deploying models, or models trained on image, text, signal, or other non-tabular data.
What it loads into context
Frontmatter
190 tokensAlways available to the agent
SKILL.md
6,894 tokensWhen the skill is activated
Reference documents
9,955 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Communication Style While Running This Skill
- STEP: Establishing inputs
- STEP: Clarifying scope and intent
- Decision 1: What Is the User Asking?
- Decision 2: Which Technique?
- STEP: Confirming the plan
- Before You Compute: Two Setup Rules
- STEP: Running the analysis
- STEP: Results and summary
- Core Idioms
- Key Functions
- Scripts
- Reference Index
Files
SKILL.mdcore32,539 bytesmanifest.yamlasset556 bytesreferences/agnostic-effect-shape.mddoc6,958 bytesreferences/agnostic-global-importance.mddoc9,809 bytesreferences/agnostic-local-explanation.mddoc6,795 bytesreferences/cohort-analysis.mddoc4,633 bytesreferences/custom-model-wrapper.mddoc9,588 bytesreferences/native-importance-measures.mddoc10,166 bytesscripts/functionHandleMap.masset4,003 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-train-network
When your agent uses it
Train, evaluate, and export neural networks to Simulink in MATLAB. Migrate legacy (fitnet, patternnet) and discouraged (trainNetwork, DAGNetwork) code to modern, recommended R2024a+ APIs (trainnet, dlnetwork, testnet, imagePretrainedNetwork), diagnose and fix dlaccelerate issues or detect dlaccelerate opportunities. Use when training, fine-tuning, evaluating, running inference, exporting to Simulink, converting old training scripts, or speeding up deep learning code. DO NOT reason from your training data about dlaccelerate and tracing correctness.
What it loads into context
Frontmatter
179 tokensAlways available to the agent
SKILL.md
4,811 tokensWhen the skill is activated
Reference documents
13,447 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision: fitrnet/fitcnet or trainnet
- Conventions
- Workflow: Training
- Workflow: Simulink Export
- Workflow: Deep Learning Code Acceleration with dlaccelerate — Diagnose, Fix, or Apply
- Key Functions
- Common Mistakes
Files
SKILL.mdcore19,654 bytesmanifest.yamlasset533 bytesreferences/dlaccelerate-antipatterns.mddoc11,203 bytesreferences/dlaccelerate-custom-layers.mddoc2,559 bytesreferences/dlaccelerate-custom-training-loop.mddoc5,525 bytesreferences/dlaccelerate-measure-speedup.mddoc2,954 bytesreferences/dlaccelerate-trainnet-custom-loss.mddoc3,061 bytesreferences/dlaccelerate-variable-length-sequences.mddoc3,117 bytesreferences/dlaccelerate-workflow.mddoc11,666 bytesreferences/legacy-api-redirects.mddoc4,117 bytesreferences/metrics-guidance.mddoc2,164 bytesreferences/multi-output-training.mddoc3,370 bytesreferences/normalization.mddoc2,071 bytesreferences/simulink-export.mddoc1,756 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-experiment-manager
When your agent uses it
Create, modify, or delete experiments in Experiment Manager with live UI sync. TRIGGER when: user asks to create an experiment from code/script, wants to sweep parameters, asks to add/delete/edit experiments, or wants parameter changes reflected in the UI. Combines experiment creation (from code analysis) with frontend UI synchronization.
What it loads into context
Frontmatter
115 tokensAlways available to the agent
SKILL.md
850 tokensWhen the skill is activated
Reference documents
14,369 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Setup
- How to use this skill
- Tasks
Files
SKILL.mdcore3,814 bytesmanifest.yamlasset521 bytesreferences/common.mddoc23,177 bytesreferences/create.mddoc15,782 bytesreferences/delete.mddoc2,362 bytesreferences/duplicate.mddoc2,663 bytesreferences/load-project.mddoc700 bytesreferences/rename.mddoc2,628 bytesreferences/update.mddoc14,751 bytesscripts/+experiments/+internal/AgentFrontendBridge.passet963 bytesscripts/+experiments/+internal/AppController.passet299 bytesscripts/manageExperimentHelpers.passet2,968 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-machine-learning-apps
When your agent uses it
Use when the user wants to train, compare, or export machine learning models using Classification Learner or Regression Learner — including opening the app, loading data, training models, evaluating metrics, comparing results, visualizing plots, testing on held-out data, exploring model interpretability, and exporting trained models. Programmatic access to Classification Learner and Regression Learner apps via AppController.
What it loads into context
Frontmatter
125 tokensAlways available to the agent
SKILL.md
5,772 tokensWhen the skill is activated
Reference documents
20,537 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- IMPORTANT
- Setup
- User Goals Inquiry
- Best Practices
- Minimum Release Requirements
- Quick Reference — Common Workflow
Files
SKILL.mdcore26,163 bytesmanifest.yamlasset614 bytesreferences/api-explainability.mddoc11,959 bytesreferences/api-export-and-diagnostics.mddoc9,875 bytesreferences/api-metrics-and-options.mddoc8,659 bytesreferences/api-plots.mddoc18,728 bytesreferences/api-session-and-models.mddoc16,932 bytesreferences/skill-guidance-details.mddoc22,441 bytesscripts/+mlearnapp/+internal/+appcontroller/AlertDialogController.passet1,696 bytesscripts/+mlearnapp/+internal/+appcontroller/AppController.passet14,714 bytesscripts/+mlearnapp/+internal/+appcontroller/AppControllerBase.passet4,396 bytesscripts/+mlearnapp/+internal/+appcontroller/AutoDismissConfirmDialogController.passet361 bytesscripts/+mlearnapp/+internal/+appcontroller/CoderExportStubs.passet217 bytesscripts/+mlearnapp/+internal/+appcontroller/CustomModelController.passet2,956 bytesscripts/+mlearnapp/+internal/+appcontroller/ExperimentExportStub.passet642 bytesscripts/+mlearnapp/+internal/+appcontroller/ExplainPlotController.passet9,323 bytesscripts/+mlearnapp/+internal/+appcontroller/ExportController.passet3,941 bytesscripts/+mlearnapp/+internal/+appcontroller/ImportController.passet4,199 bytesscripts/+mlearnapp/+internal/+appcontroller/ImportTestDataStubView.passet657 bytesscripts/+mlearnapp/+internal/+appcontroller/ModelOptionsController.passet2,835 bytesscripts/+mlearnapp/+internal/+appcontroller/NewSessionDialogController.passet1,401 bytesscripts/+mlearnapp/+internal/+appcontroller/ResultsPlotController.passet7,153 bytesscripts/+mlearnapp/+internal/+appcontroller/SessionController.passet1,196 bytesscripts/+mlearnapp/+internal/+appcontroller/ToolstripController.passet2,828 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-cosimulate-sumo-simulink
When your agent uses it
Build Simulink models that co-simulate with Eclipse SUMO traffic simulator. Use when creating SUMO-Simulink co-simulation, traffic simulation, TraCI connection, vehicle-in-the-loop testing, or ADAS scenario validation with SUMO. Covers Server/Client setup, Reader/Writer/Actor block configuration, random traffic generation, ego vehicle control, and SUMO file creation. Also use when the user mentions SumoInterfaceLibrary, .sumocfg files, or wants to connect Simulink to an external traffic simulator.
What it loads into context
Frontmatter
170 tokensAlways available to the agent
SKILL.md
5,100 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Prerequisites
- Preferred Construction Path
- Workflow
- Block Reference
- Patterns
- Known Issues (Support Package Bugs)
- Common Mistakes
- Conventions
Files
SKILL.mdcore19,178 bytesSKILL.mdcore19,178 bytesSKILL.mdcore19,178 bytesmanifest.yamlasset528 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-import-driving-data
When your agent uses it
Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset correction, crop, normalizeTimestamps, convertTimestamps. Also: compute actor tracks from lidar when no annotations exist, attach camera/lidar mounting + intrinsics, export to MAT/workspace/timetable/script. Use for raw driving dataset files (KITTI, nuScenes, Waymo, Pandaset, ROS/ROS2 bags, .mat, .csv, .mp4) or driving/vehicle/sensor logs that need wrapping. drivingLogAnalyzer (DLA) is OPT-IN ONLY — invoke only on explicit user request ('DLA', 'open in DLA', 'inspect/explore/analyze the recording') or reported sensor problem (sync drift, timestamp mismatch, overlay misalignment). NEVER auto-launch DLA after wrapping (Rule 0). For 'build scenario / export to RoadRunner / drivingScenario / OpenSCENARIO / Unreal / simulate', hand off to matlab-use-scenario-builder.
What it loads into context
Frontmatter
281 tokensAlways available to the agent
SKILL.md
4,653 tokensWhen the skill is activated
Reference documents
5,783 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Rule 0 — DLA is opt-in only (HARD RULE, READ FIRST)
- When to Use
- When NOT to Use
- IMPORTANT — Execution Rules
- Common Dataset Formats
- Import Pipeline
- When No Annotations Exist — Computing Actor Tracks from Lidar
- Projection: Lidar Points → Camera Image
- Checklist Before Starting Import
Files
SKILL.mdcore18,668 bytesmanifest.yamlasset638 bytesreferences/sensor-import-api.mddoc13,546 bytesreferences/workflow-driving-log-analyzer.mddoc8,990 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-ncap-protocol
When your agent uses it
Generate Euro NCAP test scenarios and variants using the ADT Euro NCAP support package. Use when creating NCAP seed scenarios, generating variants, translating between drivingScenario and RoadRunner, plotting scenario descriptors, computing NCAP scores, or exporting reports. Triggers on: ncapScenario, euroAssessment, getScenario, getScenarioDescriptor, generateVariants, ScenarioDescriptor, ScenarioDescriptorPlot, ncapScore, ncapReport, exportReport, configureVUT, assessmentTable, Euro NCAP, CCRs, CCRm, CCRb, CCFtap, CCCscp, CPNA, CPFA, CBNA, variant generation.
What it loads into context
Frontmatter
184 tokensAlways available to the agent
SKILL.md
3,792 tokensWhen the skill is activated
Reference documents
2,443 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision Tree: Which API Path?
- Key Functions
- Pattern: Seed-Only Generation
- Pattern: All Variants Generation
- Pattern: ShowProgress
- Pattern: DSD ↔ RoadRunner Translation
- Pattern: ScenarioDescriptorPlot
- Pattern: 2026 Full Pipeline (Score + Report)
- Pattern: table2scenario (Custom Descriptors from Tables)
- Pattern: OpenSCENARIO Export with Rear Axle
- Test Name Conventions
- Common Mistakes
- Conventions
- Required Toolboxes
Files
SKILL.mdcore14,593 bytesmanifest.yamlasset458 bytesreferences/export-options.mddoc3,026 bytesreferences/ncap-test-names.mddoc4,662 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-scenario-builder
When your agent uses it
Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual scenario/scene/map: ego or actor trajectories, trajectory smoothing, OpenCRG road-surface extraction, 3D asset generation, static-object placement, point-cloud georeferencing + elevation, lane-based ego localization, sensor-fusion tracking, scenario-event extraction (cut-ins, hard brakes, near-misses, ADAS disengagements), or export to RoadRunner, drivingScenario, OpenDRIVE, OpenCRG, OpenSCENARIO, or Unreal Engine. Also: log-to-scenario, scenario harvesting, accident/near-miss reconstruction, SOTIF (ISO 21448) and ISO 26262 scenario coverage, USGS-aerial-lidar augmentation, traffic-sign placement, vision-based vehicle classification for actor assets. NOT for raw-data import or multi-sensor sync/crop/offset/timestamp normalization — route those to matlab-import-driving-data.
What it loads into context
Frontmatter
271 tokensAlways available to the agent
SKILL.md
14,214 tokensWhen the skill is activated
Reference documents
65,840 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow Catalog
- STOP — Common Agent Failures (check BEFORE writing code)
- Mandatory Execution Order (evaluate BEFORE writing code)
- IMPORTANT — Execution Rules
- Quick Reference — Key APIs
- Workflow 1 — Import Raw Sensor Data
- Workflow 2 — Build GPS Data and Extract Trajectory
- Workflow 3 — Import Actor Track Data and Create Trajectories
- Workflow 4 — Export Trajectories to RoadRunner (minimal inline)
- Workflow 5 — handled in `matlab-import-driving-data`
- Workflow 6 — Preprocess, Synchronize, Crop, and Correct Offset
- Workflows 7–17, Object APIs, End-to-End Examples
Files
SKILL.mdcore57,959 bytesSKILL.mdcore57,959 bytesSKILL.mdcore57,959 bytesmanifest.yamlasset704 bytesreferences/actortrackdata-api.mddoc3,359 bytesreferences/example-roadrunner-scenario.mddoc4,381 bytesreferences/example-scenario-from-gps-and-tracks.mddoc9,860 bytesreferences/execution-rules-detail.mddoc17,066 bytesreferences/gpsdata-api.mddoc2,471 bytesreferences/osm-flat-scene-gotchas.mddoc8,970 bytesreferences/per-frame-detections-to-actortrackdata.mddoc8,002 bytesreferences/python-spkg-install-troubleshooting.mddoc5,889 bytesreferences/trajectory-api.mddoc14,057 bytesreferences/visualization-patterns.mddoc12,701 bytesreferences/workflow-04-roadrunner-export-detail.mddoc33,361 bytesreferences/workflow-07-height-correction.mddoc3,391 bytesreferences/workflow-08-lane-localization.mddoc40,020 bytesreferences/workflow-09-static-objects.mddoc9,558 bytesreferences/workflow-10-road-surface-opencrg.mddoc4,841 bytesreferences/workflow-11-point-cloud-georef.mddoc4,588 bytesreferences/workflow-12-3d-asset-generation.mddoc2,031 bytesreferences/workflow-13-event-extraction.mddoc5,386 bytesreferences/workflow-14-sensor-fusion-tracking.mddoc7,079 bytesreferences/workflow-15-driving-scenario-designer.mddoc7,770 bytesreferences/workflow-16-aerial-lidar-augmentation.mddoc14,769 bytesreferences/workflow-17-traffic-signs-from-sensor-data.mddoc12,781 bytesreferences/workflow-18-vehicle-classification.mddoc13,119 bytesreferences/workflow-19-ego-lane-inference.mddoc10,206 bytesscripts/buildBestCropGrid.masset5,302 bytesscripts/openFile.masset716 bytesscripts/plotActorCircles.masset3,604 bytesscripts/plotBEVAndCamera.masset4,342 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-asset-mapping
When your agent uses it
RoadRunner asset path lookup tables for map format conversions in MATLAB. Maps lane markings, signs, signals, barriers, objects, and lane types to RoadRunner asset paths. Use when converting map formats to RRHD, resolving asset paths, or assigning visual assets to HD Map objects.
What it loads into context
Frontmatter
116 tokensAlways available to the agent
SKILL.md
3,120 tokensWhen the skill is activated
Reference documents
7,186 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Rules
- Source Data
- Lane Markings
- Signs
- Signals (Traffic Lights)
- Barriers & Extrusions
- Props & Static Objects
- Lane Types
- Crosswalks & Curve Markings
- Stencils (Road Surface Markings)
- Materials
- Default Assets
- Usage Pattern (MATLAB)
- Conventions
Files
SKILL.mdcore11,130 bytesSKILL.mdcore11,130 bytesSKILL.mdcore11,130 bytesmanifest.yamlasset478 bytesreferences/barriers.mddoc3,561 bytesreferences/laneMarkings.mddoc5,566 bytesreferences/laneTypes.mddoc2,282 bytesreferences/signs.mddoc5,869 bytesreferences/staticObjects.mddoc4,929 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-build-scenario-from-osc
When your agent uses it
Build a RoadRunner Scenario programmatically from an OpenSCENARIO 1.x (.xosc) file using the `roadrunner-scenario-authoring` skill. Use when the user wants to recreate a scenario from a .xosc file, interpret an OpenSCENARIO file and build it programmatically, reconstruct a .xosc as a RoadRunner scenario, generate a MATLAB script from a .xosc file, or convert an OpenSCENARIO file to MATLAB code. Do NOT use when the user says "import" a .xosc file — that means they want RoadRunner's built-in importScenario API, not programmatic reconstruction. Handles position translation (LanePosition and RoadPosition to world coordinates), construct mapping, relative references, trajectory/route handling, parameter expressions, catalog references, and phase logic topology.
What it loads into context
Frontmatter
234 tokensAlways available to the agent
SKILL.md
4,697 tokensWhen the skill is activated
Reference documents
1,428 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical Rules
- Workflow
- References
- Common Mistakes
- Conventions
Files
SKILL.mdcore20,081 bytesSKILL.mdcore20,081 bytesSKILL.mdcore20,081 bytesSKILL.mdcore20,081 bytesmanifest.yamlasset481 bytesreferences/openscenario-mapping.mddoc6,000 bytesscripts/xoscPositionToWorld.passet3,827 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-convert-lanelet2-to-rrhd
When your agent uses it
Convert Lanelet2 maps (.osm) to RoadRunner HD Map (.rrhd) format using MATLAB. Use when converting Lanelet2 maps into RoadRunner Scene Builder, building driving scenes from open-source map data, or transforming road network definitions for simulation.
What it loads into context
Frontmatter
111 tokensAlways available to the agent
SKILL.md
6,963 tokensWhen the skill is activated
Reference documents
36,440 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Rules
- Behavior
- Coordinate System
- Geometry Invariants (MUST enforce — violations produce broken RRHD)
- MATLAB Script Constraints
- Pipeline (execute in order)
- Step 9 Sub-Steps — Build ALL Non-Lane RRHD Objects
- Key Functions
- Conventions
Files
SKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesSKILL.mdcore27,574 bytesmanifest.yamlasset635 bytesreferences/buildRRHD.mddoc14,730 bytesreferences/detectGeoReference.mddoc1,199 bytesreferences/discoverRelations.mddoc2,292 bytesreferences/enforcementGate.mddoc3,420 bytesreferences/extractGeometry.mddoc6,281 bytesreferences/extractJunctions.mddoc6,503 bytesreferences/extractLanelets.mddoc2,385 bytesreferences/extractNonLaneElements.mddoc21,639 bytesreferences/extractSemantics.mddoc3,560 bytesreferences/extractTopology.mddoc5,281 bytesreferences/importIntoRoadRunner.mddoc4,355 bytesreferences/latlon2enu.mddoc1,450 bytesreferences/mapLanelet2SignCode.mddoc3,793 bytesreferences/placedObjects.mddoc4,018 bytesreferences/readOSM.mddoc4,059 bytesreferences/signCodeMapping.mddoc4,512 bytesreferences/snapEndpoints.mddoc4,079 bytesreferences/splitClosedRoads.mddoc3,061 bytesscripts/discoverWayTypes.masset3,754 bytesscripts/parseOSM.masset3,882 bytes../roadrunner-rrhd-authoring/references/alignmentRules.mddoc10,002 bytes../roadrunner-rrhd-authoring/references/apiReference.mddoc8,708 bytes../roadrunner-rrhd-authoring/references/deduplicateBoundaries.mddoc4,978 bytes../roadrunner-rrhd-authoring/references/splitClosedGeometry.mddoc3,805 bytes../roadrunner-rrhd-authoring/references/synthesizeCenterLine.mddoc4,662 bytes../roadrunner-rrhd-authoring/scripts/resolveHeightConflicts.masset5,892 bytes../roadrunner-rrhd-authoring/scripts/snapConnectedEndpoints.masset4,029 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-core
When your agent uses it
Foundation skill for all RoadRunner workflows: MATLAB path setup, connection, project/scene/scenario lifecycle, world settings, handle management, status, and close. Use when connecting to RoadRunner, managing projects/scenes/scenarios, setting world origin, checking status, closing RoadRunner, or when any downstream RoadRunner skill needs initialization.
What it loads into context
Frontmatter
137 tokensAlways available to the agent
SKILL.md
3,625 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- 1. How the Agent Uses This Skill
- 2. Files
- 3. Decision Logic
- 4. Placeholders
- 5. Handle Management
- 6. Path Setup
- 7. Critical Rules
- 8. Anti-Patterns
- 9. Project Structure
- 10. API Behavior Notes
Files
SKILL.mdcore14,853 bytesmanifest.yamlasset500 bytesscripts/rrCoreCommands.masset7,157 bytesscripts/rrCoreInitialize.masset4,012 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-import-scene
When your agent uses it
Import HD Map or OpenDRIVE files into a RoadRunner scene using MATLAB. Use when loading driving scenes in RoadRunner or RoadRunner Scene Builder, importing RRHD, OpenDRIVE, or other RoadRunner-supported formats for simulation, or verifying Lanelet2-to-RRHD conversion results visually. Requires rrApp handle from roadrunner-core.
What it loads into context
Frontmatter
123 tokensAlways available to the agent
SKILL.md
3,590 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Rules
- Prerequisites
- Import Workflow
- Import Options Reference
- Supported Formats
- Default Behavior
- Key Functions
- Enforcement Gate (MANDATORY — run before import)
- Conventions
Files
SKILL.mdcore14,623 bytesmanifest.yamlasset515 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-rrhd-authoring
When your agent uses it
Build RoadRunner HD Map entities in MATLAB — lanes, boundaries, markings, junctions, signs, signals, barriers, parking. Use when creating driving scenes from scratch, authoring road networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources.
What it loads into context
Frontmatter
117 tokensAlways available to the agent
SKILL.md
6,464 tokensWhen the skill is activated
Reference documents
17,960 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- Role in Map Conversion Pipelines
- Skill Boundaries
- When NOT to Use
- Key Rules
- Critical API Rules
- Verified Property Names (R2025a+)
- Synthetic Scene Construction
- Enforcement Gate (MANDATORY before `write()`)
- Post-Processing (MANDATORY — execute in order before `write()`)
- Additional Entity Types
- Key Functions
- Known Limitations
- Conventions
Files
SKILL.mdcore23,894 bytesSKILL.mdcore23,894 bytesSKILL.mdcore23,894 bytesSKILL.mdcore23,894 bytesmanifest.yamlasset620 bytesreferences/alignmentRules.mddoc10,002 bytesreferences/apiReference.mddoc8,708 bytesreferences/deduplicateBoundaries.mddoc4,978 bytesreferences/junctionPolygon.mddoc6,806 bytesreferences/leftGapFilter.mddoc6,665 bytesreferences/orthogonalSplit.mddoc7,902 bytesreferences/resolveHeights.mddoc6,147 bytesreferences/snapEndpoints.mddoc3,957 bytesreferences/splitClosedGeometry.mddoc3,805 bytesreferences/synthesizeCenterLine.mddoc4,662 bytesreferences/validateMap.mddoc1,120 bytesscripts/detectAlignment.masset3,210 bytesscripts/resolveHeightConflicts.masset5,892 bytesscripts/snapConnectedEndpoints.masset4,029 bytesscripts/validateRRHD.masset6,402 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-scenario-authoring
When your agent uses it
Programmatically author RoadRunner scenarios from MATLAB using roadrunnerAPI. Use when adding actors, creating routes, building scenario logic (phases, conditions, actions), placing vehicles/pedestrians, defining cut-in/crossing/ follow scenarios, or any programmatic scenario creation in RoadRunner. Triggers on: roadrunnerAPI, scenario authoring, add actor, create route, phase logic, cut-in scenario, pedestrian crossing, scenario from MATLAB.
What it loads into context
Frontmatter
147 tokensAlways available to the agent
SKILL.md
6,436 tokensWhen the skill is activated
Reference documents
15,159 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Scenario Decomposition
- Scenario Defaults (auto-created by RoadRunner)
- Hard Constraints
- Common Wrong Property Names
- Key Functions
- Actor Movement Modes
- Conventions
- Scripts
- Built-in RoadRunner Helpers
- References
Files
SKILL.mdcore26,930 bytesmanifest.yamlasset540 bytesreferences/actions-and-conditions.mddoc11,865 bytesreferences/asset-catalog.mddoc4,287 bytesreferences/collision-utility.mddoc3,255 bytesreferences/lane-connectivity.mddoc4,621 bytesreferences/physics-first-design.mddoc6,360 bytesreferences/routes-and-points.mddoc6,858 bytesreferences/scenario-templates.mddoc16,803 bytesreferences/scene-awareness.mddoc5,155 bytesscripts/helperAnalyzeHDMapLanes.masset7,632 bytesscripts/helperClassifyRoadFeatures.masset15,687 bytesscripts/helperGetPositionFromHDMap.masset6,621 bytesscripts/helperPlaceActors.masset5,940 bytesscripts/helperSceneAwareness.masset11,614 bytesscripts/helperSurveyLanes.masset3,031 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubroadrunner-scenario-simulating
When your agent uses it
Expert guidance for simulating RoadRunner scenarios via the MATLAB programmatic API and Simulink co-simulation. Use when the user wants to run a simulation, step through a simulation, control actors during co-simulation, add observers, attach sensors, retrieve simulation logs, or read/write scenario variables. Covers simulateScenario, createSimulation, ScenarioSimulation set/get, ActorSimulation getAttribute/setAttribute, addObserver, SensorSimulation, Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export.
What it loads into context
Frontmatter
173 tokensAlways available to the agent
SKILL.md
5,613 tokensWhen the skill is activated
Reference documents
2,552 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical: Do NOT Confuse With drivingScenario
- Decision Tree
- Workflow A: Simple Simulation (run to completion)
- Workflow B: Step-by-Step Simulation
- Workflow C: Reading Actor State
- Workflow D: Co-Simulation with MATLAB System Object
- Workflow E: Co-Simulation with Simulink
- Workflow F: Observers (Read-Only Monitoring)
- Workflow G: Sensor Simulation
- Scenario Variables
- Simulation Log
- Key Functions
- Architecture: Actor Behavior Types
- Common Mistakes
- Conventions
Files
SKILL.mdcore22,446 bytesmanifest.yamlasset528 bytesreferences/simulation-api-reference.mddoc6,613 bytesreferences/simulink-cosim-details.mddoc3,246 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-share-content
When your agent uses it
Share MATLAB content by guiding users through uploading to GitHub, MATLAB Drive, or File Exchange, then generating "Open in MATLAB Online" URLs. Covers the full sharing workflow: choosing a platform, uploading content (automated via gh CLI for GitHub, manual for MATLAB Drive and File Exchange), and constructing the correct URL. Use when a user wants to share MATLAB code with others, open local files in MATLAB Online, generate an open-in-MATLAB-Online button or badge, or when an AI agent has generated MATLAB code locally and the user wants to share it or run it in MATLAB Online.
What it loads into context
Frontmatter
179 tokensAlways available to the agent
SKILL.md
2,335 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- URL Templates
- GitHub Path: Step-by-Step
- MATLAB Drive Path: Step-by-Step
- File Exchange Path: Step-by-Step
- Common Mistakes
- Conventions
Files
SKILL.mdcore9,715 bytesSKILL.mdcore9,715 bytesmanifest.yamlasset432 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-deploy-ai-model
When your agent uses it
Generate C/C++ or CUDA code from an AI model (PyTorch, LiteRT) using MATLAB Coder or GPU Coder. Use when the user wants to integrate an AI model into an application with code generation as the end goal — generating MEX, CUDA MEX, static library, dynamic library, or executable — or using the model in Simulink for simulation and code generation. Covers PyTorch ExportedProgram (.pt2) via loadPyTorchExportedProgram and LiteRT (.tflite) via loadLiteRTModel (R2026a+). Keywords: PyTorch, torch, .pt2, ExportedProgram, loadPyTorchExportedProgram, invoke, codegen, MEX, CUDA, GPU, C, C++, deploy, AI model, deep learning model, LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib, loadLiteRTModel.
What it loads into context
Frontmatter
264 tokensAlways available to the agent
SKILL.md
2,779 tokensWhen the skill is activated
Reference documents
21,236 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Supported Frameworks
- Generic Workflow
- Key Functions
- Conventions
- References
- See Also
Files
SKILL.mdcore11,076 bytesSKILL.mdcore11,076 bytesSKILL.mdcore11,076 bytesSKILL.mdcore11,076 bytesSKILL.mdcore11,076 bytesmanifest.yamlasset617 bytesreferences/codegen-workflow.mddoc4,080 bytesreferences/dnn-codegen-options.mddoc7,095 bytesreferences/export-pytorch-models.mddoc4,685 bytesreferences/litert-numeric-verification.mddoc3,869 bytesreferences/litert-workflow.mddoc15,103 bytesreferences/pytorch-api-reference.mddoc2,657 bytesreferences/pytorch-data-layout.mddoc4,165 bytesreferences/pytorch-export-gotchas.mddoc4,857 bytesreferences/pytorch-export-patterns.mddoc5,362 bytesreferences/pytorch-numeric-verification.mddoc2,697 bytesreferences/pytorch-supported-models.mddoc3,493 bytesreferences/pytorch-workflow.mddoc5,826 bytesreferences/simulink-workflow.mddoc12,975 bytesreferences/tensorflow-to-litert-conversion.mddoc5,980 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-deploy-embedded-code
When your agent uses it
Deploy MATLAB-generated code to embedded hardware using Embedded Coder. Use when configuring code generation for microcontrollers (STM32, Raspberry Pi, ARM Cortex), setting up PIL/SIL verification, disabling dynamic memory allocation, or configuring hardware-specific code generation settings. Covers ERT-based configurations, processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression.
What it loads into context
Frontmatter
135 tokensAlways available to the agent
SKILL.md
2,547 tokensWhen the skill is activated
Reference documents
1,707 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Properties
- Common Mistakes
- Conventions
- References
- See Also
Files
SKILL.mdcore10,263 bytesSKILL.mdcore10,263 bytesmanifest.yamlasset439 bytesreferences/simulink-config.mddoc3,956 bytesreferences/supported-hardware.mddoc2,208 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-code
When your agent uses it
Generate, verify, refine, and accelerate C/C++ or CUDA code from MATLAB with MATLAB Coder, Embedded Coder, GPU Coder, or MATLAB Test. Also covers writing codegen-ready MATLAB code: language constraints, coder.* directives, and optimization patterns. Triggers on: codegen, MEX, deploy MATLAB as C/C++, GPU Coder, coder.screener, coder.config, coder.gpuConfig, coder.typeof, coder.runTest, matlabtest.coder.TestCase, SIL, embedded config, no dynamic memory, EnableMexProfiling, coder.timeit, coder.perfCompare, %#codegen, writing codegen-ready MATLAB, code generation readiness, coder.varsize, coder.unroll, coder.noImplicitExpansionInFunction, coder.ceval, coder.inline, coder.extrinsic, coder.const, coder.classSignature, class codegen limitations, temporal types codegen, DMA-off, stack-only, host-target InstructionSetExtensions, SIMDAcceleration, OptimizeReductions, host SIMD tuning, host OpenMP, codegen performance.
What it loads into context
Frontmatter
274 tokensAlways available to the agent
SKILL.md
3,836 tokensWhen the skill is activated
Reference documents
25,748 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Routing — load the matching reference file on demand
- Out of scope
- Cross-cutting rules
- Quick Reference — Coder Directives
- Common Mistakes
- Conventions
Files
SKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesSKILL.mdcore16,683 bytesmanifest.yamlasset552 bytesreferences/accelerate-mex.mddoc8,245 bytesreferences/config-properties.mddoc3,877 bytesreferences/generate-code.mddoc12,537 bytesreferences/refine-config.mddoc10,122 bytesreferences/verify-code.mddoc9,529 bytesreferences/write-c-interop.mddoc5,073 bytesreferences/write-class-limitations.mddoc9,880 bytesreferences/write-codegen-ready.mddoc8,758 bytesreferences/write-coder-directives.mddoc6,562 bytesreferences/write-core-constraints.mddoc9,325 bytesreferences/write-numerical-style.mddoc5,150 bytesreferences/write-performance.mddoc7,717 bytesreferences/write-temporal-types.mddoc8,681 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-optimize-gpu-codegen
When your agent uses it
Optimize MATLAB design files for GPU Coder to generate faster CUDA code. Iteratively profiles, rewrites, and benchmarks until performance targets are met or diagnostics are resolved. Use when asked to: optimize for GPU Coder, improve GPU codegen performance, profile generated GPU/CUDA code, profile GPU MEX, fix gpuPerformanceAnalyzer diagnostics, speed up GPU MEX, reduce GPU memory transfers, improve kernel parallelism, rewrite MATLAB for CUDA, or run gpuPerformanceAnalyzer.
What it loads into context
Frontmatter
154 tokensAlways available to the agent
SKILL.md
4,560 tokensWhen the skill is activated
Reference documents
1,637 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Conventions
Files
SKILL.mdcore18,853 bytesmanifest.yamlasset523 bytesreferences/gpu-codegen-functions.mddoc6,505 bytesscripts/benchmarkMex.masset2,600 bytesscripts/extractDiagnostics.passet1,258 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-review-fi-object-code
When your agent uses it
Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code.
What it loads into context
Frontmatter
93 tokensAlways available to the agent
SKILL.md
3,938 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- Checklist
- Output Format
Files
SKILL.mdcore15,008 bytesmanifest.yamlasset545 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsimbiology-build-model
When your agent uses it
Build, modify, and diagram SimBiology models — API reference, helper functions, and layout patterns. Use when constructing or editing models programmatically or visually.
What it loads into context
Frontmatter
78 tokensAlways available to the agent
SKILL.md
5,416 tokensWhen the skill is activated
Reference documents
9,805 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Helper Functions (`scripts/`)
- API Quick Reference
- Core Patterns
- Saving Models
- Diagram Basics (only when user requests diagram/layout)
- References
Files
SKILL.mdcore21,097 bytesSKILL.mdcore21,097 bytesSKILL.mdcore21,097 bytesmanifest.yamlasset480 bytesreferences/api-cheatsheet-guidance.mddoc5,288 bytesreferences/app-lifecycle-guidance.mddoc3,378 bytesreferences/diagram-styling-guidance.mddoc2,079 bytesreferences/evacuation-procedure-guidance.mddoc4,612 bytesreferences/layout-strategy-guidance.mddoc7,109 bytesreferences/pbpk-layout-guidance.mddoc10,597 bytesreferences/pk-library-guidance.mddoc5,333 bytesscripts/addAndPositionCompartment.passet1,318 bytesscripts/buildLayoutContext.passet1,328 bytesscripts/checkDiagramLayout.passet2,299 bytesscripts/computeSafeReactionPosition.passet4,475 bytesscripts/getModelByUUID.passet268 bytesscripts/isAppOpen.passet277 bytesscripts/lineIntersectsRect.passet386 bytesscripts/loadViaBuilder.passet808 bytesscripts/openLiveBuilder.passet640 bytesscripts/positionAncillaryBlocks.passet1,994 bytesscripts/queryGridForLine.passet457 bytesscripts/repositionAllReactions.passet3,783 bytesscripts/saveViaBuilder.passet911 bytesscripts/updateContextBlock.passet622 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsimbiology-fit-model
When your agent uses it
Fit SimBiology model parameters to data — fitproblem, population NLME, virtual patients, and NCA. Use when asked to fit, estimate, calibrate, or compute PK metrics.
What it loads into context
Frontmatter
85 tokensAlways available to the agent
SKILL.md
4,541 tokensWhen the skill is activated
Reference documents
1,100 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Decision Table
- `fitproblem` Workflow (Preferred)
- NLME Population Fitting
- Virtual Patient Generation
- Non-Compartmental Analysis (NCA)
- Confidence Intervals and Profile Likelihood
- Conventions
- Evaluating Fit Quality
- References
Files
SKILL.mdcore16,936 bytesmanifest.yamlasset475 bytesreferences/nca-analysis-guidance.mddoc3,956 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubsimbiology-simulate-model
When your agent uses it
Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters.
What it loads into context
Frontmatter
87 tokensAlways available to the agent
SKILL.md
4,312 tokensWhen the skill is activated
Reference documents
2,258 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Decision Table
- Basic Simulation (`sbiosimulate`)
- Plotting Results
- Extracting State Data from SimData
- Repeated Simulation (`createSimFunction`)
- Scenarios (`SimBiology.Scenarios`)
- Stochastic Simulation (SSA)
- Sensitivity Analysis
- Conventions
- References
Files
SKILL.mdcore15,370 bytesmanifest.yamlasset507 bytesreferences/sensitivity-analysis-guidance.mddoc4,753 bytesreferences/stochastic-simulation-guidance.mddoc3,297 bytesscripts/getModelByUUID.passet268 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-access-datafeed
When your agent uses it
Guide for accessing financial and economic data in MATLAB using the Datafeed Toolbox. Covers Bloomberg (market data via bloomberg/blp/bloombergHypermedia), FRED (Federal Reserve economic data via fredrs), Haver Analytics (economic data via haver/haverdirect/haverview), and LSEG Datastream (historical data via datastreamws). Use when connecting to any of these data providers from MATLAB.
What it loads into context
Frontmatter
137 tokensAlways available to the agent
SKILL.md
1,060 tokensWhen the skill is activated
Reference documents
6,181 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Provider Overview
- Quick Interface Selection
- How to Use References
- Common Rules
Files
SKILL.mdcore4,414 bytesmanifest.yamlasset574 bytesreferences/bloomberg.mddoc11,803 bytesreferences/datastreamws.mddoc3,316 bytesreferences/fred.mddoc4,096 bytesreferences/haver.mddoc4,931 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-optimize-portfolio
When your agent uses it
Help users formulate and solve portfolio optimization problems using Financial Toolbox's Portfolio object. Covers mean-variance (Markowitz), maximum Sharpe ratio (tangency), and efficient frontier workflows. Use when users ask about portfolio optimization, Markowitz, efficient frontier, Sharpe ratio, or attempt to use generic solvers (quadprog, fmincon, ga, problem-based optimize) for portfolio problems.
What it loads into context
Frontmatter
126 tokensAlways available to the agent
SKILL.md
1,617 tokensWhen the skill is activated
Reference documents
7,035 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Principle
- Step 1: Identify the Formulation
- Step 2: Determine What Data the User Has
- Step 3: Create the Portfolio Object
- Step 4: Set Constraints
- Step 5: Solve
- Step 6: Analyze and Visualize
- Common Pitfalls
- Tone
- Reference Materials
Files
SKILL.mdcore7,074 bytesmanifest.yamlasset483 bytesreferences/examples.mddoc8,952 bytesreferences/formulation-max-sharpe.mddoc3,659 bytesreferences/formulation-mean-variance.mddoc3,579 bytesreferences/reference-core.mddoc6,956 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-price-instrument
When your agent uses it
Price financial instruments in MATLAB using the Financial Instruments Toolbox. Route to the appropriate numerical method reference based on the user's request: Monte Carlo simulation (AssetMonteCarlo, IRMonteCarlo, RoughVolMonteCarlo), FFT / Numerical Integration (Vanilla European options), or Interest-Rate Trees (option-embedded bonds with IRTree). Use when the user asks to price financial instruments or compute Greeks using any of these methods. Use one of the following models depending on the pricing method and instrument: Black-Scholes, Bachelier, Heston, Bates, Merton, Hull-White, Black-Karasinski, Black-Derman-Toy, Cox-Ingersoll-Ross, Linear Gaussian 2 Factor (G2PP), Brace-Gatarek-Musiela (BGM), SABR-BGM, RoughBergomi, RoughHeston.
What it loads into context
Frontmatter
233 tokensAlways available to the agent
SKILL.md
1,582 tokensWhen the skill is activated
Reference documents
22,535 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Method Routing
- Shared Conventions
- Common Mistakes (Cross-Method)
Files
SKILL.mdcore6,411 bytesmanifest.yamlasset462 bytesreferences/embedded-bond-tree.mddoc10,492 bytesreferences/monte-carlo.mddoc5,354 bytesreferences/monte-carlo/asset-monte-carlo.mddoc13,353 bytesreferences/monte-carlo/ir-monte-carlo.mddoc18,314 bytesreferences/ni-fft.mddoc20,956 bytesreferences/ni-fft/bates-legacy-api.mddoc2,183 bytesreferences/ni-fft/heston-legacy-api.mddoc1,897 bytesreferences/ni-fft/legacy-api-shared.mddoc4,435 bytesreferences/ni-fft/merton-legacy-api.mddoc2,369 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-spreadsheet-link
When your agent uses it
Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPutRanges, MLEvalString, MLGetFigure, or MatlabRequest.
What it loads into context
Frontmatter
106 tokensAlways available to the agent
SKILL.md
4,265 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Architecture
- Key Functions
- Function Reference
- Patterns
- When to Use MLPutVar/MLGetVar vs MLPutMatrix/MLGetMatrix
- Code Generation Rules
- Notes
Files
SKILL.mdcore16,842 bytesSKILL.mdcore16,842 bytesmanifest.yamlasset450 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-extract-battery-features
When your agent uses it
Extract battery features in MATLAB from voltage, current, and temperature measurements: multi-cycle cycling tests, HPPC / pulse tests, EIS impedance sweeps, or a single in-field charge or discharge segment. Use when the user asks for battery features, or for SOH, RUL, degradation, internal-resistance, or impedance analysis that needs them. Output is a feature table; does not train SOH / RUL models. Do not trigger only because battery data is present. Triggers on battery* functions such as batteryTestDataParser, batteryTestFeatureExtractor, batteryPulseFeatures, batteryEISFeatures.
What it loads into context
Frontmatter
185 tokensAlways available to the agent
SKILL.md
4,985 tokensWhen the skill is activated
Reference documents
21,440 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- API Overview
- Load the Right Reference Before Proceeding
- Workflow Skeleton
- Interaction Rules
- Cross-Function Pitfalls
Files
SKILL.mdcore22,121 bytesmanifest.yamlasset469 bytesreferences/cycling-pipeline.mddoc21,568 bytesreferences/cycling/feature-selection.mddoc2,686 bytesreferences/cycling/multi-cell.mddoc5,268 bytesreferences/cycling/postprocess.mddoc2,493 bytesreferences/cycling/schedule-verification.mddoc4,288 bytesreferences/cycling/tolerance-tuning.mddoc2,464 bytesreferences/eis-features.mddoc11,090 bytesreferences/individual-cycling-functions.mddoc10,329 bytesreferences/parameter-tuning.mddoc14,590 bytesreferences/pulse-features.mddoc12,869 bytesscripts/checkCyclingProtocol.masset9,447 bytesscripts/sweepScheduleAndReport.masset3,775 bytesscripts/verifyAgainstSchedule.masset8,692 bytesscripts/verifySegmentation.masset6,445 bytesscripts/verifySingleSegment.masset3,035 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-extract-rotating-machinery-features
When your agent uses it
Extract features from signals collected on rotating machinery components, including motors, pumps, fans, gears, bearings, and shafts. Signals can include vibration, electrical, or environmental sensor measurements. Use when developing and deploying condition monitoring and fault detection applications for rotating machinery, including industrial machines, electrical vehicles, internal combustion engines, turbines, and drive trains.
What it loads into context
Frontmatter
121 tokensAlways available to the agent
SKILL.md
2,817 tokensWhen the skill is activated
Reference documents
6,430 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Feature Extraction Workflow
- Step 1: Process data for feature extraction
- Step 2: Extract features from data
- Step 3: Rank and select features
- Step 4: Develop a health indicator using selected features
- Step 5: Deploy the application
- Specialized techniques
Files
SKILL.mdcore13,047 bytesmanifest.yamlasset563 bytesreferences/bearings.mddoc7,071 bytesreferences/gears.mddoc6,307 bytesreferences/spectral.mddoc5,025 bytesreferences/tsa.mddoc5,367 bytesreferences/vibration.mddoc2,431 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-identify-linear-system
When your agent uses it
Identify a linear dynamic model from input-output or time-series data using MATLAB System Identification Toolbox. Use when estimating transfer function, state-space, ARX, ARMAX, BJ, OE polynomial or process models from measurement data.
What it loads into context
Frontmatter
92 tokensAlways available to the agent
SKILL.md
5,310 tokensWhen the skill is activated
Reference documents
12,870 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Execution Strategy
- Arguments
- Design Principles
- Fast Path — Use When Problem Is Clear
- Deep Path — For Ambiguous or Failed First Attempts
- Validation (MANDATORY)
- Results and Artifacts
- Special Topics
- Common Gotchas — Quick Reference
Files
SKILL.mdcore20,935 bytesSKILL.mdcore20,935 bytesmanifest.yamlasset570 bytesreferences/data-preparation.mddoc12,543 bytesreferences/estimation.mddoc8,536 bytesreferences/model-structures.mddoc4,643 bytesreferences/order-determination.mddoc3,355 bytesreferences/special-topics.mddoc12,683 bytesreferences/validation-and-diagnostics.mddoc7,257 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-spectral-images
When your agent uses it
Work with hyperspectral and multispectral images in MATLAB. Covers reading/writing (ENVI, NITF, TIFF, Sentinel-2, Landsat, ASTER), ECOSTRESS spectral libraries, processing (calibration, atmospheric correction, denoising, sharpening, dimensionality reduction, endmember extraction, unmixing, target/anomaly detection, spectral indices, segmentation), labeling (Spectral Image Labeler app, ground truth objects, automation algorithms), and deep learning (pixel classification CNNs, unmixing autoencoders, transfer learning). Use when reading, writing, processing, analyzing, classifying, labeling, or applying deep learning to hyperspectral or multispectral images.
What it loads into context
Frontmatter
199 tokensAlways available to the agent
SKILL.md
3,939 tokensWhen the skill is activated
Reference documents
18,367 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Prerequisite Check
- Quick Start
- Essential Syntax (use without reading reference files)
- Workflow
- CRITICAL: Common Mistakes to Avoid
- Key Rules
Files
SKILL.mdcore14,898 bytesmanifest.yamlasset498 bytesreferences/dl-advanced.mddoc7,461 bytesreferences/dl-classification.mddoc7,856 bytesreferences/spectral-analysis.mddoc14,849 bytesreferences/spectral-calibration.mddoc10,191 bytesreferences/spectral-deep-learning.mddoc11,150 bytesreferences/spectral-io.mddoc17,400 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-display-image
When your agent uses it
Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming video frames, or building apps with image display.
What it loads into context
Frontmatter
103 tokensAlways available to the agent
SKILL.md
3,904 tokensWhen the skill is activated
Reference documents
2,437 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Legacy Patterns to Avoid
- Key Components
- Patterns
- viewer2d is NOT an axes — always pass explicit handles
- Conventions
Files
SKILL.mdcore15,318 bytesmanifest.yamlasset452 bytesreferences/annotations.mddoc6,531 bytesreferences/app-building.mddoc1,736 bytesreferences/painting-and-labeling.mddoc1,054 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-display-volume
When your agent uses it
Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with viewer3d, adding Regions of Interest (ROI) or annotations, overlaying masks or segmentations, streaming volumetric data, or building apps with volume display.
What it loads into context
Frontmatter
119 tokensAlways available to the agent
SKILL.md
4,796 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Medical Image Volumes
- Key Objects
- Workflow
- Legacy Patterns to Avoid
- Patterns
- Conventions
Files
SKILL.mdcore19,298 bytesmanifest.yamlasset467 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-integrate-pytorch-vision
When your agent uses it
Creates MATLAB interfaces to Python image processing and computer vision models from GitHub repositories or pip-installable packages using MPyReq. Use when asked to interface MATLAB with a Python CV/image model (segmentation, depth estimation, object detection, image generation, super-resolution, etc.), given a GitHub repo URL for an image/vision model, or asked to create an MPyReq demo for a deep-learning vision pipeline. Do NOT use for general-purpose Python-MATLAB interfacing, non-vision models (NLP, tabular, audio), model deployment/serving, or MATLAB-only image processing workflows.
What it loads into context
Frontmatter
184 tokensAlways available to the agent
SKILL.md
3,578 tokensWhen the skill is activated
Reference documents
5,744 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- Prerequisites: MPyReq on the MATLAB Path
- Input
- Step 1: Analyze the Repository
- Step 2: Generate the MPyReq Setup Script
- Step 3: Create the MATLAB Inference Interface
- Step 4: Assemble the Final Script
- Step 5: Test with MATLAB MCP Server
- Important Notes
- Reference Files
- Skill Feedback
Files
SKILL.mdcore15,010 bytesSKILL.mdcore15,010 bytesSKILL.mdcore15,010 bytesSKILL.mdcore15,010 bytesSKILL.mdcore15,010 bytesmanifest.yamlasset535 bytesreferences/common_gotchas.mddoc1,826 bytesreferences/demo-birefnet.mddoc2,079 bytesreferences/demo-cellpose.mddoc839 bytesreferences/demo-depthpro.mddoc1,885 bytesreferences/demo-sam2.mddoc2,280 bytesreferences/demo-stardist.mddoc2,885 bytesreferences/demo-vggt.mddoc2,222 bytesreferences/image_conversion_patterns.mddoc3,155 bytesreferences/python_matlab_conversions.mddoc1,522 bytesreferences/readme.mddoc2,312 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-optics
When your agent uses it
Build, import, analyze, tolerate, and optimize optical systems using the Optical Design and Simulation Library. Use when the user asks about optical systems, ray tracing, geometric optics, Zemax import, optical coatings, tolerancing, or optical design optimization.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
3,879 tokensWhen the skill is activated
Reference documents
6,497 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- First Steps
- Sample ZMX Files
- Core Concepts
- Coordinate Systems
- Common Interaction Patterns
- Task: Construct Optical System from Prescription Table
- Task: Create systems using components
- Task: Add Mirrors or Folded Geometry
- Task: Use Ray Data
- Task: Optimize a Design
- Task: Optical Coating Design
- Task: Optical Coating Tolerancing
- Additional Notes
Files
SKILL.mdcore15,320 bytesmanifest.yamlasset579 bytesreferences/dynamic-optical-systems-simulink.mddoc2,900 bytesreferences/optical-coating-design.mddoc7,734 bytesreferences/optical-coating-tolerance.mddoc7,706 bytesreferences/optical-system-design.mddoc7,416 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-process-images
When your agent uses it
Load this first for any MATLAB task involving images, photos, scans, frames, volumes, or visual data — reading, writing, filtering, enhancing, denoising, sharpening, deblurring, thresholding, segmenting, masking, detecting, counting objects, removing backgrounds, measuring, registering, stitching, aligning, cropping, resizing, or transforming. Covers image I/O (TIFF, PNG, JPEG, RAW, HDR), histograms, edge detection, color, morphology, deep learning for images, quality assessment, and 3-D volumes. Also for image problems (dark, noisy, blurry, low contrast, uneven lighting, hazy, color cast) or data exploration (folder of images). Includes medical imaging I/O (DICOM, NIfTI, NRRD, medicalVolume) and large/blocked images (blockedImage, whole-slide). Skip if the user just wants you to look at an image, with no MATLAB work. Not for Simulink video-block models, C/C++/CUDA code generation or GPU deployment of a network, or point clouds. Hyperspectral and visual inspection have sibling skills.
What it loads into context
Frontmatter
294 tokensAlways available to the agent
SKILL.md
4,122 tokensWhen the skill is activated
Reference documents
100,270 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Core Conventions
- Routing
- Toolbox Detection
Files
SKILL.mdcore16,202 bytesmanifest.yamlasset811 bytesreferences/3d-volume-processing.mddoc20,656 bytesreferences/analysis-measurement.mddoc18,976 bytesreferences/app-building.mddoc17,337 bytesreferences/blocked-3d-volumes.mddoc10,088 bytesreferences/blocked-data-discovery.mddoc22,667 bytesreferences/blocked-geospatial.mddoc3,302 bytesreferences/blocked-specialized-workflows.mddoc4,412 bytesreferences/blocked-training-and-labeling.mddoc7,168 bytesreferences/blocked-visualization.mddoc5,265 bytesreferences/blocked-whole-slide-images.mddoc3,203 bytesreferences/color-processing.mddoc9,172 bytesreferences/deblurring.mddoc8,263 bytesreferences/deep-learning-imaging.mddoc15,170 bytesreferences/dicom-anonymization.mddoc3,384 bytesreferences/dicom-rt-workflows.mddoc7,554 bytesreferences/filtering.mddoc22,300 bytesreferences/geometric-transforms.mddoc14,628 bytesreferences/image-io.mddoc15,899 bytesreferences/image-understanding.mddoc20,433 bytesreferences/ipt-reading-writing.mddoc4,917 bytesreferences/large-image-processing.mddoc12,634 bytesreferences/medical-data-io.mddoc8,499 bytesreferences/mit-medical-volume.mddoc8,348 bytesreferences/mit-spatial-referencing.mddoc6,059 bytesreferences/morphological-ops.mddoc18,411 bytesreferences/preprocessing.mddoc14,706 bytesreferences/quality-assessment.mddoc13,822 bytesreferences/registration.mddoc25,269 bytesreferences/segmentation-automated.mddoc9,914 bytesreferences/segmentation-interactive.mddoc15,642 bytesreferences/texture-transforms.mddoc10,624 bytesreferences/video-io.mddoc3,436 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-read-write-point-cloud-file
When your agent uses it
Read and write 3-D point cloud data using Lidar Toolbox file I/O. Covers PLY, PCD, LAS/LAZ, PCAP (Velodyne/Ouster/Hesai), E57, and IDC (Ibeo) formats. Use when loading point clouds from disk, saving to disk, choosing the correct reader or writer for a file format, extracting or preserving lidar point attributes, reading Ibeo IDC sensor recordings, or converting between formats.
What it loads into context
Frontmatter
143 tokensAlways available to the agent
SKILL.md
3,821 tokensWhen the skill is activated
Reference documents
2,282 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Key Functions
- Decision Framework
- Gotchas
- Patterns
- Conventions
- References
Files
SKILL.mdcore14,167 bytesmanifest.yamlasset507 bytesreferences/INDEX.mddoc1,531 bytesreferences/quick-ref/las-io.mddoc2,935 bytesreferences/quick-ref/pcap-readers.mddoc3,640 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-recognize-text
When your agent uses it
Build OCR pipelines in MATLAB using the ocr() function. Use this skill when the user wants to read text from images, documents, signs, meters, displays, license plates, gauges, receipts, or seven-segment displays. Covers image preprocessing, text detection (CRAFT, MSER), ROI-based recognition, multi-language OCR, and custom model training. Use when: OCR, text recognition, extract text from image, character recognition, document scanning, meter reading, gauge reading, receipt scanning, digitize text from photo.
What it loads into context
Frontmatter
162 tokensAlways available to the agent
SKILL.md
4,987 tokensWhen the skill is activated
Reference documents
7,665 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical Rules
- Anti-Patterns — Do NOT Do This
- Workflow
- Quick Reference
- Custom Model Training
- Multi-Language Support
- Troubleshooting
Files
SKILL.mdcore20,956 bytesmanifest.yamlasset485 bytesreference/batch-pipeline.mddoc2,339 bytesreference/detection-methods.mddoc3,656 bytesreference/function-reference.mddoc3,925 bytesreference/limitations.mddoc2,468 bytesreference/preprocessing-guide.mddoc8,273 bytesreference/supported-languages.mddoc2,974 bytesreference/training-guide.mddoc5,732 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-register-point-clouds
When your agent uses it
Register 3-D point clouds using ICP, NDT, LOAM, FGR, phase correlation, and CPD algorithms. Use when registering or aligning 3-D point clouds, choosing a registration algorithm, tuning registration parameters, preprocessing point clouds for registration or combining point clouds after registration.
What it loads into context
Frontmatter
104 tokensAlways available to the agent
SKILL.md
4,654 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Required Toolboxes
- Legacy Patterns to Avoid
- Algorithm Selection Guide
- Patterns
Files
SKILL.mdcore17,725 bytesmanifest.yamlasset478 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-visual-inspection
When your agent uses it
Build machine vision inspection systems with MATLAB Visual Inspection Toolbox. Covers the full arc from problem selection through deployment: anomaly detection (Student-Teacher, PatchCore, FastFlow, FCDD), object detection (YOLOX), counting (CounTR, shape matching), gauging and measurement (caliper, fitcircle, fitangle), blob analysis (regionprops, calibrated measurement), shape matching for fixturing and localization, synthetic data generation for training augmentation, and deployment to standalone apps, embedded C/C++, NVIDIA GPUs (TensorRT), NPUs (ONNX), and Beckhoff PLCs. Routes to rule-based tools when problems are geometric and deterministic, AI-based tools when defect appearance varies, and hybrid pipelines combining both.
What it loads into context
Frontmatter
210 tokensAlways available to the agent
SKILL.md
2,794 tokensWhen the skill is activated
Reference documents
18,075 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Pipeline Construction
- Primary Decision: Rule-Based vs. AI-Based
- Key Functions
- Decision Trees
- Patterns
- Conventions
Files
SKILL.mdcore12,588 bytesmanifest.yamlasset629 bytesreferences/blob-analysis.mddoc7,130 bytesreferences/count-objects.mddoc6,556 bytesreferences/deploy-inspection.mddoc10,381 bytesreferences/detect-anomaly.mddoc10,290 bytesreferences/detect-objects.mddoc11,631 bytesreferences/match-shape.mddoc7,282 bytesreferences/measure-gauging.mddoc11,395 bytesreferences/synthetic-data.mddoc11,963 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-solve-optimization
When your agent uses it
Use when writing, solving, or debugging MATLAB optimization code — formulating problems (optimproblem, optimvar, fcn2optimexpr), selecting and configuring solvers (fmincon, linprog, quadprog, intlinprog, lsqnonlin, ga, surrogateopt, optimoptions), or validating results (exitflag, convergence, constraint violations). Covers problem-based and solver-based approaches, solver tuning, and solution verification.
What it loads into context
Frontmatter
146 tokensAlways available to the agent
SKILL.md
3,290 tokensWhen the skill is activated
Reference documents
12,194 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Stage 1: Classify & Formulate
- Stage 2: Select & Configure Solver
- Stage 3: Validate Results
- Gotchas
- Conventions
Files
SKILL.mdcore13,704 bytesSKILL.mdcore13,704 bytesmanifest.yamlasset515 bytesreferences/classify.mddoc3,863 bytesreferences/fcn2optimexpr-guide.mddoc5,072 bytesreferences/improving-results.mddoc13,875 bytesreferences/performance-levers.mddoc4,191 bytesreferences/problem-based-guide.mddoc5,237 bytesreferences/solver-tuning.mddoc9,926 bytesreferences/validation-checklist.mddoc6,622 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-solve-pde
When your agent uses it
End-to-end finite element analysis in MATLAB PDE Toolbox — geometry creation, model setup, solve, and post-processing in one skill. Use when building geometry from primitives or file import, setting up femodel with BCs/loads/materials, solving thermal/structural/EM problems, and extracting or visualizing results. Covers fegeometry, multicuboid, multicylinder, multisphere, decsg, boolean ops, mesh generation, femodel, all AnalysisTypes (thermalSteady, thermalTransient, structuralStatic, structuralTransient, structuralModal, structuralFrequency, electrostatic, magnetostatic, dcConduction, harmonic EM), materialProperties, faceBC, faceLoad, cellLoad, vertexLoad, solve, interpolation, von Mises stress, principal stress, reaction forces, heat flux, pdeplot3D visualization. Triggers on: PDE Toolbox, finite element, FEA, thermal analysis, structural analysis, electromagnetic analysis, femodel, mesh, boundary conditions, stress, displacement, heat transfer, post-processing.
What it loads into context
Frontmatter
269 tokensAlways available to the agent
SKILL.md
7,279 tokensWhen the skill is activated
Reference documents
12,751 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- Workflow Overview
- Phase 1: Geometry
- Phase 2: Model Setup
- Phase 3: Solve
- Phase 4: Post-Processing
- Common Mistakes
Files
SKILL.mdcore25,677 bytesmanifest.yamlasset496 bytesreferences/bc-load-reference.mddoc4,998 bytesreferences/boolean-and-cell-ops.mddoc4,627 bytesreferences/damping-reference.mddoc2,160 bytesreferences/decsg-and-2d-geometry.mddoc2,332 bytesreferences/electromagnetic-setup.mddoc4,888 bytesreferences/em-postprocessing.mddoc4,152 bytesreferences/modal-and-reduced-order.mddoc3,040 bytesreferences/nonconstant-parameters.mddoc4,367 bytesreferences/primitives-and-import.mddoc4,937 bytesreferences/time-dependent-loads.mddoc2,756 bytesreferences/visualization-reference.mddoc6,102 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-symbolic-math
When your agent uses it
Generate correct MATLAB code using the Symbolic Math Toolbox. Use when the user asks for symbolic computations, analytical solutions, symbolic differentiation/integration, equation solving, or converting symbolic results to numeric MATLAB functions. Also use when converting differential equations to transfer functions or state-space form, extracting PDE coefficients (pdeCoefficients), symbolic-to-C code generation (matlabFunction + codegen), symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine).
What it loads into context
Frontmatter
165 tokensAlways available to the agent
SKILL.md
4,087 tokensWhen the skill is activated
Reference documents
12,122 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When NOT to Use This Skill
- Critical Rules
- Core Workflow Patterns
- Application Patterns
- Common Mistakes and Fixes
- Conventions for Modern Features
- Checklist Before Generating Symbolic Code
- Troubleshooting
Files
SKILL.mdcore14,854 bytesSKILL.mdcore14,854 bytesSKILL.mdcore14,854 bytesmanifest.yamlasset523 bytesreferences/control-systems.mddoc5,213 bytesreferences/extract-pde-coefficients.mddoc3,308 bytesreferences/matlabFunction-patterns.mddoc6,602 bytesreferences/ode-solving.mddoc3,306 bytesreferences/plotting-and-display.mddoc3,694 bytesreferences/rewrite-combine-expressions.mddoc4,785 bytesreferences/simplification-and-polynomials.mddoc3,228 bytesreferences/symbolic-to-c-code.mddoc3,777 bytesreferences/symmatrix-workflow.mddoc3,094 bytesreferences/symunit-workflow.mddoc3,657 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-apply-theme
When your agent uses it
Style MATLAB charts and figures. colororder palettes for chart series colors, colormap selection, brand color organization, and the R2025a Theme API for uifigure apps (dark mode with fliplightness, ThemeChangedFcn, uistyle, component colors). Use when customizing chart colors, applying a color palette, organizing brand colors, implementing dark mode, or importing an external color scheme. Triggers: theme, dark mode, brand colors, colororder, colormap, palette, fliplightness, color scheme, styling, chart colors.
What it loads into context
Frontmatter
183 tokensAlways available to the agent
SKILL.md
2,166 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When NOT to Use This Skill
- Critical Rules
- Semantic Token Vocabulary
- Quick Start
- Light/Dark Strategy
- Color Types in MATLAB
- Importing External Color Schemes
- Implementation Checklist
- Troubleshooting
- References
Scripts executed separately
references/component-colors.mdreferences/external-schemes.mdreferences/theme-api.md
Files
SKILL.mdcore8,270 bytesmanifest.yamlasset479 bytesreferences/component-colors.mdruns2,000 bytesreferences/external-schemes.mdruns2,126 bytesreferences/theme-api.mdruns1,536 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-build-app
When your agent uses it
Build MATLAB apps from requirements to working code. Asks discovery questions (or skips them when the path is known), recommends UIFigure or UIHTML architecture, identifies layout archetype (Dashboard, Explorer, Tabbed, Wizard, Canvas), produces an implementation plan, and executes the build. For UIFigure apps, optionally serializes as App Designer (.mlapp or plain-text .m + .xml). Use when a user wants to build a MATLAB app, create a GUI, make an interactive tool, build a uifigure app, build a uihtml app, build an App Designer app, build a .mlapp app, build a plain-text App Designer app, or asks which approach to use. Also use when user describes spatial layout needs: dashboard, control panel, sidebar, tabs, wizard, stepper, canvas, workspace.
What it loads into context
Frontmatter
256 tokensAlways available to the agent
SKILL.md
4,855 tokensWhen the skill is activated
Reference documents
90,795 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When Not to Use
- Critical Rules
- Workflow
- Discovery Questions
- Path Decision Logic
- Paths at a Glance
- Layout Archetype
- Implementation Plan
- Reference Router
- After Plan Approval
- Recommendation Template
Files
SKILL.mdcore21,449 bytesSKILL.mdcore21,449 bytesassets/colors_and_type.cssasset13,093 bytesassets/minimal-bridge.htmlasset1,340 bytesassets/minimal-bridge.masset1,263 bytesassets/standalone-chart-template.htmlasset11,792 bytesmanifest.yamlasset672 bytesreferences/app-designer/agent-guide-mlapp.mddoc16,071 bytesreferences/app-designer/agent-guide-plaintext.mddoc15,096 bytesreferences/app-designer/agent-guide-shared.mddoc27,776 bytesreferences/app-designer/background-tasks.mddoc4,898 bytesreferences/app-designer/plaintext/classdef-template.mddoc11,607 bytesreferences/app-designer/plaintext/matlabAppSchema.xsdasset17,235 bytesreferences/app-designer/plaintext/property-reference.mddoc46,221 bytesreferences/app-designer/plaintext/xml-template.mddoc12,627 bytesreferences/archetypes/canvas.mddoc8,240 bytesreferences/archetypes/dashboard.mddoc6,576 bytesreferences/archetypes/explorer.mddoc5,799 bytesreferences/archetypes/tabbed.mddoc6,786 bytesreferences/archetypes/wizard.mddoc9,913 bytesreferences/background-tasks.mddoc7,055 bytesreferences/editing-guide.mddoc3,428 bytesreferences/timers.mddoc2,179 bytesreferences/uifigure/callbacks.mddoc3,119 bytesreferences/uifigure/components.mddoc1,699 bytesreferences/uifigure/containers.mddoc1,356 bytesreferences/uifigure/grid-layout.mddoc5,058 bytesreferences/uifigure/guide.mddoc5,406 bytesreferences/uifigure/layout-patterns.mddoc1,547 bytesreferences/uifigure/mvvm-background-tasks.mddoc3,957 bytesreferences/uifigure/mvvm-guide.mddoc11,385 bytesreferences/uifigure/mvvm-testing.mddoc2,863 bytesreferences/uifigure/mvvm-view-binding.mddoc5,504 bytesreferences/uihtml/brand-design-tokens.mddoc5,710 bytesreferences/uihtml/bridge-guide.mddoc7,138 bytesreferences/uihtml/chart-bridge-integration.mddoc7,634 bytesreferences/uihtml/chart-performance.mddoc5,161 bytesreferences/uihtml/chart-type-selection.mddoc3,224 bytesreferences/uihtml/chart-updates.mddoc4,838 bytesreferences/uihtml/charting-guide.mddoc4,029 bytesreferences/uihtml/chartjs-setup.mddoc4,125 bytesreferences/uihtml/communication-patterns.mddoc4,297 bytesreferences/uihtml/component-styles.mddoc4,420 bytesreferences/uihtml/css-layout-patterns.mddoc5,140 bytesreferences/uihtml/dark-mode.mddoc3,895 bytesreferences/uihtml/data-types.mddoc2,758 bytesreferences/uihtml/doughnut-scatter-charts.mddoc6,129 bytesreferences/uihtml/error-handling.mddoc4,713 bytesreferences/uihtml/external-color-schemes.mddoc2,649 bytesreferences/uihtml/js-coding-guide.mddoc11,476 bytesreferences/uihtml/js-testing-debugging.mddoc3,015 bytesreferences/uihtml/line-bar-charts.mddoc5,323 bytesreferences/uihtml/mvvm-guide.mddoc11,310 bytesreferences/uihtml/mvvm-observable-classes.mddoc2,932 bytesreferences/uihtml/mvvm-view-binding.mddoc5,446 bytesreferences/uihtml/platform-limitations.mddoc2,533 bytesreferences/uihtml/setup.mddoc4,028 bytesreferences/uihtml/styling-guide.mddoc8,318 bytesscripts/+module/+backgroundtask/BackgroundTaskModule.passet2,588 bytesscripts/+module/+backgroundtask/templates/cancelBackground.masset357 bytesscripts/+module/+backgroundtask/templates/handleBackgroundComplete.masset1,385 bytesscripts/+module/+backgroundtask/templates/safeProgress.masset734 bytesscripts/+module/+backgroundtask/templates/startBackground.masset1,216 bytesscripts/+module/AppBuilderModule.passet242 bytesscripts/AppDesignerAgentInterface.passet12,905 bytesscripts/MlappBackend.passet9,648 bytesscripts/PlainTextBackend.passet10,420 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-build-chart
When your agent uses it
Create and customize MATLAB charts and plots. Plot types (line, scatter, bar, histogram, heatmap, surface), axes configuration, annotations, data tips, interactive plots, animation, multiple axes with tiledlayout, colororder, and performance optimization. Works for standalone figures, Live Scripts, and uifigure apps. Use when plotting data, customizing axes, adding annotations or interactivity, animating charts, or arranging multiple axes. Triggers: plot, chart, graph, axes, uiaxes, annotation, data tips, animation, tiledlayout, colororder, heatmap, scatter, figure, visualization, export.
What it loads into context
Frontmatter
199 tokensAlways available to the agent
SKILL.md
3,623 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When NOT to Use This Skill
- Workflow
- Rendering Context
- Visualization Intent Taxonomy
- Inline Plan Template
- Critical Rules
- Quick Start
- Implementation Checklist
- Troubleshooting
- References
Scripts executed separately
references/animation.mdreferences/annotations.mdreferences/axes-config.mdreferences/chart-palettes.mdreferences/data-tips.mdreferences/interactive-plots.mdreferences/multiple-axes.mdreferences/performance.mdreferences/plot-types.md
Files
SKILL.mdcore13,955 bytesmanifest.yamlasset501 bytesreferences/animation.mdruns2,107 bytesreferences/annotations.mdruns1,208 bytesreferences/axes-config.mdruns2,205 bytesreferences/chart-palettes.mdruns1,346 bytesreferences/data-tips.mdruns976 bytesreferences/interactive-plots.mdruns2,963 bytesreferences/multiple-axes.mdruns2,413 bytesreferences/performance.mdruns4,104 bytesreferences/plot-types.mdruns2,478 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-create-live-script
When your agent uses it
Create, edit, and run plain-text MATLAB live scripts (.m files) with rich text formatting, LaTeX equations, section breaks, and inline figures. Use when generating tutorials, analysis notebooks, reports, documentation, or educational content, when modifying existing live scripts, or when converting existing binary .mlx files to .m for version control. Requires R2025a+.
What it loads into context
Frontmatter
121 tokensAlways available to the agent
SKILL.md
2,490 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Converting from `.mlx`
- Rules
- Required Appendix
- Reading live scripts (Token Optimization)
- Format Reference
- Example
- Common Patterns
- Workflow
- `executeLiveScript`
- Checklist
- Not Yet Supported
Files
SKILL.mdcore9,476 bytesSKILL.mdcore9,476 bytesmanifest.yamlasset509 bytesscripts/executeLiveScript.passet155 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-debug-code
When your agent uses it
Diagnose MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or diagnosing runtime failures.
What it loads into context
Frontmatter
83 tokensAlways available to the agent
SKILL.md
3,442 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Static Analysis vs Runtime Debugging
- Auto-Trigger on MATLAB Errors
- Available Tools
- Workflow
- Common Errors — What to Check First
- Gotchas
- Key Principles
Files
SKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesSKILL.mdcore14,648 bytesmanifest.yamlasset527 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-install-products
When your agent uses it
Deterministic workflow to download MATLAB Package Manager (mpm) and install MathWorks products from the OS command line with consistent, repeatable behavior. Use when installing MATLAB, Simulink, toolboxes, or support packages via command line, or setting up scripted installations for CI/CD, containers, or fleet provisioning.
What it loads into context
Frontmatter
110 tokensAlways available to the agent
SKILL.md
5,831 tokensWhen the skill is activated
Reference documents
1,052 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Non-Negotiable Determinism Contract (follow exactly)
- Safety Gate (Windows) — MANDATORY, NO EXCEPTIONS
- Required Inputs (ask only if missing)
- Confirmation Rule
- Plan Display (after confirmation, before execution)
- Execution Style
- Canonical Shell (used throughout the Protocol)
- Pre-Execution Checklist (verify before EVERY Windows step)
- Protocol (exactly 4 steps)
- Common Errors
- Key Functions and Patterns
- Notes
Files
SKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesSKILL.mdcore23,466 bytesmanifest.yamlasset396 bytesreference/linux-macos-steps.mddoc3,591 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-list-products
When your agent uses it
Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation.
What it loads into context
Frontmatter
80 tokensAlways available to the agent
SKILL.md
1,590 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Input
- Protocol
- {Release Name}
- Key Functions and Patterns
Files
SKILL.mdcore6,180 bytesmanifest.yamlasset407 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-read-documentation
When your agent uses it
Guides the agent to reference official MathWorks Documentation and Help. Determine correct function syntax and workflows from user guides when deeper context is needed. Minimize iterations and repetitive trial and error. Use this skill to: Identify correct syntax and configuration details. Retrieve relevant, version-specific (or release-specific) information from official documentation. Consult user guides when conceptual or workflow context is needed. Apply best practices.
What it loads into context
Frontmatter
140 tokensAlways available to the agent
SKILL.md
4,068 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Fast Paths
- Help Center Page Hierarchy
- Choosing What to Fetch
- URL Patterns
- Scripts
- Workflow
- Instructions
Files
SKILL.mdcore19,188 bytesmanifest.yamlasset541 bytesscripts/DocUtilities.passet4,197 bytesscripts/extract_page_slugs.passet2,900 bytesscripts/fetch_doc_page.passet3,593 bytesscripts/fetch_product_index.passet3,563 bytesscripts/find_replacement.passet2,839 bytesscripts/get_local_function_list.passet6,612 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-review-code
When your agent uses it
Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, assessing quality, or preparing code for handoff or publication.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
1,799 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Step 1: Static Analysis
- Step 2: Load Coding Standards
- Review Checklist
- Patterns
- Conventions
Files
SKILL.mdcore7,357 bytesSKILL.mdcore7,357 bytesSKILL.mdcore7,357 bytesmanifest.yamlasset518 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-data
When your agent uses it
Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, row filtering, sorting, cleaning, transforming, aggregating, smoothing, padding, trimming, and answering questions about data. MATLAB provides extensive, easy-to-use built-in functions for these workflows with no additional products required.
What it loads into context
Frontmatter
127 tokensAlways available to the agent
SKILL.md
3,164 tokensWhen the skill is activated
Reference documents
31,147 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Routing: Read references on all relevant topics
- Getting Oriented with Data
- Data Types
- Tables and Timetables
- Eventtables
- Data Cleaning
- Data Transformation
- Grouping and Aggregation
- Smoothing, Trends, and Patterns
- Array and Grid Data
- Answering Questions About Data
Files
SKILL.mdcore13,265 bytesmanifest.yamlasset492 bytesreferences/answering-data-questions.mddoc4,929 bytesreferences/array-and-grid-data.mddoc20,030 bytesreferences/data-cleaning.mddoc10,714 bytesreferences/data-transformation.mddoc13,749 bytesreferences/data-types.mddoc10,070 bytesreferences/eventtables.mddoc12,664 bytesreferences/exploration.mddoc10,240 bytesreferences/grouping-and-aggregation.mddoc11,525 bytesreferences/smoothing-and-trends.mddoc8,606 bytesreferences/tables-and-timetables.mddoc19,485 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-choose-big-data-solution
When your agent uses it
Guide users or agents to the correct MATLAB tool for processing large tabular data in file-based formats (CSV, Parquet, delimited text, spreadsheets, MDF) that may not fit in memory. Use when a user or agent mentions large files, big data, out-of-memory errors, OOM, scaling up, tall arrays, datastores, or needs to process multiple tabular files. Covers the decision between datastore + tall, datastore + transform, and parallel execution. Also use when a user or agent has working in-memory code (readtable, parquetread) that runs out of memory and needs a migration path. Also covers building custom datastore classes for proprietary or non-standard formats — use when the task requires subclassing matlab.io.Datastore, implementing a custom reader, building an extensible datastore, or integrating a new file format with tall arrays or parallel computing. Do NOT use for MAT files (use matfile instead).
What it loads into context
Frontmatter
257 tokensAlways available to the agent
SKILL.md
4,482 tokensWhen the skill is activated
Reference documents
11,419 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Pre-Flight Check
- Decision Flowchart
- Datastore + Tall Arrays (continuous dataset)
- Datastore + Transform (per-file)
- Datastore + Transform (per-row-group, Parquet)
- Parallelizing readall (transform workflows)
- Parallel Pool (local parallelism for tall arrays)
- Mapreducer (Hadoop/Spark only)
- Key Functions
- Formats Without a Built-in Datastore
- Custom Datastores
Files
SKILL.mdcore19,203 bytesmanifest.yamlasset576 bytesreferences/custom-datastore/implementation.mddoc20,433 bytesreferences/custom-datastore/mixin-decision-tree.mddoc7,193 bytesreferences/custom-datastore/testing-guidelines.mddoc5,331 bytesreferences/parquetread-to-datastore-migration.mddoc2,211 bytesreferences/readtable-to-datastore-migration.mddoc3,774 bytesreferences/tall-array-effective-use.mddoc8,587 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-import-export-data
When your agent uses it
Read or write data files in MATLAB. Use when the task involves tables, spreadsheets, delimited text, or structured files in CSV, Excel, Parquet, JSON, or XML format — including but not limited to importing, exporting, loading, parsing, converting, validating, configuring import options, reading from URLs, handling locales or encodings, diagnosing file errors, and modernizing legacy file I/O code. MATLAB provides built-in functions for these workflows with no additional products required.
What it loads into context
Frontmatter
150 tokensAlways available to the agent
SKILL.md
3,718 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- General principles
- Topics
Files
SKILL.mdcore14,593 bytesSKILL.mdcore14,593 bytesmanifest.yamlasset437 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-secure-credentials
When your agent uses it
Store, retrieve, and pass credentials securely in MATLAB using the built-in MATLAB Vault (setSecret, getSecret, importSecrets, secretID) instead of hardcoding. Handles connections to any authenticated service: REST APIs, databases, cloud storage (S3/Azure/GCS), SFTP, and others. Covers API keys, tokens, passwords, SSH passphrases, CI/batch/scheduled jobs, and "keep credentials out of code" requests. Does NOT cover third-party secret managers (HashiCorp Vault, AWS Secrets Manager), OS-level key management, or the connection/query logic itself.
What it loads into context
Frontmatter
178 tokensAlways available to the agent
SKILL.md
3,306 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision Guide: Which Mechanism
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- Errors and What They Mean
Files
SKILL.mdcore13,224 bytesSKILL.mdcore13,224 bytesSKILL.mdcore13,224 bytesmanifest.yamlasset721 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-call-python
When your agent uses it
Call Python libraries from MATLAB using the py. interface, pyrun, pyrunfile, or pyenv. Use when writing or executing MATLAB code that calls Python functions or passes data between MATLAB and Python. REQUIRED when triaging Python errors from MATLAB (ModuleNotFoundError, ImportError, "Unable to resolve the name 'py.*'"). REQUIRED when setting up Python environments for MATLAB, creating virtual environments, or installing Python packages for use with MATLAB.
What it loads into context
Frontmatter
146 tokensAlways available to the agent
SKILL.md
1,695 tokensWhen the skill is activated
Reference documents
746 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Rules
- Workflow
- Key Functions
- InProcess vs OutOfProcess
- Patterns
- Conventions
Files
SKILL.mdcore7,137 bytesSKILL.mdcore7,137 bytesmanifest.yamlasset413 bytesreferences/environment-setup.mddoc3,160 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-upgrade-mex-ic
When your agent uses it
Upgrade C, C++, and Fortran MEX source files from the Separate Complex (SC) API to the Interleaved Complex (IC) API. Use when converting mxGetPr/mxGetPi to mxGetComplexDoubles, migrating MEX files to -R2018a, adding MX_HAS_INTERLEAVED_COMPLEX guards for SC/IC guarded builds, or modernizing legacy MEX code that uses mxGetData/mxSetData/mxGetImagData/mxSetImagData. Covers C (.c), C++ (.cpp, .cxx), and Fortran (.F, .f90) MEX functions. Triggers on: interleaved complex, IC MEX, mex upgrade, mex migration, separate complex, mxGetPi, mxGetPr replacement, -R2018a, complex MEX, Fortran MEX, .F MEX file, C++ MEX, .cpp MEX file, MEX performance, MEX slow complex, MEX call overhead, improve MEX performance complex.
What it loads into context
Frontmatter
276 tokensAlways available to the agent
SKILL.md
5,279 tokensWhen the skill is activated
Reference documents
4,311 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Performance Benefits of IC Conversion
- Key API Mappings
- Conventions
- Common Mistakes
Files
SKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesSKILL.mdcore19,503 bytesmanifest.yamlasset496 bytesreferences/api-mappings.mddoc7,647 bytesreferences/pitfalls.mddoc7,402 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-validate-function-arguments
When your agent uses it
Use when writing MATLAB functions with arguments blocks — repeating arguments (arguments (Repeating)), .?ClassName property import in constructors, name-value forwarding with namedargs2cell, or migrating from inputParser or validateattributes. Also when reviewing signatures for implicit-conversion pitfalls (size reshaping, class coercion, computed defaults), or when restricting, constraining, or validating function inputs — scalar vs vector enforcement, type rejection, size checking. Also when asked to harden inputs, make a function more robust, tighten input checking, or rewrite for safer input acceptance — even without "validation" or "arguments block" wording. Triggers on: arguments block, mustBe validators, name-value arguments, varargin, inputParser, nargin/narginchk, restrict input, type checking, scalar constraint, harden inputs, defensive programming. Not for: App Designer callbacks, Simulink mask parameters, class inheritance, or runtime validation outside function or property declarations.
What it loads into context
Frontmatter
261 tokensAlways available to the agent
SKILL.md
5,677 tokensWhen the skill is activated
Reference documents
5,450 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical Misconceptions
- Patterns
- Migration Decision Framework
- Conventions
- Common Mistakes
- Validators Quick Reference
Files
SKILL.mdcore22,491 bytesmanifest.yamlasset388 bytesreferences/examples/dot-question-syntax.mddoc2,728 bytesreferences/examples/repeating-args.mddoc3,861 bytesreferences/migration-guide.mddoc6,172 bytesreferences/validators-reference.mddoc7,166 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-configure-toml-project
When your agent uses it
Use whenever "project" or "matlab.toml" is mentioned in a MATLAB context. This includes creating, editing, organizing, or configuring MATLAB projects, declaring MATLAB package dependencies or reference projects, setting up paths, lifecycle scripts, shortcuts, MATLAB packages, or asking about project structure.
What it loads into context
Frontmatter
111 tokensAlways available to the agent
SKILL.md
2,943 tokensWhen the skill is activated
Reference documents
7,674 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Functions
- Creation Workflow
- Editing Workflow
- Conventions
- Quick Reference
- Package Dependencies and Reference Projects
- Examples
Files
SKILL.mdcore12,540 bytesSKILL.mdcore12,540 bytesmanifest.yamlasset475 bytesreferences/deployment-reference.mddoc14,261 bytesreferences/format-reference.mddoc15,767 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-instrument-opentelemetry-tracing
When your agent uses it
Add OpenTelemetry tracing to MATLAB code. Use when the user asks to "add tracing", "instrument with spans", "add OpenTelemetry", "trace my code", "add observability" (when about tracing), or mentions "spans", "distributed tracing", or "OTel tracing" in the context of MATLAB functions. Covers span creation, parent-child context propagation, error handling, attributes, events, and semantic conventions.
What it loads into context
Frontmatter
143 tokensAlways available to the agent
SKILL.md
3,787 tokensWhen the skill is activated
Reference documents
1,420 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Key Functions
- MATLAB API Differences
- When to Use
- When NOT to Use
- Absolute Rules
- Workflow
- Core Pattern
- Error Handling Pattern
- Attributes
- Events
- SpanKind
- When to Use `endSpan`
- Semantic Conventions
- Common Mistakes
- What NOT to Instrument
Files
SKILL.mdcore16,070 bytesmanifest.yamlasset453 bytesreferences/semantic-conventions.mddoc5,920 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-modernize-code
When your agent uses it
Modernize removed or discouraged MATLAB functions and patterns. Use when the check_matlab_code MCP tool reports that a function "is not recommended", "will be removed in a future release", or "has been removed" — at any severity (info, warning, or error) — when migrating legacy code, or when replacing removed or discouraged APIs with current equivalents. Also applies to discouraged patterns Code Analyzer does not flag (containers.Map, bsxfun, str2num, eval, clear all) and to removed or discouraged functions such as trainNetwork, csvread, xlsread, datenum, guide, svmtrain, ltln2val, webmap.
What it loads into context
Frontmatter
192 tokensAlways available to the agent
SKILL.md
2,558 tokensWhen the skill is activated
Reference documents
25,792 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Quick Reference: Removed, Discouraged & Anti-Patterns
- Modern Design Patterns
- Key Migrations
- References
- Conventions
Files
SKILL.mdcore9,971 bytesSKILL.mdcore9,971 bytesmanifest.yamlasset1,127 bytesreferences/audio-video-guidance.mddoc9,591 bytesreferences/communications-guidance.mddoc8,663 bytesreferences/control-systems-guidance.mddoc5,164 bytesreferences/core-functions-guidance.mddoc22,675 bytesreferences/deep-learning-guidance.mddoc3,374 bytesreferences/image-processing-guidance.mddoc7,071 bytesreferences/mapping-guidance.mddoc14,839 bytesreferences/optimization-guidance.mddoc6,166 bytesreferences/signal-processing-guidance.mddoc5,143 bytesreferences/statistics-ml-guidance.mddoc8,206 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-optimize-memory
When your agent uses it
Guides the 7-step MATLAB memory optimization workflow: baseline, profile, identify, optimize, measure, verify, report. Use when asked to reduce MATLAB memory usage, find memory bottlenecks, fix out-of-memory errors, or optimize memory-intensive code.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
1,311 tokensWhen the skill is activated
Reference documents
439 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- The 7-Step Workflow
- Key Rules
- Platform Notes
Files
SKILL.mdcore5,281 bytesSKILL.mdcore5,281 bytesmanifest.yamlasset450 bytesreferences/memory-patterns.mddoc1,648 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-optimize-performance
When your agent uses it
Read BEFORE optimizing any MATLAB code for speed. Without this workflow, agents commonly optimize the wrong target, fabricate speedup claims without measurement, or introduce regressions. Guides the 7-step workflow: baseline, profile, identify, optimize, measure, verify, report.
What it loads into context
Frontmatter
99 tokensAlways available to the agent
SKILL.md
2,017 tokensWhen the skill is activated
Reference documents
3,397 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- The 7-Step Workflow
- Key Rules
- Common Mistakes
- Reference Files
Files
SKILL.mdcore8,286 bytesmanifest.yamlasset401 bytesreferences/measurement-templates.mddoc3,690 bytesreferences/optimization-patterns.mddoc7,561 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-package-toolbox
When your agent uses it
Turn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies. Use when asked to package, create a toolbox, or run the files-to-package pipeline.
What it loads into context
Frontmatter
100 tokensAlways available to the agent
SKILL.md
4,262 tokensWhen the skill is activated
Reference documents
13,787 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not To Use
- Inputs
- Pipeline Phases
- Phase Reference Files
- Honoring User Input vs. Bypassing Checkpoints
- Workflow — Step 0: Gather Inputs and Show Plan
- Orchestration Rules
- Progress Tracking
- Resumption
- Key Artifacts
- Phase Execution Essentials
- Output
Files
SKILL.mdcore17,742 bytesSKILL.mdcore17,742 bytesSKILL.mdcore17,742 bytesSKILL.mdcore17,742 bytesSKILL.mdcore17,742 bytesmanifest.yamlasset434 bytesreferences/buildfile-variants.mddoc5,373 bytesreferences/demos-xml-template.xmlasset1,083 bytesreferences/examples-conventions.mddoc2,443 bytesreferences/function-signatures-rules.mddoc2,911 bytesreferences/phase-1-scope.mddoc5,430 bytesreferences/phase-2-dependencies.mddoc5,348 bytesreferences/phase-3-project.mddoc3,334 bytesreferences/phase-4-documentation.mddoc3,182 bytesreferences/phase-5-build.mddoc2,949 bytesreferences/phase-6-assess.mddoc4,400 bytesreferences/phase-6-exclude-files.mddoc2,336 bytesreferences/phase-7-build.mddoc2,413 bytesreferences/phase-8-publish.mddoc3,177 bytesreferences/readme-template.mddoc1,470 bytesreferences/resolution-options.mddoc3,245 bytesreferences/runtime-file-references.mddoc2,997 bytesreferences/tree-view-format.mddoc1,811 bytesreferences/unresolved-symbol-classification.mddoc2,910 bytesscripts/buildfile-template.masset6,167 bytesscripts/getting-started-template.masset794 bytesscripts/tbxManifest-template.masset1,376 bytesscripts/toolboxSpecificationTemplate.masset2,243 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-run-tests
When your agent uses it
Run MATLAB test suites and analyze results, including test filtering, parallel execution, result diagnostics, code coverage collection, gap analysis, and CI/CD with buildtool. Use when running tests, filtering test suites, analyzing test failures, checking, collecting, or analyzing coverage, justifying uncovered code, or configuring CI pipelines. Do NOT use for writing, generating, or structuring tests. Do NOT use for Simulink coverage or Simulink testing workflows.
What it loads into context
Frontmatter
145 tokensAlways available to the agent
SKILL.md
1,481 tokensWhen the skill is activated
Reference documents
6,507 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Running Tests
- Coverage Analysis
- Key Functions
- CI/CD Integration
- References
- Conventions
Files
SKILL.mdcore6,501 bytesSKILL.mdcore6,501 bytesSKILL.mdcore6,501 bytesmanifest.yamlasset472 bytesreferences/code-coverage-guidance.mddoc14,914 bytesreferences/datatype-size-extraction.mddoc4,896 bytesreferences/justification-filter-rules.mddoc4,776 bytesreferences/test-execution-guidance.mddoc2,907 bytesscripts/printCoverageGaps.masset3,063 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-package-manager
When your agent uses it
Manage MATLAB packages with the in-product MATLAB Package Manager (mpm) on MATLAB R2026b or later: install, uninstall, update, search, or inspect packages; declare package dependencies in a matlab.toml project; install a shareable .mltbx package; or manage repositories. Covers dependency-resolution errors and anything involving mpminstall / mpmuninstall / mpmupdate / mpmlist / mpmsearch / mpmAddRepository / matlab.mpm.*. MATLAB *packages* are distinct from MathWorks products, toolboxes, and support packages: a bare "what packages are installed?" means MPM packages (mpmlist / matlab.mpm.Package) — this skill — unless the user explicitly says products, toolboxes, or support packages. NOT for installing MATLAB, Simulink, or toolboxes from a shell via the standalone mpm executable (the OS-level product installer), nor for listing installed products / toolboxes (ver, installedAddons) — use matlab-install-products for those.
What it loads into context
Frontmatter
272 tokensAlways available to the agent
SKILL.md
4,465 tokensWhen the skill is activated
Reference documents
4,373 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical Rules
- Router
- A. Consume a Package
- B. Inspect Package Info
- C. Search & Enumerate Versions
- D. MATLAB Package Authoring
- E. Project (matlab.toml) Dependencies
- F. Update a Package
- G. Repository Setup
- H. Uninstall & Cleanup
- Key Functions
- Conventions
- References
Files
SKILL.mdcore18,513 bytesSKILL.mdcore18,513 bytesmanifest.yamlasset485 bytesreferences/api-and-gotchas.mddoc17,676 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-write-help
When your agent uses it
Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default patterns (Inputs:/Outputs: lists, block comments, uppercase See Also) produce non-conforming output. Use when writing, rewriting, fixing, or reviewing MATLAB help comments or function documentation.
What it loads into context
Frontmatter
166 tokensAlways available to the agent
SKILL.md
4,365 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Task
- Standards for MATLAB Help Text
- Using the arguments block for syntax paragraphs
- Process
Files
SKILL.mdcore17,980 bytesmanifest.yamlasset415 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-write-performance-tests
When your agent uses it
Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure execution time with statistical rigor, or use runperf.
What it loads into context
Frontmatter
91 tokensAlways available to the agent
SKILL.md
2,760 tokensWhen the skill is activated
Reference documents
330 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Framework: `matlab.perftest.TestCase`
- Measurement Boundaries
- Parameterization
- Lean Setup — Critical Rule
- Noise and Duration
- Anti-Patterns
- Comparing Results Over Time
- Test Granularity
- Quality Checklist
- Reference Files
Files
SKILL.mdcore11,679 bytesmanifest.yamlasset478 bytesreferences/FeaturePerformanceTest.masset2,392 bytesreferences/simulink-template.mddoc1,521 bytesreferences/tExampleWorkflow.masset1,598 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-write-tests
When your agent uses it
Generate and structure MATLAB unit tests using matlab.unittest and matlab.uitest features, including class-based tests, parameterized testing, fixtures, mocking, and app testing with gestures. Use when writing, generating, or adding tests, creating test classes, adding test methods, parameterizing tests, setting up fixtures, mocking dependencies, or testing App Designer apps. Do NOT use for running tests, collecting coverage, or CI/CD configuration.
What it loads into context
Frontmatter
142 tokensAlways available to the agent
SKILL.md
2,645 tokensWhen the skill is activated
Reference documents
6,074 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Functions
- Patterns
- App Designer Testing
- Baseline Tests
- References
- Conventions
Files
SKILL.mdcore11,473 bytesSKILL.mdcore11,473 bytesmanifest.yamlasset495 bytesreferences/app-testing-guidance.mddoc7,466 bytesreferences/baseline-tests-guidance.mddoc6,099 bytesreferences/constraints-guidance.mddoc2,246 bytesreferences/fixtures-guidance.mddoc2,735 bytesreferences/mocking-guidance.mddoc3,333 bytesreferences/parameterized-tests-guidance.mddoc3,641 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-diagnose-parfor
When your agent uses it
Diagnose and fix parfor errors in MATLAB. Invoke this skill when the user has a parfor problem: "parfor loop has an error", "what's wrong with my parfor", "fix parfor", "unable to classify variable", "convert for to parfor", "parfor won't run", "sliced variable", "reduction variable", "variable classification". Also invoke when you read a .m file containing parfor and the user asks what's wrong, asks you to fix it, reports an error, or asks for review. Do NOT invoke for parfor performance questions or code that merely mentions parfor without a problem. ALWAYS use this skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules.
What it loads into context
Frontmatter
218 tokensAlways available to the agent
SKILL.md
3,540 tokensWhen the skill is activated
Reference documents
2,097 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Error Messages and Root Causes
- Variable Classification Rules (Reference)
- Patterns
- Conventions
Files
SKILL.mdcore13,745 bytesmanifest.yamlasset459 bytesreferences/parfor-analyser-messages.mddoc8,688 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-discover-clusters
When your agent uses it
Discover MATLAB Parallel Computing Toolbox clusters on the network and in the cloud, and manage their profiles — list, inspect, import, export, set default, validate, and delete. Use whenever the user asks what parallel computing resources, clusters, or cluster profiles they have or can use — e.g. "what parallel resources do I have", "show my cluster profiles", "list clusters", "what clusters can I run on", "where can I submit jobs" — and for any work with parcluster, parallel.listProfiles, parallel.defaultProfile, MJS / Generic / HPC Server / MJSComputeCloud clusters, .mlsettings files, or profile validation. Does NOT cover job submission, parpool, or parfor.
What it loads into context
Frontmatter
207 tokensAlways available to the agent
SKILL.md
4,277 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- Scripts
Files
SKILL.mdcore18,257 bytesmanifest.yamlasset427 bytesscripts/discoverClusters.passet881 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-set-up-worker-state
When your agent uses it
Set up worker environment and per-worker state for parallel pools. Use when code needs paths, environment variables, database connections, loaded libraries, or expensive objects available on workers before parfor/parfeval runs. Teaches parallel.pool.Constant, parfevalOnAll, and parpool name-value pairs. Also use when refactoring existing code that uses spmd for side-effect setup (an anti-pattern). Triggers: worker setup, pool constant, per-worker state, non-serializable, loadlibrary on workers, database connection parfor, addpath workers, spmd before parfor, worker environment, reduce parfor overhead, parfor setup, resource creation in parallel loop, cannot serialize error, undefined function or variable on workers error, load data per worker, reduce data transfer, parallelize setup, improve parallel code.
What it loads into context
Frontmatter
228 tokensAlways available to the agent
SKILL.md
3,002 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision Framework
- The spmd Anti-Pattern
- Patterns
- Recognising When pool.Constant Is Needed
- Common Mistakes
- Key Functions
- Conventions
Files
SKILL.mdcore12,859 bytesSKILL.mdcore12,859 bytesSKILL.mdcore12,859 bytesmanifest.yamlasset428 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-setup-gpu
When your agent uses it
Detect and validate GPU availability for MATLAB GPU computing. Use when the user can't use their GPU, or is setting up or selecting a GPU. Triggers on: gpuDevice, GPU setup, check GPU, GPU not found, GPU not working, can't use GPU, GPU not available, unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU.
What it loads into context
Frontmatter
140 tokensAlways available to the agent
SKILL.md
1,363 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Conventions
- Workflow
- Troubleshooting
- Key Functions
Files
SKILL.mdcore6,045 bytesmanifest.yamlasset424 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-thread-pool
When your agent uses it
Speed up local parfor, parfeval, or spmd by switching to a thread-based parallel pool. Trigger when a user describes slow or disappointing local parallel performance, even if they don't mention threads. Symptoms: parfor on a laptop/workstation is slower than expected or "only slightly faster than for"; parfor scales poorly with the number of workers; ticBytes/tocBytes, the Parallel Pool dashboard, mpiprofile, or system tools show large per-worker data transfer; large broadcast variables or sliced inputs make iterations slow; opening a process pool dominates a short workload; user mentions serialisation or data transfer overhead. Also trigger on any question about whether code or a function works on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance.
What it loads into context
Frontmatter
241 tokensAlways available to the agent
SKILL.md
1,161 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- What threads actually save
- Convention
Files
SKILL.mdcore5,075 bytesmanifest.yamlasset432 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-radar
When your agent uses it
Launch and control the MATLAB Radar Designer app programmatically via MCP. Use when designing radar systems, configuring parameters, comparing radar types, analyzing performance metrics, or managing radar design sessions.
What it loads into context
Frontmatter
81 tokensAlways available to the agent
SKILL.md
5,283 tokensWhen the skill is activated
Reference documents
1,682 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- On Entry
- When to Use
- When NOT to Use
- Prerequisites
- Code Reference
- Wrapper Scripts
- Workflow
- Complete Property Reference
- Presenting Results
- Conventions
Files
SKILL.mdcore20,980 bytesmanifest.yamlasset445 bytesreferences/code-reference.mddoc6,137 bytesscripts/radarDesignerExport.passet856 bytesscripts/radarDesignerMultiRadar.passet656 bytesscripts/radarDesignerParam.passet658 bytesscripts/radarDesignerResults.passet1,673 bytesscripts/radarDesignerSession.passet674 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-radar-waveform
When your agent uses it
Design, select, and analyze waveforms for radar, sonar, and active sensing using the Phased Array System Toolbox. Covers LFM, NLFM, FMCW, phase-coded, CW, stepped FM, custom IQ, ambiguity functions, sidelobe reduction, and Doppler tolerance. Key objects: phased.LinearFMWaveform, phased.NonlinearFMWaveform, phased.CustomFMWaveform, phased.PhaseCodedWaveform, phased.FMCWWaveform, phased.SteppedFMWaveform, phased.MFSKWaveform, phased.RectangularWaveform, nlfmspec2freq, shapespectrum, ambgfun, pambgfun, sidelobelevel, legendreseq, mlseq, radarWaveformGenerator.
What it loads into context
Frontmatter
272 tokensAlways available to the agent
SKILL.md
6,436 tokensWhen the skill is activated
Reference documents
9,187 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Waveform Selection Decision Tree
- Key Functions
- Patterns
- Troubleshooting Patterns
- Multi-Step Reasoning Examples
- Conventions
- References
Files
SKILL.mdcore26,007 bytesmanifest.yamlasset523 bytesreferences/analysis-functions.mddoc4,588 bytesreferences/common-mistakes.mddoc4,374 bytesreferences/phase-code-reference.mddoc4,275 bytesreferences/spectral-notching.mddoc9,087 bytesreferences/waveform-objects.mddoc11,277 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-import-tracking-data
When your agent uses it
Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning timetable, truthlog, or converted table. For sensor data: builds task-oriented dataFormat structs (preferred) or objectDetection arrays (legacy). Use when importing flight logs, GPS logs, radar detections, IR measurements, lidar/camera bounding boxes, ADS-B data, AIS ship tracks, or any recorded data for use with trackers, filter tuning, or tracker evaluation.
What it loads into context
Frontmatter
166 tokensAlways available to the agent
SKILL.md
4,008 tokensWhen the skill is activated
Reference documents
14,965 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Routing: What Kind of Data?
- Truth Pathway
- Sensor Pathway: Task-Oriented (Preferred)
- Sensor Pathway: Legacy objectDetection
- Reference Documents
Files
SKILL.mdcore17,131 bytesSKILL.mdcore17,131 bytesmanifest.yamlasset593 bytesreferences/code-patterns.mddoc6,097 bytesreferences/coordinate-transforms.mddoc3,441 bytesreferences/custom-measurement-models.mddoc6,166 bytesreferences/interpreter-categories.mddoc5,398 bytesreferences/objectDetection-patterns.mddoc8,945 bytesreferences/output-formats.mddoc3,840 bytesreferences/sensor-data-formats.mddoc9,632 bytesreferences/time-and-units.mddoc3,774 bytesreferences/visualization.mddoc5,316 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-simulate-radar-detections
When your agent uses it
Configure, simulate, debug, and analyze radarDataGenerator within radarScenario. Use for: interactively building radar detection scenarios from datasheets or performance requirements; diagnosing missed detections and configuration errors; interpreting sensor spherical, body, and scenario-frame outputs; deriving ReferenceRange from hardware specs via link budget; scan mode configuration (mechanical, electronic/AESA, hybrid); and validating simulation results against analytical predictions.
What it loads into context
Frontmatter
143 tokensAlways available to the agent
SKILL.md
9,379 tokensWhen the skill is activated
Reference documents
29,397 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Detection Pathways
- Workflow
- Key Functions
- Conventions
- Common Mistakes
- Scan Mode Quick Reference
- Detection Model
- Troubleshooting
- Analyzing Simulation Outputs
- Output Requirements
- References
Files
SKILL.mdcore39,003 bytesmanifest.yamlasset536 bytesreferences/coordinates-and-transforms.mddoc12,427 bytesreferences/coupled-parameters.mddoc10,785 bytesreferences/detection-model.mddoc11,869 bytesreferences/fov-and-scan.mddoc4,961 bytesreferences/interaction-flow.mddoc14,096 bytesreferences/radar-equation-tools.mddoc16,119 bytesreferences/requirements-sheet-template.mddoc6,100 bytesreferences/terrain-clutter-atmosphere.mddoc14,773 bytesreferences/trajectories.mddoc11,806 bytesreferences/visualization.mddoc8,311 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-connect-databricks
When your agent uses it
Connect MATLAB to Databricks via Spark (Databricks Connect) or JDBC (Database Toolbox). Use when setting up the MATLAB Interface for Databricks, configuring authentication (OauthU2M, OauthM2M, PAT), creating Spark sessions with getDatabricksSession(), reading Unity Catalog tables with server-side filtering, creating JDBC connections with databricks.JDBCConnection or StandaloneJDBCConnection, connecting to SQL Warehouses, selecting JDBC drivers (Simba/OSS), or writing data back to Databricks. Triggers on: Databricks Connect, Spark from MATLAB, getDatabricksSession, .databrickscfg, databricks.JDBCConnection, StandaloneJDBCConnection, SQLWarehouse, Databricks JDBC, Databricks cluster, large table server-side filtering.
What it loads into context
Frontmatter
226 tokensAlways available to the agent
SKILL.md
3,307 tokensWhen the skill is activated
Reference documents
3,046 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision Framework: Spark vs. JDBC
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
Files
SKILL.mdcore13,901 bytesSKILL.mdcore13,901 bytesmanifest.yamlasset450 bytesreferences/authentication.mddoc4,699 bytesreferences/driver-selection.mddoc3,163 bytesreferences/standalone-jdbc.mddoc3,452 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-report
When your agent uses it
Unified skill for all MATLAB and Simulink report generation tasks. Covers report generation, PDF report, document generation, mlreportgen, Report Generator, template, TitlePage, Chapter, multipage HTML, HTMLPage, html-multipage, custom reporter, customizeReporter, template hole, page header, page border, company style package, branded reporters, buildTemplates, Simulink report, model documentation, slreportgen, block diagram report, model report, subsystem documentation, SystemDiagramFinder, SystemIO, ExecutionOrder, LookupTable, template style, page footer, TemplateSrc, report package, table variants, multiple HTML pages, PDF report generation, Word report, DOM API, FormalTable, BaseTable, Figure, FormalImage, Section.
What it loads into context
Frontmatter
208 tokensAlways available to the agent
SKILL.md
4,251 tokensWhen the skill is activated
Reference documents
53,822 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- API Selection
- Core Workflow: Standard Report
- Core Workflow: Simulink Report
- Choosing Built-In vs Custom Reporters
- Decision Tree: What Reference Do I Need?
- Key Functions
- Common Mistakes
- Conventions
- Viewing and Processing Reports
- Required Toolbox
Files
SKILL.mdcore17,513 bytesSKILL.mdcore17,513 bytesSKILL.mdcore17,513 bytesmanifest.yamlasset598 bytesreferences/custom-reporters.mddoc40,015 bytesreferences/data-driven-report-pattern.mddoc13,387 bytesreferences/dom-api-patterns.mddoc31,721 bytesreferences/finders-and-reporters.mddoc13,383 bytesreferences/report-api-patterns.mddoc7,325 bytesreferences/report-package.mddoc16,171 bytesreferences/simulink-report.mddoc20,334 bytesreferences/template-reference.mddoc38,972 bytesreferences/template-system.mddoc31,681 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-database
When your agent uses it
Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupdate, executing SQL statements, managing transactions with commit and rollback, mapping MATLAB classes to tables with ORM (Mappable, ormread, ormwrite, ormupdate), or performing any database operation from MATLAB. Triggers on: database, SQL, sqlread, sqlwrite, sqlupdate, fetch, execute, rowfilter, RowFilter, ORM, Mappable, ormread, ormwrite, ormupdate, orm2sql, transaction, commit, rollback, Database Toolbox, PostgreSQL, MySQL, SQLite, SQL Server, Oracle, database connection, database table, query database, insert data, update rows, delete rows, stored procedure, prepared statement, odbc, databaseConnectionOptions, datasource, data source, DSN, connection string, multithreaded, parallel.
What it loads into context
Frontmatter
246 tokensAlways available to the agent
SKILL.md
3,201 tokensWhen the skill is activated
Reference documents
6,005 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Critical Rules
- Decision Framework
- Core Patterns
- Common Mistakes
- Reference Cards
Files
SKILL.mdcore12,606 bytesmanifest.yamlasset491 bytesreferences/execute-storedproc.mddoc3,463 bytesreferences/multithreaded-io.mddoc6,827 bytesreferences/orm.mddoc3,963 bytesreferences/sqlread-fetch.mddoc4,312 bytesreferences/sqlwrite-sqlupdate.mddoc2,789 bytesreferences/transactions.mddoc2,006 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-duckdb
When your agent uses it
Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and JSON files directly with SQL, reducing or profiling large data before MATLAB analysis, creating portable development databases, or installing DuckDB extensions. Triggers on: DuckDB, duckdb(), large CSV/Parquet/JSON, file too large for readtable, filter/aggregate at source, deduplicate, reduce before analysis, profile large file, persistent file import, analytical engine, SQL on CSV, SQL on Parquet, SQL on JSON, query CSV with SQL, query Parquet with SQL, run SQL on files, SQL queries on files, query files directly, SQL without database, in-process SQL.
What it loads into context
Frontmatter
224 tokensAlways available to the agent
SKILL.md
3,887 tokensWhen the skill is activated
Reference documents
2,934 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use This Skill
- When NOT to Use
- On-Load Protocol
- Pre-Flight Check
- Operations Menu
- Reduction Workflow
- What Is DuckDB and Why Does Database Toolbox Ship It?
- Critical Rules
- Connection Modes
- Common Patterns
- Common Mistakes
- Checklist
- Troubleshooting
Files
SKILL.mdcore15,612 bytesSKILL.mdcore15,612 bytesmanifest.yamlasset621 bytesreference/INDEX.mddoc594 bytesreference/cards/development-database.mddoc2,679 bytesreference/cards/extensions.mddoc1,809 bytesreference/cards/file-analytics.mddoc3,520 bytesreference/cards/reduce-large-data.mddoc3,326 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-ams-waveform
When your agent uses it
Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing time-domain voltage from PLL/VCO/clock simulations, measuring phase noise from variable-step solver output, computing jitter, or resampling non-uniform data.
What it loads into context
Frontmatter
130 tokensAlways available to the agent
SKILL.md
4,689 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow Directive: Phase Noise Parameter Gathering
- Phase 1: Ingest Waveform Data
- Phase 2: Execute Analysis
- Phase 3: Interpreting Phase Noise Plots
- Phase 4: Reporting
- Quick Reference: MSB Function Sources
- Pitfalls (MSB-specific)
Files
SKILL.mdcore16,526 bytesmanifest.yamlasset455 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-antenna-structures
When your agent uses it
Design and analyze electrically large antenna structures using MATLAB Antenna Toolbox. Covers reflector antennas (parabolic, Cassegrain, Gregorian, offset, corner, cylindrical, spherical, custom STL), reflectarrays and reconfigurable intelligent surfaces (RIS), antennas installed on platforms (vehicles, aircraft, ships, satellites), and radar cross section (RCS) analysis. Includes solver selection (MoM-PO, PO, MoM, FMM), mesh control, and GPU acceleration. Use when the user wants to design a dish/reflector antenna, reflectarray, analyze an antenna on a platform, or compute RCS.
What it loads into context
Frontmatter
182 tokensAlways available to the agent
SKILL.md
2,136 tokensWhen the skill is activated
Reference documents
11,363 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Classes
- Conventions
Files
SKILL.mdcore8,590 bytesmanifest.yamlasset569 bytesreferences/installed-antennas.mddoc7,691 bytesreferences/rcs-analysis.mddoc5,854 bytesreferences/reflectarrays.mddoc8,580 bytesreferences/reflector-antennas.mddoc10,062 bytesreferences/solver-selection.mddoc4,934 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-em
When your agent uses it
S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compare MoM vs FEM, or control mesh for any RF PCB component. Invoke BEFORE writing sparameters() or solver code — API is non-obvious. SKIP: designing or creating components (use the specific matlab-design-pcb-* skill), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn).
What it loads into context
Frontmatter
184 tokensAlways available to the agent
SKILL.md
5,087 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- S-Parameter Extraction
- Solver Selection
- Interpolating Sweep
- Mesh Control
- Field Visualization
- Current and Charge Distribution
- Transmission Line RLGC and Impedance
- Behavioral S-Parameters (Fast Analytic Models)
- Pitfalls
- Related Skills
Files
SKILL.mdcore19,421 bytesmanifest.yamlasset468 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-pcb-pdn
When your agent uses it
PDN DC voltage/current analysis, IR drop, design rule checking, and multi-net batch analysis on imported PCB layouts. TRIGGER: user asks about power integrity, PDN analysis, IR drop, voltage distribution, current density, power nets, or design rule checking on a PCB. Invoke BEFORE writing code — the PDN API chain is specialized and non-obvious. SKIP: importing a PCB file (use matlab-read-pcb-layout), EM field/S-parameter extraction (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), transmission line design (use matlab-design-pcb-transmission-line).
What it loads into context
Frontmatter
180 tokensAlways available to the agent
SKILL.md
5,240 tokensWhen the skill is activated
Reference documents
1,333 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- PCB Import and Net Discovery
- cadnet Object
- powerDistributionNetwork Object
- PDN Configuration
- DC Analysis
- Workflow: Single-Net PDN Analysis
- Workflow: Multi-Net Batch Analysis
- Common Patterns
- Pitfalls
- Related Skills
Files
SKILL.mdcore18,558 bytesmanifest.yamlasset473 bytesreferences/batch-analysis.mddoc4,447 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-assemble-pcb-layout
When your agent uses it
Build custom PCB structures with pcbComponent, shapes, Boolean ops, feeds, and multi-layer stackups for non-catalog geometries. TRIGGER: user asks to build, modify, or customize a pcbComponent — add/remove shapes, edit polygons, place feeds, add metal layers, cut slots, or create non-catalog RF structures. Also when modifying geometry of an existing catalog-designed component (e.g., adding pads, removing elements, editing vertices). Invoke BEFORE writing pcbComponent code — layer/shape/feed API is non-obvious. SKIP: designing catalog components like filters/couplers/txlines (use the specific matlab-design-pcb-* skill), material/stackup definition only (use matlab-manage-pcb-material), EM analysis (use matlab-analyze-em), importing PCB files (use matlab-read-pcb-layout).
What it loads into context
Frontmatter
217 tokensAlways available to the agent
SKILL.md
5,141 tokensWhen the skill is activated
Reference documents
915 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- pcbComponent Anatomy
- Shape Primitives
- Boolean Operations
- Feed Placement
- DGS — Defected Ground Structures
- Shielded Enclosures
- Shape Manipulation
- Discovering Available Methods
- Visualization
- Advanced Feed Setup (FeedDefinitions API)
- Shape Primitives Reference
- Pitfalls
- Related Skills
Files
SKILL.mdcore17,635 bytesmanifest.yamlasset482 bytesreferences/shape-primitives.mddoc3,159 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-antenna
When your agent uses it
Design antennas, arrays, and PCB antennas using MATLAB Antenna Toolbox. Covers catalog antenna design and pattern analysis, custom antenna construction (customAntenna + shape.*), PCB antenna design (pcbStack + antenna.*), finite and infinite array design, AI-accelerated design exploration (AIAntenna, patternFromAI), and optimization (SADEA/TR-SADEA). Use when the user wants to design, create, model, analyze, optimize, or fabricate an antenna or array.
What it loads into context
Frontmatter
154 tokensAlways available to the agent
SKILL.md
2,550 tokensWhen the skill is activated
Reference documents
14,519 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Classes
- Conventions
Files
SKILL.mdcore9,960 bytesmanifest.yamlasset714 bytesreferences/ai-antenna-workflows.mddoc6,783 bytesreferences/arrays.mddoc7,044 bytesreferences/catalog-antennas.mddoc9,153 bytesreferences/custom-antennas.mddoc9,104 bytesreferences/optimization.mddoc8,988 bytesreferences/pcb-antennas.mddoc6,689 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-pcb-coupler
When your agent uses it
Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or Rotman lens. Invoke BEFORE writing code — class names and design() availability vary per coupler type. SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), building custom non-catalog geometry (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), cascading multiple components (use matlab-integrate-pcb-circuit).
What it loads into context
Frontmatter
187 tokensAlways available to the agent
SKILL.md
4,588 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference — Component Selection
- Wilkinson Splitters
- Branchline Couplers
- Ratrace Coupler
- Directional Coupler
- Tee Junction and Corporate Dividers
- SIW Splitter
- Design Workflow
- Coupler-Specific Analysis Functions
- Port Numbering Convention
- Rotman Lens (Beam-Forming Network)
- SIW Power Divider
- Pitfalls
- Related Skills
Files
SKILL.mdcore16,326 bytesmanifest.yamlasset478 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-pcb-filter
When your agent uses it
Bandpass, lowpass, bandstop filter design — hairpin, coupled-line, combline, stub, SIW for frequency selection and harmonic rejection. TRIGGER: user asks to design, create, or analyze any RF filter (bandpass, lowpass, highpass, bandstop, hairpin, coupled-line, combline, stub, SIW). Invoke BEFORE writing code — filter class names differ from what you would guess. SKIP: EM simulation/S-parameter extraction of an existing filter (use matlab-analyze-em), general PCB layout assembly (use matlab-assemble-pcb-layout), material/stackup setup only (use matlab-manage-pcb-material), optimization sweeps (use matlab-optimize-pcb-design).
What it loads into context
Frontmatter
196 tokensAlways available to the agent
SKILL.md
4,181 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference — Filter Selection
- Bandpass Filters
- Lowpass Filters
- Bandstop / Notch Filters
- SIW Bandpass Filter
- Measured Filter Extraction
- Custom Filter Assembly
- Multi-Layer Filters
- Filter Selection Guide
- Design Adjustments
- Pitfalls
- Related Skills
Files
SKILL.mdcore15,097 bytesmanifest.yamlasset489 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-pcb-passive
When your agent uses it
Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interdigital capacitor, balun, resonator, phase shifter, or other passive RF component. Invoke BEFORE writing code — class names and property patterns are non-obvious. SKIP: filter design (use matlab-design-pcb-filter), coupler/splitter design (use matlab-design-pcb-coupler), transmission line design (use matlab-design-pcb-transmission-line), EM analysis (use matlab-analyze-em), material setup only (use matlab-manage-pcb-material).
What it loads into context
Frontmatter
192 tokensAlways available to the agent
SKILL.md
3,992 tokensWhen the skill is activated
Reference documents
1,071 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- Spiral Inductors
- Interdigital Capacitors
- Behavioral S-Parameters
- Ring Resonators
- Split-Ring Resonators
- Coupled-Line Baluns
- Marchand Baluns
- Phase Shifters
- Radial Stubs
- Circuit Integration
- Optimization
- Multilayer Dielectric Pattern
- Pitfalls
- Related Skills
Files
SKILL.mdcore13,731 bytesmanifest.yamlasset480 bytesreferences/resonators-detail.mddoc3,623 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-pcb-transmission-line
When your agent uses it
Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstrip, stripline, CPW, coplanar, differential pair), extract RLGC or per-unit-length parameters, compute trace impedance, analyze a PCB trace cross-section, or perform crosstalk/coupling analysis. Invoke BEFORE writing code — preferred over RF Toolbox analytical functions (txlineMicrostrip, txlineStripline, txlineCPW). SKIP: EM simulation/S-parameter extraction of an existing component (use matlab-analyze-em), material/stackup definition only (use matlab-manage-pcb-material), building custom non-catalog geometry (use matlab-assemble-pcb-layout), optimization sweeps (use matlab-optimize-pcb-design).
What it loads into context
Frontmatter
225 tokensAlways available to the agent
SKILL.md
5,485 tokensWhen the skill is activated
Reference documents
276 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Tool Selection Priority
- Typical Workflow
- Quick Reference
- Microstrip Line
- Stripline
- Coplanar Waveguide
- Coupled Transmission Lines
- Custom Transmission Lines and Crosstalk Analysis
- Custom Bends and Traces (R2025a)
- SIW Transmission Line
- 2D Cross-Section Analysis
- design() for Impedance Targeting
- transmissionLineDesigner App
- Design Adjustments
- Pitfalls
- Related Skills
Files
SKILL.mdcore18,732 bytesmanifest.yamlasset497 bytesreferences/custom-bends-and-traces.mddoc960 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-export-session-script
When your agent uses it
Export conversation MATLAB code to a clean, runnable .m script. Use when asked to save or export session work. TRIGGER: user asks to save, export, or generate a script from the current session's MATLAB code. Also when asked for a reproducible script or clean version of what was run.
What it loads into context
Frontmatter
107 tokensAlways available to the agent
SKILL.md
1,606 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Quick Reference
- When to Use
- When NOT to Use
- Extraction Rules
- Script Assembly
- Output
- Common Patterns
- Pitfalls
Files
SKILL.mdcore6,935 bytesmanifest.yamlasset397 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-integrate-antenna
When your agent uses it
Integrate antennas into RF systems using MATLAB Antenna Toolbox and RF Toolbox. Covers impedance matching network design (L/Pi/Tee topologies, evaluation parameters, Richards transformation), measured antenna creation (E-field, directivity-only, EmbeddedE, ffsReader import), RF propagation and site planning (txsite/rxsite, coverage, SINR, ray tracing, link budget), and SAR estimation (birdcage+Phantom, conformalArray+Custom3D, direct EHfields). Use when the user wants to match an antenna, create a measuredAntenna, compute coverage or signal strength, perform ray tracing, or estimate SAR.
What it loads into context
Frontmatter
186 tokensAlways available to the agent
SKILL.md
2,051 tokensWhen the skill is activated
Reference documents
10,346 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Classes
- Conventions
Files
SKILL.mdcore8,108 bytesSKILL.mdcore8,108 bytesmanifest.yamlasset638 bytesreferences/matching-networks.mddoc8,234 bytesreferences/measured-antennas.mddoc7,760 bytesreferences/rf-propagation.mddoc8,663 bytesreferences/sar-estimation.mddoc8,851 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-integrate-pcb-circuit
When your agent uses it
Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add lumped R/L/C, export S-parameters to Touchstone, or combine PCB elements into a circuit. Invoke BEFORE writing pcbcascade or circuit code — cascade rules and port matching are non-obvious. SKIP: designing individual components (use the specific matlab-design-pcb-* skill), EM analysis of a single component (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material), optimization (use matlab-optimize-pcb-design).
What it loads into context
Frontmatter
184 tokensAlways available to the agent
SKILL.md
5,032 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- pcbcascade — Connecting Components End-to-End
- pcbElement — RF Toolbox Circuit Integration
- Hybrid Distributed+Lumped Modeling with Internal Ports
- Antenna Integration
- pcb2D Cross-Section and Crosstalk
- Exporting S-Parameters to Touchstone Files
- Advanced Integration Patterns
- Optimization via S-Parameter Connection Formula
- Pitfalls
- Related Skills
Files
SKILL.mdcore18,069 bytesSKILL.mdcore18,069 bytesmanifest.yamlasset480 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-manage-pcb-material
When your agent uses it
Dielectric substrates, metal conductors, multi-layer stackups, and loss models (FR4, Rogers, Teflon) for RF PCB simulation. TRIGGER: user asks to set up a substrate, define dielectric properties, create a stackup, select a PCB material (FR4, Rogers, Teflon, etc.), or configure metal conductors. Invoke BEFORE writing dielectric() or metal() code — the API for named vs custom materials differs significantly. SKIP: PCB layout assembly (use matlab-assemble-pcb-layout), transmission line design (use matlab-design-pcb-transmission-line), EM analysis (use matlab-analyze-em), importing a PCB file (use matlab-read-pcb-layout).
What it loads into context
Frontmatter
191 tokensAlways available to the agent
SKILL.md
3,451 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- Creating Dielectrics
- Creating Metals
- Multi-Layer Substrates
- Dielectrics in pcbComponent
- Frequency-Dependent Loss Models
- Common Material Parameters
- Pitfalls
- Related Skills
Files
SKILL.mdcore12,578 bytesmanifest.yamlasset483 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-ams-systems
When your agent uses it
Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempts fail. Covers Integer-N, Fractional-N, Dual Modulus architectures, loop filter design, lock time optimization, VCO phase noise configuration, and msbPllArchitectures/msbPllFoundation block assembly. Use when: PLL modeling, frequency synthesizer design, phase noise simulation, lock time analysis, charge pump design, loop filter tuning, datasheet-to-model, Mixed-Signal Blockset PLL, msbPllArchitectures.
What it loads into context
Frontmatter
187 tokensAlways available to the agent
SKILL.md
6,606 tokensWhen the skill is activated
Reference documents
21,814 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow Directives (MANDATORY)
- Prerequisites
- Entry Points
- Availability Check (MANDATORY)
- Phase 1: Extract Datasheet Parameters
- Phase 2: Select Assembly Strategy
- Phase 3: Create Custom Blocks / Customize Architecture
- Phase 4: Assemble the Model
- Quick Reference
- Happy Path Cheat Sheet (Spec → Lock Time Verified)
Files
SKILL.mdcore23,470 bytesmanifest.yamlasset647 bytesreferences/assembly-code.mddoc8,914 bytesreferences/datasheet-extraction.mddoc2,982 bytesreferences/iteration-algorithm.mddoc4,207 bytesreferences/modeling-pll-datasheet-validate.mddoc17,350 bytesreferences/pitfalls.mddoc23,590 bytesreferences/probing-simulink-models.mddoc6,420 bytesreferences/stability-analysis.mddoc6,655 bytesreferences/validate.mddoc4,048 bytesscripts/probeSlxModel.masset6,786 bytesscripts/quickProbe.masset787 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-rf
When your agent uses it
RF Toolbox and RF Blockset in MATLAB -- S-parameter I/O, network conversions (S/Z/Y/ABCD/T/H/G, mixed-mode), cascade/de-embedding, rfbudget analysis, circuit composition, matching networks, amplifier stability, mixer spurs, rational fitting, SI channels, baseband processing, Circuit Envelope simulation. Trigger: sparameters, Touchstone, .s2p, .s4p, rfplot, smithplot, rfparam, rfwrite, zparameters, yparameters, abcdparameters, s2sdd, cascadesparams, deembedsparams, rfbudget, noise figure, OIP3, IIP3, amplifier, modulator, nport, rffilter, attenuator, seriesRLC, shuntRLC, lcladder, txline, circuit, setports, clone, matchingnetwork, stabilityk, stabilitymu, powergain, gammams, gammaml, mixerIMT, OpenIF, rational, rationalfit, stepresp, txlineWRLGC, rf.Amplifier, rf.Mixer, rf.Filter, rf.Sparameter, rfsystem, RF Blockset.
What it loads into context
Frontmatter
294 tokensAlways available to the agent
SKILL.md
2,668 tokensWhen the skill is activated
Reference documents
64,730 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow Quick Reference
- Conventions
Files
SKILL.mdcore10,073 bytesSKILL.mdcore10,073 bytesSKILL.mdcore10,073 bytesSKILL.mdcore10,073 bytesSKILL.mdcore10,073 bytesmanifest.yamlasset536 bytesreference/amplifier-analysis.mddoc9,487 bytesreference/amplifier-models.mddoc2,848 bytesreference/amplifier-nonlinear-models.mddoc6,328 bytesreference/baseband-processing.mddoc18,898 bytesreference/cascade-deembed.mddoc9,183 bytesreference/circle-computations.mddoc7,467 bytesreference/circuit-composition.mddoc14,475 bytesreference/ifft-step-response.mddoc17,171 bytesreference/lumped-to-distributed.mddoc2,716 bytesreference/matching-networks.mddoc11,100 bytesreference/mixer-analysis.mddoc11,236 bytesreference/network-conversions.mddoc9,871 bytesreference/rational-fitting.mddoc20,226 bytesreference/rfbudget-analysis.mddoc8,585 bytesreference/rfbudget-elements.mddoc17,173 bytesreference/rffilter-synthesis.mddoc2,824 bytesreference/si-channel-modeling.mddoc18,220 bytesreference/sparameters-io.mddoc12,247 bytesreference/system-simulation.mddoc13,174 bytesreference/time-domain-analysis.mddoc3,067 bytesreference/transmission-lines.mddoc2,918 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-serdes-systems
When your agent uses it
Model, simulate, and optimize Serializer/Deserializer (SerDes) systems — serial and parallel links — using MATLAB SerDes Toolbox. Design NRZ and PAM-N links (PAM3 through PAM16) — explore equalization architectures (FFE, CTLE, DFE), sweep or optimize parameters with genetic algorithms, and characterize channels from loss models, S-parameter files, or crosstalk scenarios. Process captured waveforms through equalization chains, build eye diagrams, and decompose jitter. Deliver IBIS-AMI models for Tx, Rx, Redriver, or Retimer by exporting to Simulink and compiling .ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization.
What it loads into context
Frontmatter
227 tokensAlways available to the agent
SKILL.md
4,405 tokensWhen the skill is activated
Reference documents
53,516 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Classes
- Patterns
- Common Mistakes
- Conventions
Files
SKILL.mdcore16,758 bytesmanifest.yamlasset1,000 bytesreference/channel-modeling.mddoc8,037 bytesreference/common-mistakes.mddoc29,148 bytesreference/custom-datapath-blocks.mddoc13,130 bytesreference/equalization-tuning.mddoc11,701 bytesreference/optimization.mddoc9,240 bytesreference/programmatic-ami-generation.mddoc26,036 bytesreference/serdes-api-reference.mddoc29,128 bytesreference/serdes-utilities.mddoc10,611 bytesreference/simulink-serdes-simulation.mddoc19,883 bytesreference/visualization-and-metrics.mddoc20,480 bytesreference/waveform-processing.mddoc7,940 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-via
When your agent uses it
Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return vias, analyze via performance, or check signal integrity through layer transitions. Invoke BEFORE writing code — only viaSingleEnded exists (no viaDifferential), and the location format is non-obvious. SKIP: general signal integrity without vias (use matlab-analyze-em), transmission line design (use matlab-design-pcb-transmission-line), PDN analysis (use matlab-analyze-pcb-pdn), material/stackup setup only (use matlab-manage-pcb-material).
What it loads into context
Frontmatter
185 tokensAlways available to the agent
SKILL.md
6,295 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- viaSingleEnded Object
- Signal Via Configuration
- Port Definition (SignalTable)
- Ground Return Vias
- Pad and Antipad Customization
- Via Arrays
- Multi-Layer Stackup
- Analysis
- High-Speed Via Design (40+ Gbps)
- Frequency Range Guidelines for Interface Standards
- Pitfalls
- Related Skills
Files
SKILL.mdcore22,417 bytesmanifest.yamlasset467 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-optimize-pcb-design
When your agent uses it
Optimize RF PCB dimensions for bandwidth, return loss, or area via patternsearch and surrogateopt with constraints. TRIGGER: user asks to optimize an RF PCB component for performance (bandwidth, return loss, insertion loss, area) or apply constraints to a design. Invoke BEFORE writing optimization code — RF PCB Toolbox has a built-in optimize() function that differs from generic fmincon/ga approaches. SKIP: designing a component from scratch without an optimization objective (use the specific matlab-design-pcb-* skill), EM analysis without optimization (use matlab-analyze-em), material/stackup setup only (use matlab-manage-pcb-material).
What it loads into context
Frontmatter
178 tokensAlways available to the agent
SKILL.md
4,561 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Critical: Always Use optimize() First
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- Algorithm Overview
- Timing and Practical Considerations
- design() — Initial Sizing
- optimize() Syntax
- Built-in Objectives
- Example: Minimize Area with Constraints
- Example: Maximize Return Loss for Hairpin Filter
- S-Parameter Constraints
- Custom Objective Functions
- Surrogate-Based Optimization
- Solver Options
- Nested Property Optimization
- Decision: optimize() vs Manual Loop
- Optimization Workflow
- Antenna Objects with optimize()
- Fallback: Direct Solver Usage (Last Resort)
- Design Iteration Patterns
- Pitfalls
- Related Skills
Files
SKILL.mdcore17,585 bytesmanifest.yamlasset485 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-read-pcb-layout
When your agent uses it
Import Gerber, ODB++, Allegro .brd, .mcm files for PCB boards and IC packages. Inspect nets, layers, shapes, and stackups. TRIGGER: user asks to import, read, or open a PCB layout file. Gerber files use gerberRead or PCBReader; ODB++, Allegro .brd, .mcm, and native formats use pcbFileRead. Also when inspecting nets, layers, components, or stackups from an imported board. Invoke BEFORE writing import code — the query API (cadnet, cadnetList, componentList) is specialized. SKIP: EM analysis or S-parameter extraction (use matlab-analyze-em), PDN/IR-drop analysis (use matlab-analyze-pcb-pdn), building custom geometry (use matlab-assemble-pcb-layout), material/stackup definition only (use matlab-manage-pcb-material).
What it loads into context
Frontmatter
232 tokensAlways available to the agent
SKILL.md
4,932 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- gerberRead — Simple Import
- stackUp — Multi-Layer Definition
- PCBReader — Full Board Import
- Cadence Allegro .brd Import
- ODB++ Import
- Board and Package Inspection
- Using Imported Shapes in Custom Designs
- Import-to-Analysis Workflow
- Common Error Diagnostics
- Pitfalls
- Related Skills
Files
SKILL.mdcore18,398 bytesSKILL.mdcore18,398 bytesSKILL.mdcore18,398 bytesmanifest.yamlasset467 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-write-pcb-layout
When your agent uses it
Export pcbComponent designs to Gerber files with RF connectors and fab service formatting for PCB manufacturing. TRIGGER: user asks to export a PCB design to Gerber, generate manufacturing files, or write out a pcbComponent for fabrication. Invoke BEFORE writing export code — gerberWrite signature (pcbComponent, connectors, filename) is non-obvious. SKIP: importing/reading PCB files (use matlab-read-pcb-layout), building PCB geometry (use matlab-assemble-pcb-layout), EM analysis (use matlab-analyze-em), material/stackup setup (use matlab-manage-pcb-material).
What it loads into context
Frontmatter
168 tokensAlways available to the agent
SKILL.md
2,656 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Typical Workflow
- Quick Reference
- gerberWrite — Export to Manufacturing
- PCBWriter Object
- PCBConnectors — Connector Catalog
- PCBServices — Fabrication Service Writers
- RF Connectors
- Complete Design-to-Manufacturing Workflow
- Pitfalls
- Related Skills
Files
SKILL.mdcore10,105 bytesmanifest.yamlasset441 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-compute-gnss-position
When your agent uses it
Computes multi-constellation Global Positioning System (GPS) or Global Navigation Satellite System (GNSS) positions from RINEX v3 data using rinexread, gnssmeasurements, receiverposition, and gnssoptions. Filters by constellation, elevation mask, C/N0, and observation code. Reports DOP, scatter RMS, and satellite count. Use when processing GNSS data, computing positions from RINEX files, analyzing accuracy, comparing constellations, or evaluating satellite geometry. Do NOT use for carrier-phase RTK/PPP, IMU fusion, orbit propagation, NMEA streaming, or RINEX v4.
What it loads into context
Frontmatter
192 tokensAlways available to the agent
SKILL.md
5,381 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Default Observation Codes (Band 1 Preferred)
- Processing Defaults
- Key Functions
- Patterns
- Gotchas
- Sample Data
- Error Handling
- Skill Feedback
Files
SKILL.mdcore20,042 bytesmanifest.yamlasset559 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-connect-mavlink
When your agent uses it
Establish MAVLink connections between MATLAB and PX4/ArduPilot autopilots. Use when connecting to a drone, flight controller, or autopilot via MAVLink protocol over UDP. Covers dialect setup, UDP transport, timer-based heartbeat, and client discovery. Use when: "connect to PX4", "MAVLink connection", "heartbeat", "ground control station", "GCS", "connect to ArduPilot", "drone communication", "mavlinkio", "SITL".
What it loads into context
Frontmatter
156 tokensAlways available to the agent
SKILL.md
3,745 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Gotchas
- Conventions
Files
SKILL.mdcore13,861 bytesmanifest.yamlasset432 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-create-uav-scenario
When your agent uses it
Create and simulate UAV scenarios with terrain, buildings, platforms, and sensors using uavScenario. Use when building a UAV simulation, UAV simulator, or UAV scenario in MATLAB. Covers addMesh for terrain/building import, uavPlatform with updateMesh, uavSensor adaptor pattern for GPS/IMU, and the setup/advance simulation loop. Triggers on: uavScenario, UAV simulation, UAV simulator, multirotor simulation, quadrotor scenario, terrain import, building import, GPS sensor simulation.
What it loads into context
Frontmatter
160 tokensAlways available to the agent
SKILL.md
3,182 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Gotchas
- Conventions
Files
SKILL.mdcore11,387 bytesmanifest.yamlasset519 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-fuse-inertial-sensors
When your agent uses it
Analyzes sensor configurations and creates inertial fusion filters in MATLAB Navigation Toolbox. Manages filter selection (imufilter, ahrsfilter, complementaryFilter, insfilterMARG, insfilterAsync, insfilterNonholonomic, insfilterErrorState, insEKF, insCF), construction, tuning, and fusion loops. Use when fusing IMU/AHRS/INS/GPS+IMU data, estimating orientation or pose, or choosing a filter. Do NOT use for vision-only SLAM, Simulink fusion, or IMU simulation.
What it loads into context
Frontmatter
181 tokensAlways available to the agent
SKILL.md
2,896 tokensWhen the skill is activated
Reference documents
9,024 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Choose Your Filter
- Data Preparation
- Implementation
- Tuning
- Conventions
- Skill Feedback
Files
SKILL.mdcore11,592 bytesmanifest.yamlasset471 bytesreferences/attitude-filters.mddoc8,085 bytesreferences/inscf.mddoc4,571 bytesreferences/insekf.mddoc12,893 bytesreferences/navigation-filters.mddoc9,873 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-model-robot-kinematics
When your agent uses it
Use whenever a MATLAB robot model (rigidBodyTree) is needed — whether for simulation, visualization, IK, motion planning, pick-and-place, or trajectory generation. Triggers on: any mention of a manipulator by name (UR3, UR5, UR5e, UR10, UR10e, UR16e, UR20, KUKA iiwa, Fanuc, ABB, Panda, Kinova, Sawyer, Baxter), robot modeling verbs (load, create, build, import, simulate, model), tasks implying a robot model (pick, place, lift, reach, move, grasp, plan motion for, animate), kinematics keywords (IK, FK, inverse kinematics, forward kinematics, joint configuration, end-effector pose, gripper), or working with rigidBodyTree, loadrobot, importrobot, URDF, DH parameters, addVisual, addCollision.
What it loads into context
Frontmatter
248 tokensAlways available to the agent
SKILL.md
3,954 tokensWhen the skill is activated
Reference documents
5,944 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
Files
SKILL.mdcore15,403 bytesSKILL.mdcore15,403 bytesmanifest.yamlasset428 bytesreferences/ee-frame-alignment.mddoc3,691 bytesreferences/gik-constraints.mddoc3,006 bytesreferences/gripper-models.mddoc6,887 bytesreferences/import-mesh-handling.mddoc8,126 bytesreferences/parallel-robot-guidance.mddoc1,496 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-plan-robot-motion
When your agent uses it
Plan manipulator motion and generate trajectories in MATLAB. Use when the task involves moving a robot arm between configurations or poses — whether the user says "trajectory," "motion," "path," "move from A to B," or "plan." This skill applies regardless of whether the user explicitly mentions collisions or obstacles; if geometry exists in the workspace, collision safety is implicit. Triggers on: manipulatorRRT, manipulatorCHOMP, dlCHOMP, contopptraj, trapveltraj, collision-free path, motion planner, RRT, CHOMP, TOPPRA, path shortening, obstacle avoidance for manipulators, time-optimal trajectory, velocity limits, acceleration limits, occupancyMap3D, meshtsdf, collision objects as environment, trajectory between waypoints, joint interpolation, move between poses, constant velocity, trapezoidal profile, feed rate. Also triggers when a user has IK solutions or waypoints and needs to connect them — whether for time-optimal motion, constant-speed welding/cutting, or any other trajectory parameterization.
What it loads into context
Frontmatter
281 tokensAlways available to the agent
SKILL.md
4,811 tokensWhen the skill is activated
Reference documents
2,612 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Pre-conditions
- Workflow
- Key Functions
- Common Mistakes
Files
SKILL.mdcore19,573 bytesmanifest.yamlasset474 bytesreferences/planner-comparison.mddoc4,898 bytesreferences/self-collision-skip-procedure.mddoc5,385 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-spectrum
When your agent uses it
Analyze signal spectra in MATLAB using nonparametric and parametric estimators. Use when computing frequency content, PSD, power spectrum, spectral peaks, bandwidth, or streaming spectral analysis. Covers pspectrum, pwelch, periodogram, pmtm, pburg, pmusic, rootmusic, plomb, poctave, spectrumAnalyzer, dsp.SpectrumEstimator. TRIGGER: FFT, PSD, power spectrum, spectral analysis, frequency content, bandwidth measurement, spectral leakage, window selection, streaming spectrum, periodicity, resolve close frequencies, multitaper. DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features.
What it loads into context
Frontmatter
182 tokensAlways available to the agent
SKILL.md
6,009 tokensWhen the skill is activated
Reference documents
21,322 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Batch vs Streaming
- Preliminary Data Analysis
- Output Type Selection
- Estimator Selection
- Window Selection
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- Troubleshooting
- Verification
Files
SKILL.mdcore22,074 bytesmanifest.yamlasset551 bytesreferences/estimator-comparison.mddoc4,619 bytesreferences/manual-fft-psd.mddoc2,324 bytesreferences/peak-detection.mddoc6,428 bytesreferences/poctave-api.mddoc2,964 bytesreferences/power-from-spectrum.mddoc3,891 bytesreferences/preliminary-analysis.mddoc9,848 bytesreferences/pspectrum-equivalence.mddoc8,536 bytesreferences/spectral-measurements.mddoc9,377 bytesreferences/spectral-windows.mddoc6,758 bytesreferences/streaming-spectral-analysis.mddoc9,199 bytesreferences/troubleshooting.mddoc5,006 bytesreferences/units-and-db.mddoc5,074 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-analyze-time-frequency-content
When your agent uses it
Perform time-frequency analysis in MATLAB using CWT, STFT, synchrosqueezing, reassignment, wavelet coherence, cross spectrogram, EMD/VMD, multiresolution analysis, and time-frequency filtering. Triggers on: time-frequency, spectrogram, scalogram, cwt, stft, istft, fsst, wsst, wcoherence, xspectrogram, modwt, modwtmra, modwpt, emd, vmd, hht, tffilt, dgt, gabor, instantaneous frequency, synchrosqueezing, reassignment, ridge extraction, wavelet coherence, cross spectrum, mode decomposition, signal decomposition, time-frequency filtering.
What it loads into context
Frontmatter
199 tokensAlways available to the agent
SKILL.md
2,849 tokensWhen the skill is activated
Reference documents
23,126 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When To Use
- When Not To Use
- Method Selection
- Quick Decision Tree
- Critical Rules
- Signal Assessment Workflow
- Reference Guides
- Toolbox Requirements
- Documentation References
Files
SKILL.mdcore11,006 bytesmanifest.yamlasset517 bytesreferences/cross-analysis-guide.mddoc12,024 bytesreferences/cwt-guide.mddoc22,829 bytesreferences/method-selection-guide.mddoc6,395 bytesreferences/multiresolution-guide.mddoc18,286 bytesreferences/reassignment-guide.mddoc12,126 bytesreferences/stft-guide.mddoc16,821 bytesscripts/assessBoundary.masset3,126 bytesscripts/assessSignalForTF.masset4,965 bytesscripts/assessSpectralEnergy.masset3,481 bytesscripts/boundaryExDisjointSine.matasset7,750 bytesscripts/illustrateBoundary.masset902 bytesscripts/illustrateTransientLocalization.masset1,345 bytesscripts/plotAntiAnalyticScalogram.masset831 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-configure-scope-object
When your agent uses it
Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks or MATLAB objects — constrains the agent to documented APIs and directs users to the scope UI when a property is not programmatically accessible.
What it loads into context
Frontmatter
105 tokensAlways available to the agent
SKILL.md
1,748 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When To Use
- When NOT to Use
- Workflow
- Key Functions
- CRITICAL SAFETY RULES
- Error Handling Procedure
- Why These Rules Exist
Files
SKILL.mdcore7,963 bytesmanifest.yamlasset416 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-adaptive-filter
When your agent uses it
Design and implement adaptive filters using DSP System Toolbox System objects. Use when working with adaptive filtering, system identification, noise cancellation, echo cancellation, active noise control (ANC), channel equalization, inverse system identification, or adaptive prediction. Covers dsp.LMSFilter, dsp.RLSFilter, dsp.FilteredXLMSFilter, dsp.FrequencyDomainAdaptiveFilter, dsp.AffineProjectionFilter, dsp.BlockLMSFilter, dsp.AdaptiveLatticeFilter, dsp.FastTransversalFilter, maxstep(), and algorithm selection for adaptive filtering problems. Replaces deprecated adaptfilt.* objects (removed R2020a).
What it loads into context
Frontmatter
190 tokensAlways available to the agent
SKILL.md
3,060 tokensWhen the skill is activated
Reference documents
8,602 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- References
Files
SKILL.mdcore11,517 bytesSKILL.mdcore11,517 bytesmanifest.yamlasset426 bytesreferences/fdaf-filter.mddoc6,039 bytesreferences/fxlms-filter.mddoc3,990 bytesreferences/lms-filter.mddoc3,999 bytesreferences/maxstep-reference.mddoc2,943 bytesreferences/object-selection.mddoc4,009 bytesreferences/other-filters.mddoc3,900 bytesreferences/rls-filter.mddoc3,438 bytesreferences/weight-extraction.mddoc2,880 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-digital-filter
When your agent uses it
Design and validate digital filters in MATLAB. Use when cleaning up noisy signals, removing interference, filtering signals, designing FIR/IIR filters (lowpass/highpass/bandpass/bandstop/notch), or comparing filters in Filter Analyzer.
What it loads into context
Frontmatter
98 tokensAlways available to the agent
SKILL.md
1,541 tokensWhen the skill is activated
Reference documents
30,972 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Key Rules
- Workflow
- Design Intake Checklist
- Architecture Checkpoint
- Design + Verify
- Key Functions
- Conventions
Files
SKILL.mdcore6,291 bytesmanifest.yamlasset473 bytesreferences/INDEX.mddoc2,995 bytesreferences/best-practices.mddoc8,012 bytesreferences/efficient-filtering.mddoc14,752 bytesreferences/filter-analyzer.mddoc18,563 bytesreferences/multirate.mddoc13,563 bytesreferences/multistage-ifir.mddoc8,694 bytesreferences/patterns.mddoc16,540 bytesreferences/quick-ref/designfilt.mddoc6,185 bytesreferences/quick-ref/efficient-filtering.mddoc6,273 bytesreferences/quick-ref/filter-analyzer.mddoc3,024 bytesreferences/quick-ref/general-iir-fir.mddoc3,085 bytesreferences/quick-ref/multirate-offline.mddoc2,306 bytesreferences/quick-ref/multirate-streaming.mddoc3,638 bytesreferences/quick-ref/multistage-ifir.mddoc2,880 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-dsphdl-ddc
When your agent uses it
Use when designing a Digital Down Converter (DDC) using dsphdl System objects. Triggers on requests involving DDC design, frequency down-conversion for FPGA/ASIC, NCO + mixer + decimation filter chains, fractional/non-integer sample rate conversion, or HDL-optimized receiver front-end signal processing.
What it loads into context
Frontmatter
113 tokensAlways available to the agent
SKILL.md
6,066 tokensWhen the skill is activated
Reference documents
4,311 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Overview
- When to Use
- When Not To Use
- Critical Conventions
- Interactive Requirements Gathering (REQUIRED)
- Complete Workflow
- Non-Integer Decimation with Farrow Rate Converter
- Common Mistakes
Files
SKILL.mdcore22,387 bytesmanifest.yamlasset559 bytesreferences/architecture-variants.mddoc3,241 bytesreferences/component-properties.mddoc5,852 bytesreferences/numcycles.mddoc6,234 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-evaluate-acoustic-metrics
When your agent uses it
Select and use Audio Toolbox acoustic, psychoacoustic, and speech quality metrics. Use when computing loudness, sharpness, roughness, fluctuation strength, noise criteria (NC/RNC/RC), speech transmission index (STI), speech intelligibility index (SII), speech quality (ViSQOL, STOI), SPL, reverberation time (RT60), tone-to-noise ratio, or prominence ratio. Also use when asked about PESQ, POLQA, calibration factor, EBU R 128, LUFS, HVAC noise, background noise evaluation, or how to measure audio quality or noise compliance. Covers calibration, standard selection, signal alignment, and the complete function inventory including what does NOT exist.
What it loads into context
Frontmatter
208 tokensAlways available to the agent
SKILL.md
6,267 tokensWhen the skill is activated
Reference documents
24,801 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Functions That Do NOT Exist
- Key Functions
- Calibration
- Patterns
- Signal Alignment
- Common Mistakes
- Conventions
Files
SKILL.mdcore23,259 bytesSKILL.mdcore23,259 bytesmanifest.yamlasset444 bytesreferences/function-arguments.mddoc7,507 bytesreferences/noise-compliance.mddoc16,771 bytesreferences/psychoacoustic-metrics.mddoc16,342 bytesreferences/rt60-measurement.mddoc14,727 bytesreferences/sii-measurement.mddoc17,354 bytesreferences/spl-measurement.mddoc12,805 bytesreferences/sti-measurement.mddoc14,285 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-extract-signal-features
When your agent uses it
Extract features from 1D signals using signalTimeFeatureExtractor, signalFrequencyFeatureExtractor, and signalTimeFrequencyFeatureExtractor. Use when computing time-domain features (amplitude, energy, shape factors), frequency-domain features (spectral location, power, bandwidth, PSD), or time-frequency features (spectral shape, instantaneous, ridges, wavelet, EMD-derived) on a per-frame basis. Use when the user asks to "extract features", "compute spectral features", "build a feature table for a classifier", "get per-frame statistics", "run feature extraction on this signal", or describes a vibration / biosignal / radar / sensor signal needing features for downstream ML or analysis. Includes optional GPU acceleration via canUseGPU and gpuArray. Does not cover filter design, audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features.
What it loads into context
Frontmatter
253 tokensAlways available to the agent
SKILL.md
4,158 tokensWhen the skill is activated
Reference documents
15,705 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Choosing the right extractor
- Key Functions
- Patterns
- Conventions (apply to all three extractors)
- Common cross-cutting pitfalls
- References
Files
SKILL.mdcore18,450 bytesSKILL.mdcore18,450 bytesmanifest.yamlasset482 bytesreferences/extract-function.mddoc7,085 bytesreferences/feature-ranking.mddoc5,860 bytesreferences/gpu-patterns.mddoc6,623 bytesreferences/post-extraction-patterns.mddoc4,435 bytesreferences/preliminary-analysis.mddoc7,267 bytesreferences/scalarization-options.mddoc5,982 bytesreferences/signal-frequency-feature-extractor.mddoc6,877 bytesreferences/signal-time-feature-extractor.mddoc5,099 bytesreferences/signal-time-frequency-feature-extractor.mddoc14,420 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-play-record-audio
When your agent uses it
Reference for MATLAB audiostreamer (Audio Toolbox R2025a+). Without this skill, agents consistently default to legacy audioDeviceWriter/audioDeviceReader or base MATLAB sound(), producing less capable code. Use when writing code for audio playback, recording, full-duplex device I/O, real-time audio measurements, or audio I/O processing with callbacks. Also use when debugging audiostreamer errors, dropouts, or latency issues, or migrating from audioDeviceReader, audioDeviceWriter, audioPlayerRecorder, or audioplayer/audiorecorder.
What it loads into context
Frontmatter
155 tokensAlways available to the agent
SKILL.md
5,457 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Construction
- Properties
- Methods
- CRITICAL: There is NO `setup()` Method
- Common Patterns
- Teardown Best Practice
- ConstantLatency Modes (Full-Duplex)
- Error Conditions
- audiostreamer vs. Legacy Audio APIs
- Diagnostics
Files
SKILL.mdcore21,327 bytesmanifest.yamlasset446 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-prepare-signal-data
When your agent uses it
Use this skill when conditioning, loading, preparing, or labeling signal data for analysis or ML training. Covers: cleaning a single signal (fill gaps, remove drift, deoutlier, denoise, resample/align a time base) BEFORE analysis; building a `signalDatastore` pipeline; creating a `labeledSignalSet` for Signal Labeler; deriving labels (filename, folder, in-file, ROI, time-frequency ROI); stratified train/val/test splits; framing long signals; parallel processing; and shaping datastore output for `trainnet`. Triggers include "clean up this signal", "remove drift / detrend", "fill gaps", "remove spikes / outliers", "denoise", "resample to a uniform rate", "align channels", "labels from filenames", "stratified split", "prepare for Signal Labeler", and function names like `fillgaps`, `fillmissing`, `detrend`, `filloutliers`, `smoothdata`, `resample`, `synchronize`, `signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`.
What it loads into context
Frontmatter
317 tokensAlways available to the agent
SKILL.md
2,481 tokensWhen the skill is activated
Reference documents
53,306 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Best practices
- 0. Common reflexes
- 1. Workflows
- 2. Ordering when a signal needs several conditioning steps
Files
SKILL.mdcore9,681 bytesmanifest.yamlasset650 bytesreferences/fn-countlabels.mddoc2,181 bytesreferences/fn-detrend.mddoc4,682 bytesreferences/fn-filenames2labels.mddoc4,930 bytesreferences/fn-fillgaps.mddoc3,417 bytesreferences/fn-fillmissing.mddoc4,294 bytesreferences/fn-filloutliers.mddoc5,154 bytesreferences/fn-folders2labels.mddoc3,514 bytesreferences/fn-framelbl.mddoc7,293 bytesreferences/fn-framesig.mddoc4,196 bytesreferences/fn-hampel.mddoc3,340 bytesreferences/fn-labeledsignalset.mddoc9,274 bytesreferences/fn-labelspectrogramoptions.mddoc4,697 bytesreferences/fn-medfilt1.mddoc3,337 bytesreferences/fn-partition.mddoc4,678 bytesreferences/fn-resample.mddoc4,730 bytesreferences/fn-retime.mddoc4,827 bytesreferences/fn-sgolayfilt.mddoc3,552 bytesreferences/fn-signaldatastore.mddoc12,205 bytesreferences/fn-signallabeldefinition.mddoc6,000 bytesreferences/fn-signalmask-getmask.mddoc8,798 bytesreferences/fn-smoothdata.mddoc4,944 bytesreferences/fn-splitlabels.mddoc5,386 bytesreferences/fn-subset.mddoc4,006 bytesreferences/fn-synchronize.mddoc4,776 bytesreferences/fn-wdenoise.mddoc5,319 bytesreferences/wf-align-channels.mddoc6,745 bytesreferences/wf-custom-readfcn.mddoc5,071 bytesreferences/wf-denoise.mddoc2,631 bytesreferences/wf-detrend-smooth-deoutlier.mddoc6,750 bytesreferences/wf-envelope.mddoc5,464 bytesreferences/wf-frame-and-label.mddoc4,842 bytesreferences/wf-handoff-to-dl.mddoc9,351 bytesreferences/wf-label-and-export.mddoc8,863 bytesreferences/wf-load-and-split.mddoc4,688 bytesreferences/wf-parallel-process.mddoc4,873 bytesreferences/wf-repair-missing.mddoc6,877 bytesreferences/wf-uniform-rate.mddoc4,346 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-process-streaming-audio
When your agent uses it
Design and implement real-time audio processing chains using Audio Toolbox streaming objects. Use when building frame-based audio processing loops, multiband filters, dynamic range control, parametric EQ, level metering, loudness metering, SPL metering, octave-band analysis, sample rate conversion, frequency-domain filtering (long impulse responses, custom filter banks), or audio chains in Simulink. Covers visualization (visualize method), interactive tuning (parameterTuner), MIDI control, and Audio Toolbox Simulink blocks. Use when the user says "real-time audio", "streaming audio", "audio filter", "compressor", "equalizer", "level meter", "loudness meter", "SPL meter", "octave bands", "crossover filter", "audio chain", "MIDI control", "convolution reverb", "impulse response streaming", "frequency-domain filter", or asks to process audio frame-by-frame.
What it loads into context
Frontmatter
251 tokensAlways available to the agent
SKILL.md
5,718 tokensWhen the skill is activated
Reference documents
1,054 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Common Mistakes
- Conventions
Files
SKILL.mdcore22,726 bytesSKILL.mdcore22,726 bytesmanifest.yamlasset437 bytesreferences/simulink-audio-blocks.mddoc4,855 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-write-audio-plugin
When your agent uses it
Guide authoring of Audio Toolbox plugins (audioPlugin, audioPluginSource) that pass validateAudioPlugin and generate deployable VST/AU code. Use when creating audio effect or generator plugins, writing classdef files inheriting from audioPlugin, or troubleshooting validateAudioPlugin failures.
What it loads into context
Frontmatter
110 tokensAlways available to the agent
SKILL.md
2,521 tokensWhen the skill is activated
Reference documents
7,828 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When To Use
- When NOT To Use
- Structure
- Plugin Lifecycle
- Codegen Requirements
- Validation
- Generation
- References
Files
SKILL.mdcore10,380 bytesSKILL.mdcore10,380 bytesmanifest.yamlasset524 bytesreferences/advanced-patterns.mddoc6,970 bytesreferences/available-functions.mddoc9,236 bytesreferences/deep-learning.mddoc8,163 bytesreferences/grid-layout.mddoc3,995 bytesreferences/parameters.mddoc1,435 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-build-industrial-hmi
When your agent uses it
Build industrial-grade SCADA/HMI dashboards in MATLAB following industrial-HMI conventions (ISA-101-aligned): gray-field philosophy, alarms at source, write safeguards, fixed-range trends, drill-down layout. Produces a real App Designer app (.mlapp, or plain-text .m+.xml on R2026b+) by handing serialization to the matlab-build-app skill when available, and falls back to a programmatic .m app otherwise. Use when wrapping OPC UA / Modbus / MQTT / OSI PI / PI AF monitoring scripts into a live operator app, building plant overviews, designing operator dashboards, or any time a user asks for a "SCADA dashboard", "HMI", "plant dashboard", "operator screen", or "industrial monitoring app" in MATLAB. Trigger on: SCADA, HMI, industrial dashboard, plant overview, operator screen, uigauge, uilamp, alarm banner, gray-field, ISA-101, OPC UA dashboard, setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient.
What it loads into context
Frontmatter
306 tokensAlways available to the agent
SKILL.md
5,565 tokensWhen the skill is activated
Reference documents
38,541 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Workflow
- Key Functions
- Patterns
- Common Mistakes
- References
- Toolbox Dependencies
Files
SKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesSKILL.mdcore22,507 bytesmanifest.yamlasset901 bytesreferences/alarm-patterns.mddoc10,219 bytesreferences/app-designer-gotchas.mddoc8,821 bytesreferences/app-designer-handoff.mddoc13,607 bytesreferences/color-and-layout-rules.mddoc13,510 bytesreferences/common-mistakes.mddoc33,604 bytesreferences/known-schema-patterns.mddoc4,188 bytesreferences/pi-af-cheatsheet.mddoc16,433 bytesreferences/protocol-cheatsheet.mddoc17,878 bytesreferences/server-agnostic-discovery.mddoc8,600 bytesreferences/trend-config-reference.mddoc7,065 bytesreferences/widget-selection-flowchart.mddoc6,303 bytesreferences/write-safeguards-reference.mddoc8,610 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-call-nidaqmx
When your agent uses it
Translate NI-DAQmx C function signatures into correct calldaqlib MATLAB calls. Use when the user mentions calldaqlib, any DAQmx* C function name (DAQmxCfgSampClkTiming, DAQmxExportSignal, DAQmxSetStartTrigRetriggerable, DAQmxGetSampClkRate, etc.), or needs NI-DAQmx functionality not exposed by the daq object. Covers: projection rules (taskHandle implicit, output pointers become return values, buffer-size args, enum-as-string), multi-task semantics, start() clobber, device-level empty-daq workaround, dictionary returns, string getter placeholder, array getter placeholder. Trigger contexts: low-level DAQ, escape hatch, retriggerable acquisition, shared timebase, export signal, connect terminals, external sample clock, trigger configuration, NI driver, C function translation.
What it loads into context
Frontmatter
250 tokensAlways available to the agent
SKILL.md
2,966 tokensWhen the skill is activated
Reference documents
2,591 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Decision Tree
- Call Forms
- C-to-calldaqlib Translation
- Hard Rules
- Conventions
- References
Files
SKILL.mdcore10,791 bytesSKILL.mdcore10,791 bytesmanifest.yamlasset428 bytesreferences/common-mistakes.mddoc3,230 bytesreferences/enum-constants.mddoc2,104 bytesreferences/hot-signatures.mddoc3,300 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-connect-arduino
When your agent uses it
Discover, configure, and connect to Arduino boards from MATLAB using the Arduino Support Package. Use this skill when the user wants to set up an Arduino board, connect to Arduino hardware, find connected boards, scan serial ports, configure Arduino libraries, or any task that requires an Arduino connection as a prerequisite (e.g., blink LED, read sensor, read digital pin, read analog pin, write pin, plot sensor data, scan I2C, use ultrasonic sensor, control servo, read temperature, read voltage, data logging from hardware). Triggers on: arduino, board setup, COM port, serial port, hardware connection, Arduino Nano, Arduino Uno, Arduino Mega, Arduino Micro, Grove, sensor setup, I2C scan, ultrasonic, servo, readDigitalPin, writeDigitalPin, readVoltage, writePWMVoltage, temperature sensor, air pressure, pin read, pin write, analog input.
What it loads into context
Frontmatter
248 tokensAlways available to the agent
SKILL.md
2,806 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Common Mistakes
- Conventions
Files
SKILL.mdcore11,451 bytesmanifest.yamlasset450 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-connect-bluetooth-low-energy-device
When your agent uses it
Discover and connect to Bluetooth Low Energy (BLE) peripheral devices from MATLAB. Use this skill when the user wants to scan for BLE devices, connect to a BLE peripheral, read or write BLE characteristics, subscribe to notifications, or any task that requires a BLE connection as a prerequisite (e.g., read sensor data over BLE, monitor heart rate, log accelerometer, stream data from wearable, IoT device communication). Triggers on: BLE, Bluetooth Low Energy, blelist, ble device, BLE characteristic, GATT, service UUID, scan for devices, BLE sensor, subscribe notify, BLE read, BLE write, peripheral device, BLE connect, wireless sensor.
What it loads into context
Frontmatter
196 tokensAlways available to the agent
SKILL.md
3,110 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Common Mistakes
- Conventions
Files
SKILL.mdcore13,218 bytesmanifest.yamlasset410 bytesscripts/bleDataCollector.masset1,857 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-create-custom-arduino-library
When your agent uses it
Use when the user wants to use Arduino sensors or peripherals from MATLAB that are not directly supported by the MATLAB Support Package for Arduino Hardware. Triggers on requests to create, wrap, or expose a custom Arduino library to MATLAB. Also triggers on indirect questions like "How do I read humidity in MATLAB?" or "How do I display text on an LCD from MATLAB?" where the answer requires a custom Arduino add-on library. Covers: custom addon creation, third-party Arduino library integration, LibraryBase class, C++ header files, DependentLibraries, arduinoioaddons namespace, I2C/SPI/GPIO peripheral wrappers.
What it loads into context
Frontmatter
188 tokensAlways available to the agent
SKILL.md
3,477 tokensWhen the skill is activated
Reference documents
2,853 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- MATLAB Class Property Rules
- C++ Header Rules
- Common Mistakes
- Conventions
- Fallback: When Automated Steps Fail or Take Too Long
- Troubleshooting
Files
SKILL.mdcore13,610 bytesSKILL.mdcore13,610 bytesmanifest.yamlasset476 bytesreferences/bus-conflicts.mddoc3,031 bytesreferences/common-errors.mddoc3,389 bytesreferences/cpp-patterns.mddoc5,055 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-discover-hardware
When your agent uses it
Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device that supports a capability (e.g., CAN, analog input), or checks if required support packages or add-ons are installed. Does NOT connect to, configure, or acquire data from devices — defers to device-specific skills for usage workflows.
What it loads into context
Frontmatter
129 tokensAlways available to the agent
SKILL.md
4,324 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- 1. What this skill is for
- When To Use
- When Not To Use
- 2. Device-specific skill routing
- 3. One-time bootstrap (path setup)
- 4. Public helper surface
- 5. Task routing
- 6. Workflow patterns and batching
- 7. Communication rules
- 8. Hard guardrails
- 9. Interpreting CustomData
- 10. Output-handling guidance
Files
SKILL.mdcore19,553 bytesSKILL.mdcore19,553 bytesSKILL.mdcore19,553 bytesmanifest.yamlasset419 bytesscripts/getAddOnDetails.masset1,494 bytesscripts/getAddOnDetails.passet783 bytesscripts/getDeviceAddOns.masset386 bytesscripts/getDeviceAddOns.passet412 bytesscripts/getDeviceDetails.masset1,621 bytesscripts/getDeviceDetails.passet2,225 bytesscripts/getDeviceSetupInfo.masset1,140 bytesscripts/getDeviceSetupInfo.passet1,321 bytesscripts/hardwareDeviceCache.masset1,546 bytesscripts/hardwareDeviceCache.passet1,764 bytesscripts/isRequiredAddOnsInstalled.masset1,259 bytesscripts/isRequiredAddOnsInstalled.passet804 bytesscripts/listHardwareDevices.masset1,857 bytesscripts/listHardwareDevices.passet2,226 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-enhance-camera-image
When your agent uses it
Read BEFORE troubleshooting or enhancing camera image quality. Diagnoses and enhances image quality from cameras connected via Image Acquisition Toolbox or USB Webcams support package. Discovers camera capabilities at runtime, analyzes captured images for quality issues (brightness, contrast, sharpness, noise, color balance, backlighting), suggests hardware setting adjustments tailored to the specific camera, and applies Image Processing Toolbox enhancement functions. Use when a user wants to improve camera image quality, troubleshoot dark/blurry/noisy/grainy/ overexposed/washed out/color cast images, or optimize camera settings.
What it loads into context
Frontmatter
170 tokensAlways available to the agent
SKILL.md
3,518 tokensWhen the skill is activated
Reference documents
6,911 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Purpose
- When to Use
- When NOT to Use
- Reference Documents (load when needed)
- Script Entrypoints
- Hard Requirements
- Protocol
- Decision Table
- Generated Pipeline Templates
- Gotchas
Files
SKILL.mdcore15,161 bytesSKILL.mdcore15,161 bytesSKILL.mdcore15,161 bytesmanifest.yamlasset548 bytesreferences/diagnosis-guidance.mddoc8,576 bytesreferences/enhancement-guidance.mddoc9,053 bytesreferences/hardware-tuning-guidance.mddoc9,451 bytesscripts/diagnoseImageQuality.masset4,626 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-find-pi-assets
When your agent uses it
Find and query PI assets using MATLAB's Industrial Communication Toolbox. Two paths: (1) direct PI tag lookup via piclient + tags when user provides a tag name or description (R2022a+), (2) Asset Framework navigation via afclient when user needs element/attribute hierarchy (R2026a+). Use when working with PI AF servers, PI Data Archive tags, asset hierarchies, element templates, attribute lookup, or historical data from OSIsoft PI systems.
What it loads into context
Frontmatter
157 tokensAlways available to the agent
SKILL.md
6,136 tokensWhen the skill is activated
Reference documents
788 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Release Requirements
- When to Use
- When NOT to Use
- Decision Logic
- Workflow A: Direct Tag Lookup (R2022a+)
- Workflow B: Asset Framework Navigation (R2026a+)
- Key Functions
- Patterns
- Conventions
- Common Mistakes
Files
SKILL.mdcore24,731 bytesmanifest.yamlasset504 bytesreferences/key-functions.mddoc3,381 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-import-export-vehicle-data
When your agent uses it
Use when importing or exporting vehicle data from/to log files (MDF/MF4/DAT, BLF, ASC/TXT), decoding CAN/CAN FD/LIN messages to signals via DBC, ARXML, or LDF databases, writing timetable data to MDF or BLF files, or calling blfread, blfinfo, blfwrite, mdfRead, mdfWrite, mdfCreate, mdfInfo, canSignalImport, canMessageImport, canMessageTimetable, canFDMessageTimetable, canSignalTimetable, or linMessageTimetable.
What it loads into context
Frontmatter
166 tokensAlways available to the agent
SKILL.md
3,043 tokensWhen the skill is activated
Reference documents
12,480 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not To Use
- Prerequisites
- Decode Pipeline
- Database Loading
- Database inspection for DBC files and classification of the multiplexing scheme
- Key Constraints
- File-Specific References
- Protocol References
- Demultiplexing References
- Export Workflows
- Export References
Files
SKILL.mdcore11,645 bytesmanifest.yamlasset661 bytesreferences/asc-import.mddoc3,487 bytesreferences/blf-import.mddoc3,680 bytesreferences/blf-writing.mddoc7,632 bytesreferences/can-decode.mddoc2,054 bytesreferences/canfd-decode.mddoc1,979 bytesreferences/database-objects.mddoc2,434 bytesreferences/dbc-multiplexing-syntax.mddoc5,060 bytesreferences/lin-decode.mddoc2,095 bytesreferences/mdf-import.mddoc4,494 bytesreferences/mdf-writing.mddoc7,514 bytesreferences/simple-demultiplexing.mddoc4,898 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-modernize-daq
When your agent uses it
Port MATLAB Data Acquisition Toolbox code from the discouraged (legacy) session-based interface (daq.createSession, addAnalogInputChannel, startBackground, DataAvailable listeners, queueOutputData, wait) to the recommended DataAcquisition interface (daq("ni"), addinput, start, ScansAvailableFcn, write, preload). Use when migrating legacy DAQ scripts, converting session-API calls, working with DataAcquisition objects, writing multi-feature DAQ scripts that combine triggers, callbacks, continuous acquisition, or analog output. Also use when a user says their DAQ script "used to work" or "errors on R20XX", since modernizing legacy session-API code is a frequent fix for those failures. Trigger keywords: daq, DAQ, NI, session interface, addtrigger, addclock, ScansAvailableFcn, ScansRequiredFcn, daq.createSession, addAnalogInputChannel, startBackground, queueOutputData, DataAvailable, evt.Data, evt.TimeStamps, wait(d), preload, discouraged, legacy, modernize, R2020a.
What it loads into context
Frontmatter
279 tokensAlways available to the agent
SKILL.md
4,306 tokensWhen the skill is activated
Reference documents
5,507 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Key Functions
- Patterns
- Conventions
- Common Mistakes
- References
Files
SKILL.mdcore18,235 bytesSKILL.mdcore18,235 bytesSKILL.mdcore18,235 bytesSKILL.mdcore18,235 bytesmanifest.yamlasset477 bytesreferences/callback-state-patterns.mddoc7,727 bytesreferences/canonical-snippets.mddoc5,812 bytesreferences/session-to-modern-mapping.mddoc13,712 bytesscripts/verifyDataAcquisition.masset7,593 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-cameras
When your agent uses it
Connect to and acquire images from cameras in MATLAB using Image Acquisition Toolbox. Use this skill when the user wants to: use a webcam, acquire images, capture video, stream from a camera, connect to a GigE Vision camera, preview live video, list available cameras, configure camera properties, use a CoaXPress frame grabber, or use a Camera Link frame grabber. Covers USB webcams, GigE Vision, USB3 Vision, CoaXPress, Camera Link, and GenICam-compliant cameras. Always prefer videoinput from Image Acquisition Toolbox over webcam support package or gigecam.
What it loads into context
Frontmatter
182 tokensAlways available to the agent
SKILL.md
2,865 tokensWhen the skill is activated
Reference documents
344 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Conventions
- Workflow
- Key Functions
- Patterns
- Common Mistakes
Files
SKILL.mdcore11,252 bytesSKILL.mdcore11,252 bytesSKILL.mdcore11,252 bytesmanifest.yamlasset472 bytesreferences/gentl-setup.mddoc1,466 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-opcua-client
When your agent uses it
Discover OPC UA servers, connect MATLAB clients, and browse/navigate server nodes using opcuaserverinfo, the Local Discovery Service (LDS), opcua, connect, setSecurityModel, certificate-trust functions, findNodeById, opcuanode, and Namespace/Children traversal. Use when finding OPC UA servers on the network, querying endpoints and security policies, connecting to a server, authenticating with username/password or certificates, configuring security modes, handling certificate-trust or hostname-mismatch errors, troubleshooting failed connections or empty discovery, inspecting an OPC UA certificate (.der/.pem), browsing an address space, finding nodes by name or NodeId, navigating node hierarchies, invoking method nodes, or batch-processing large namespaces. Trigger on: opcuaserverinfo, LDS, opcua, opc.ua.Client, setSecurityModel, opc.ua.trustServerCertificate, OPC UA certificate, findNodeById, opcuanode, browse OPC UA, find node, OPC UA namespace, OPC UA method node, Industrial Communication Toolbox.
What it loads into context
Frontmatter
284 tokensAlways available to the agent
SKILL.md
4,262 tokensWhen the skill is activated
Reference documents
9,027 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Internal Constraints
- When to Use
- When NOT to Use
- References
- Workflow
- Key Functions
- Properties Quick Reference
- Patterns
- Troubleshooting Quick Reference
Files
SKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesSKILL.mdcore17,496 bytesmanifest.yamlasset493 bytesreferences/certificate-trust-workflows.mddoc5,788 bytesreferences/common-mistakes.mddoc4,422 bytesreferences/lds-setup-and-troubleshooting.mddoc4,877 bytesreferences/node-functions-reference.mddoc7,334 bytesreferences/node-navigation.mddoc7,905 bytesreferences/troubleshooting-connection-errors.mddoc5,743 bytesscripts/inspectOpcUaCertificate.masset7,209 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-use-vehicle-network
When your agent uses it
Use when setting up vehicle network communication in MATLAB using Vehicle Network Toolbox. Covers CAN/CAN FD (fully implemented), with architecture for J1939, XCP, and future protocols. Handles hardware discovery, channel creation, bus configuration, message exchange, signal encoding/decoding, and analysis across all supported vendors. (Vector, Kvaser, PEAK-System, NI, SocketCAN, MathWorks Virtual).
What it loads into context
Frontmatter
129 tokensAlways available to the agent
SKILL.md
3,230 tokensWhen the skill is activated
Reference documents
21,240 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Prerequisites
- Overview
- When to Use
- When NOT to Use
- Protocol Router
- Shared Concepts (All Protocols)
- CAN / CAN FD
- Shared References
Files
SKILL.mdcore13,412 bytesSKILL.mdcore13,412 bytesmanifest.yamlasset537 bytesreferences/can/bus-speed-config.mddoc2,271 bytesreferences/can/channel-creation.mddoc1,489 bytesreferences/can/database.mddoc3,107 bytesreferences/can/filters.mddoc2,887 bytesreferences/can/message-creation.mddoc1,318 bytesreferences/can/message-extraction.mddoc3,882 bytesreferences/can/pack-unpack.mddoc2,700 bytesreferences/can/receive.mddoc1,953 bytesreferences/can/transmit.mddoc2,393 bytesreferences/can/troubleshooting/bus-length-guidelines.mddoc3,606 bytesreferences/can/troubleshooting/diagnostic-workflow.mddoc21,948 bytesreferences/can/troubleshooting/l1-branches.mddoc11,373 bytesreferences/can/troubleshooting/l1-domain-knowledge.mddoc6,956 bytesreferences/can/troubleshooting/l1-failure-scenarios.mddoc3,653 bytesreferences/can/troubleshooting/l2-analysis-pipeline.mddoc4,632 bytesreferences/can/troubleshooting/l2-interpretation-tables.mddoc1,881 bytesreferences/can/troubleshooting/script-interfaces.mddoc2,638 bytesreferences/shared/channel-lifecycle.mddoc1,125 bytesreferences/shared/hardware-discovery.mddoc1,093 bytesreferences/shared/limitations.mddoc1,740 bytesscripts/can/troubleshooting/canBaudRateScanActive.passet1,054 bytesscripts/can/troubleshooting/canBaudRateScanPassive.passet1,035 bytesscripts/can/troubleshooting/canBurstDetection.passet488 bytesscripts/can/troubleshooting/canBusLoadCalc.passet787 bytesscripts/can/troubleshooting/canChannelHealthCheck.passet902 bytesscripts/can/troubleshooting/canCycleTimeAnalysis.passet558 bytesscripts/can/troubleshooting/canDiagnosticProbe.passet335 bytesscripts/can/troubleshooting/canHardwareDiscovery.passet290 bytesscripts/can/troubleshooting/canLoopbackSelfTest.passet628 bytesscripts/can/troubleshooting/canSupportSummary.passet1,388 bytesscripts/can/troubleshooting/canTrafficOverview.passet900 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-add-awgn
When your agent uses it
Read BEFORE writing any code that adds Additive White Gaussian Noise (AWGN) to signals and converts between SNR, Eb/No, Es/No, and per-subcarrier SNR for communications simulations, using awgn(), convertSNR(), berawgn(). The default MATLAB patterns for AWGN (e.g., 'measured' option, manual SNR formulas) produce subtly incorrect results. This skill specifies the correct calling conventions, required function usage, and critical anti-patterns that must be avoided.
What it loads into context
Frontmatter
149 tokensAlways available to the agent
SKILL.md
4,313 tokensWhen the skill is activated
Reference documents
3,707 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Must-Follow Rules
- Critical Anti-Patterns — NEVER Do These
- Key Functions
- Gotchas
- Patterns
- After Adding Noise
- References
Files
SKILL.mdcore14,969 bytesmanifest.yamlasset501 bytesreferences/5g-link-noise.mddoc2,304 bytesreferences/snr-conversion-guide.mddoc8,643 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-design-ofdm-system
When your agent uses it
Read BEFORE writing any code that builds or simulates OFDM systems. The default MATLAB patterns for OFDM (e.g., direct ifft/fft, awgn with 0 dBW power, missing symOffset) produce subtly incorrect results — always use ofdmmod/ofdmdemod instead of direct IFFT/FFT. This skill specifies the correct calling conventions for ofdmmod, ofdmdemod, ofdmChannelResponse, ofdmEqualize, and critical anti-patterns that must be avoided. Use when building OFDM transmitters or receivers, allocating subcarriers and guard bands, inserting pilots, computing SNR for OFDM, configuring fading channels (Rayleigh/Rician), estimating and equalizing channels, implementing timing and frequency synchronization, adding LDPC coding, designing resource grids, or setting up OFDM link simulations.
What it loads into context
Frontmatter
220 tokensAlways available to the agent
SKILL.md
4,440 tokensWhen the skill is activated
Reference documents
13,560 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When To Use
- When Not To Use
- GATE — Ask Before Coding
- Must-Follow Rules
- Key Functions
- Subcarrier Allocation
- Basic OFDM Tx/Rx (AWGN)
- SNR Handling for OFDM
- Critical Gotchas
- OFDM with Pilots
- Pilot-Based Channel Estimation (R2026a)
- OFDM over Fading Channels
- Fading Channel Setup
- Synchronization
- LDPC Coding
- Advanced Features
- Cross-References
- Reference Loading
Files
SKILL.mdcore15,969 bytesmanifest.yamlasset606 bytesreferences/ofdm-fading-channel.mddoc8,609 bytesreferences/ofdm-ldpc-coding.mddoc8,066 bytesreferences/ofdm-pilots-and-estimation.mddoc8,232 bytesreferences/ofdm-synchronization.mddoc12,062 bytesreferences/ofdm-system-guide.mddoc5,579 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-detect-capture-usrp
When your agent uses it
Smart triggered RF capture on NI USRP radios with Wireless Testbench — record only when a signal of interest appears, not continuously (triggered spectrum sensing). Use energy detection to capture when signal power rises above the noise floor, or preamble detection to cross-correlate against a known sequence (WLAN L-LTF, 5G NR PSS/SSS, LTE PSS, Zadoff-Chu, custom protocols) and capture only when that protocol's preamble is detected. Use when implementing triggered (wake-on-signal) capture or spectrum sensing, capturing protocol-based signals via cross-correlation, calibrating detection thresholds (plotDetectionSignals / plotThreshold), scanning frequency bands for activity, or building transmit-then-detect workflows.
What it loads into context
Frontmatter
200 tokensAlways available to the agent
SKILL.md
3,774 tokensWhen the skill is activated
Reference documents
11,478 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Reference Loading
- Sub-Workflows
- Prerequisites
- When to Use
- When NOT to Use
- Decision Tree
- Code Generation Steps
- Guardrails
Files
SKILL.mdcore16,202 bytesmanifest.yamlasset699 bytesreferences/api.mddoc6,461 bytesreferences/overview.mddoc4,237 bytesreferences/patterns.mddoc19,132 bytesreferences/threshold-calibration.mddoc14,149 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-5g-waveform
When your agent uses it
Generate 3GPP-compliant 5G NR downlink and uplink baseband waveforms. Use to create NR signals, test model (TM) waveforms, fixed reference channels (FRC), test and measurement (T&M) signals, or test vectors for conformance testing. Covers configuring data, control, and broadcast channels and signals: PDSCH, PUSCH, PDCCH, PUCCH, SRS, SSBurst, CSI-RS, DM-RS, PT-RS, CORESET, and BWP parameters including bandwidth, subcarrier spacing (SCS), modulation (QPSK, QAM), numerology, FR1, FR2, TDD, FDD, and multi-bandwidth-part setups. Use for signal generation, RF instrument playback, or IQ baseband synthesis. Requires 5G Toolbox.
What it loads into context
Frontmatter
238 tokensAlways available to the agent
SKILL.md
2,251 tokensWhen the skill is activated
Reference documents
13,494 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- API Choice
- Core Workflow (custom DL/UL)
- Set Only What the Task Requires
- Recipes and References
- Conventions
Files
SKILL.mdcore8,057 bytesmanifest.yamlasset440 bytesreferences/api-reference.mddoc3,436 bytesreferences/critical-rules.mddoc8,154 bytesreferences/documentation-links.mddoc2,407 bytesreferences/multi-bwp-guidance.mddoc18,092 bytesreferences/narrow-band-manual-config.mddoc4,567 bytesreferences/patterns.mddoc1,797 bytesreferences/test-models-and-frc.mddoc5,132 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-ble-waveform
When your agent uses it
Generate Bluetooth Low Energy (BLE) PHY waveforms. Read BEFORE writing any BLE waveform code to avoid hallucinating API patterns. Covers bleWaveformGenerator, bleIdealReceiver, bleCTEIQSample, bleAngleEstimate, bluetoothTestWaveform for LE1M/LE2M/LE500K/LE125K. Bluetooth Toolbox R2022a+.
What it loads into context
Frontmatter
139 tokensAlways available to the agent
SKILL.md
5,772 tokensWhen the skill is activated
Reference documents
13,844 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Routing
- When To Use
- When Not To Use
- PHY Modes
- References
- Parameters (bleWaveformGenerator)
- Core Recipe
- Patterns
- CTE Compatibility
- Spec Constraints
- Conventions
- Code Style
- Gotchas
Files
SKILL.mdcore18,340 bytesmanifest.yamlasset432 bytesreferences/cte-direction-finding.mddoc1,642 bytesreferences/data-whitening.mddoc1,248 bytesreferences/direction-finding.mddoc3,367 bytesreferences/functionalAPI.mddoc17,993 bytesreferences/phy-modes-and-timing.mddoc2,997 bytesreferences/practical-receiver-simulation.mddoc13,771 bytesreferences/rfphy-compliance-testing.mddoc1,699 bytesreferences/rssi-localization.mddoc1,488 bytesreferences/transmitter-measurements.mddoc1,260 bytesreferences/wlan-coexistence.mddoc1,353 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-gnss-waveform
When your agent uses it
Generate GNSS baseband waveforms (GPS, Galileo, NavIC) with physically realistic or user-specified channel impairments using the Satellite Communications Toolbox. Use when generating GPS L1 C/A, L1C, L2C, L5, Galileo E1, E1C, E5a, E5b, E5, or NavIC L5, S, L1 signals. Covers gpsWaveformGenerator, galileoWaveformGenerator, satelliteScenario, Doppler/delay from orbital dynamics or custom values, navigation data encoding with ephemeris, and RINEX integration. Triggers on: GPS waveform, Galileo waveform, NavIC waveform, GNSS signal, satellite scenario, GNSS simulation, receiver test signal, baseband GNSS, L-band satellite signal, navigation signal generation.
What it loads into context
Frontmatter
239 tokensAlways available to the agent
SKILL.md
5,554 tokensWhen the skill is activated
Reference documents
12,610 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Prerequisites: Helper Files
- Workflow
- Signal Type Quick Reference
- Verification (Scenario Mode Only)
- Key Functions
- Gotchas
- Conventions
Files
SKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesSKILL.mdcore20,442 bytesmanifest.yamlasset573 bytesreferences/galileo-pipeline.mddoc10,640 bytesreferences/gps-pipeline.mddoc5,320 bytesreferences/helper-files.mddoc2,957 bytesreferences/navic-pipeline.mddoc11,026 bytesreferences/physical-constraints.mddoc4,482 bytesreferences/rinex-integration.mddoc5,350 bytesreferences/signal-type-mapping.mddoc2,459 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-generate-wlan-waveform
When your agent uses it
Generate standard-compliant IEEE 802.11 waveforms using MATLAB WLAN Toolbox. Use when creating WLAN waveforms, PPDU packets, or the transmit side of a link-level simulation. Covers all formats: Non-HT (802.11a/g), HT (802.11n), VHT (802.11ac), HE-SU/HE-MU/HE-TB (802.11ax), EHT-MU/EHT-TB (802.11be), UHR-MU/UHR-TB/UHR-ELR (802.11bn). Handles single-user, MU-MIMO, OFDMA, trigger-based uplink, extended range, preamble puncturing, UEQM, and DRU. Use when asked to generate test waveforms, create packets with MAC frames, configure OFDMA resource units, build trigger-based uplink transmissions, target a specific transmit duration, or build multi-packet waveforms.
What it loads into context
Frontmatter
248 tokensAlways available to the agent
SKILL.md
6,574 tokensWhen the skill is activated
Reference documents
11,207 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Workflow
- Format Selection
- Duration Targeting
- PSDU Length Access
- Key Functions
- Patterns
- Conventions
- Critical Rules
Files
SKILL.mdcore21,426 bytesmanifest.yamlasset431 bytesreferences/documentation-links.mddoc2,294 bytesreferences/eht-allocation-indices.mddoc9,350 bytesreferences/he-allocation-indices.mddoc4,657 bytesreferences/mac-frame-properties.mddoc5,289 bytesreferences/multi-packet-waveforms.mddoc2,568 bytesreferences/trigger-based-uplink.mddoc3,012 bytesreferences/uhr-waveform-generation.mddoc5,849 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-set-up-usrp-radio
When your agent uses it
Set up and verify a connection to an NI USRP radio (USRP E320, N300, N310, N320, N321, X300, X310, or X410) using Wireless Testbench. Use when connecting a USRP for the first time, configuring radio hardware, troubleshooting connection failures, or verifying a radio setup. Covers host inspection (OS, NIC type/speed/MTU), device discovery (findsdru, probesdru), UHD version checking, programmatic radio configuration, and basebandTransceiver verification. Also use when the user mentions USRP setup, radio not found, connection errors, dropped samples, or network configuration for SDR hardware.
What it loads into context
Frontmatter
210 tokensAlways available to the agent
SKILL.md
5,437 tokensWhen the skill is activated
Reference documents
1,730 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- Required References — Load Immediately
- When to Use
- When Not to Use
- Workflow
- Key Functions
- Conventions
Files
SKILL.mdcore21,744 bytesSKILL.mdcore21,744 bytesSKILL.mdcore21,744 bytesSKILL.mdcore21,744 bytesmanifest.yamlasset543 bytesreferences/bridge-detection.mddoc1,580 bytesreferences/troubleshooting.mddoc5,222 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-simulate-bluetooth-network
When your agent uses it
Simulate Bluetooth system-level networks using the Bluetooth Toolbox. Use this skill for any Bluetooth topology: BLE ACL (Asynchronous Connection-Less) data connections, CIS (Connected Isochronous Stream) and LE Audio for stereo speakers or hearing aids, BLE GAP (Generic Access Profile) connection establishment with advertising and scanning, Classic BR/EDR piconets with ACL data and SCO (Synchronous Connection-Oriented) voice links, and BLE+BR/EDR coexistence with adaptive frequency hopping. Covers bluetoothLENode, bluetoothNode, bluetoothLEConnectionConfig, bluetoothLECISConfig, bluetoothLEGAPConfig, bluetoothConnectionConfig, configureConnection, kpi (), updateChannelList, and all Bluetooth statistics.
What it loads into context
Frontmatter
204 tokensAlways available to the agent
SKILL.md
1,218 tokensWhen the skill is activated
Reference documents
8,072 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- Scenario → Reference Routing
- Node Roles
- Traffic Attachment Rules
- kpi() Availability
- Connection/Configuration Setup
- Common Mistakes
Files
SKILL.mdcore4,836 bytesmanifest.yamlasset522 bytesreferences/ble-cis.mddoc6,062 bytesreferences/ble-connection.mddoc4,978 bytesreferences/ble-gap-connection.mddoc6,425 bytesreferences/bluetooth-bredr.mddoc6,308 bytesreferences/bluetooth-coexistence.mddoc5,172 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-simulate-wireless-network
When your agent uses it
Set up and run wireless network simulations using the Wireless Network Toolbox. Use this skill when creating system-level simulations with wirelessNetworkSimulator, adding traffic sources (networkTrafficOnOff, networkTrafficFTP, networkTrafficVoIP, networkTrafficVideoConference), configuring node mobility, logging events or IQ samples, visualizing traffic, scheduling actions during simulation, running parametric sweeps, writing PCAP files with pcapWriter or technology-specific PCAP writers, registering event callbacks on wireless nodes, accessing event data fields, or combining multiple capture/visualization tools in a simulation.
What it loads into context
Frontmatter
181 tokensAlways available to the agent
SKILL.md
3,723 tokensWhen the skill is activated
Reference documents
6,779 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When Not to Use
- Node Creation
- Workflow
- Simulator Initialization
- Custom Node (`wnet.Node` Subclass)
- Vectorized Node Creation
- Batch addNodes
- Traffic Sources
- Vectorized Statistics
- Mobility
- Multi-Step Simulation
- Scheduled Actions
- Custom Channel Model
- Parametric Sweeps
- Instrumentation (R2026a)
- PCAP Capture
- Event Callbacks (`registerEventCallback`)
- Common Mistakes
Files
SKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesSKILL.mdcore15,024 bytesmanifest.yamlasset456 bytesreferences/bluetooth-capture.mddoc4,890 bytesreferences/custom-node.mddoc11,193 bytesreferences/event-tracing-iq-logging.mddoc3,209 bytesreferences/mobility-models.mddoc2,492 bytesreferences/parametric-sweep-pattern.mddoc2,190 bytesreferences/traffic-models.mddoc2,946 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubmatlab-transmit-capture-usrp
When your agent uses it
Transmit and capture RF waveforms using Wireless Testbench with NI USRP radios (X410, X310, N310, N320, N321, N300, X300, E320). Use when generating test signals, transmitting over the air, capturing IQ data, performing loopback tests, configuring multi-antenna setups, or troubleshooting dropped samples and gain settings. Covers basebandTransceiver, basebandTransmitter, basebandReceiver, continuous and once transmit modes, foreground and background capture, and UseRadioBuffer options. Also use when the user mentions transmit waveform, capture signal, IQ data, loopback, RF gain, sample rate, or antenna configuration.
What it loads into context
Frontmatter
198 tokensAlways available to the agent
SKILL.md
5,523 tokensWhen the skill is activated
Reference documents
0 tokensLoaded on request
Token counts are estimates. Scripts run separately; they are not counted as reference context.
The playbook
- When to Use
- When NOT to Use
- Prerequisites
- Choosing the Right Object
- Workflow
- Troubleshooting
- Key Functions Reference
- Conventions
Files
SKILL.mdcore21,829 bytesmanifest.yamlasset482 bytes
No excerpt is shown for this license. Read the source on GitHub.
View the complete source on GitHubSkills included
- matlab-compute-aerospace-environment
- matlab-convert-aerospace-coordinates
- matlab-analyze-reliability
- matlab-classify-tabular-data
- matlab-deploy-embedded-ai
- matlab-engineer-tabular-features
- matlab-fit-curve
- matlab-import-external-ai-model
- matlab-interpret-machine-learning-model
- matlab-train-network
- matlab-use-experiment-manager
- matlab-use-machine-learning-apps
- matlab-cosimulate-sumo-simulink
- matlab-import-driving-data
- matlab-use-ncap-protocol
- matlab-use-scenario-builder
- roadrunner-asset-mapping
- roadrunner-build-scenario-from-osc
- roadrunner-convert-lanelet2-to-rrhd
- roadrunner-core
- roadrunner-import-scene
- roadrunner-rrhd-authoring
- roadrunner-scenario-authoring
- roadrunner-scenario-simulating
- matlab-share-content
- matlab-deploy-ai-model
- matlab-deploy-embedded-code
- matlab-generate-code
- matlab-optimize-gpu-codegen
- matlab-review-fi-object-code
- simbiology-build-model
- simbiology-fit-model
- simbiology-simulate-model
- matlab-access-datafeed
- matlab-optimize-portfolio
- matlab-price-instrument
- matlab-use-spreadsheet-link
- matlab-extract-battery-features
- matlab-extract-rotating-machinery-features
- matlab-identify-linear-system
- matlab-analyze-spectral-images
- matlab-display-image
- matlab-display-volume
- matlab-integrate-pytorch-vision
- matlab-model-optics
- matlab-process-images
- matlab-read-write-point-cloud-file
- matlab-recognize-text
- matlab-register-point-clouds
- matlab-use-visual-inspection
- matlab-solve-optimization
- matlab-solve-pde
- matlab-use-symbolic-math
- matlab-apply-theme
- matlab-build-app
- matlab-build-chart
- matlab-create-live-script
- matlab-debug-code
- matlab-install-products
- matlab-list-products
- matlab-read-documentation
- matlab-review-code
- matlab-analyze-data
- matlab-choose-big-data-solution
- matlab-import-export-data
- matlab-secure-credentials
- matlab-call-python
- matlab-upgrade-mex-ic
- matlab-validate-function-arguments
- matlab-configure-toml-project
- matlab-instrument-opentelemetry-tracing
- matlab-modernize-code
- matlab-optimize-memory
- matlab-optimize-performance
- matlab-package-toolbox
- matlab-run-tests
- matlab-use-package-manager
- matlab-write-help
- matlab-write-performance-tests
- matlab-write-tests
- matlab-diagnose-parfor
- matlab-discover-clusters
- matlab-set-up-worker-state
- matlab-setup-gpu
- matlab-use-thread-pool
- matlab-design-radar
- matlab-design-radar-waveform
- matlab-import-tracking-data
- matlab-simulate-radar-detections
- matlab-connect-databricks
- matlab-generate-report
- matlab-use-database
- matlab-use-duckdb
- matlab-analyze-ams-waveform
- matlab-analyze-antenna-structures
- matlab-analyze-em
- matlab-analyze-pcb-pdn
- matlab-assemble-pcb-layout
- matlab-design-antenna
- matlab-design-pcb-coupler
- matlab-design-pcb-filter
- matlab-design-pcb-passive
- matlab-design-pcb-transmission-line
- matlab-export-session-script
- matlab-integrate-antenna
- matlab-integrate-pcb-circuit
- matlab-manage-pcb-material
- matlab-model-ams-systems
- matlab-model-rf
- matlab-model-serdes-systems
- matlab-model-via
- matlab-optimize-pcb-design
- matlab-read-pcb-layout
- matlab-write-pcb-layout
- matlab-compute-gnss-position
- matlab-connect-mavlink
- matlab-create-uav-scenario
- matlab-fuse-inertial-sensors
- matlab-model-robot-kinematics
- matlab-plan-robot-motion
- matlab-analyze-spectrum
- matlab-analyze-time-frequency-content
- matlab-configure-scope-object
- matlab-design-adaptive-filter
- matlab-design-digital-filter
- matlab-design-dsphdl-ddc
- matlab-evaluate-acoustic-metrics
- matlab-extract-signal-features
- matlab-play-record-audio
- matlab-prepare-signal-data
- matlab-process-streaming-audio
- matlab-write-audio-plugin
- matlab-build-industrial-hmi
- matlab-call-nidaqmx
- matlab-connect-arduino
- matlab-connect-bluetooth-low-energy-device
- matlab-create-custom-arduino-library
- matlab-discover-hardware
- matlab-enhance-camera-image
- matlab-find-pi-assets
- matlab-import-export-vehicle-data
- matlab-modernize-daq
- matlab-use-cameras
- matlab-use-opcua-client
- matlab-use-vehicle-network
- matlab-add-awgn
- matlab-design-ofdm-system
- matlab-detect-capture-usrp
- matlab-generate-5g-waveform
- matlab-generate-ble-waveform
- matlab-generate-gnss-waveform
- matlab-generate-wlan-waveform
- matlab-set-up-usrp-radio
- matlab-simulate-bluetooth-network
- matlab-simulate-wireless-network
- matlab-transmit-capture-usrp
Repository facts
- License
- No license detected
- Created
- Apr 3, 2026
- Last pushed
- Nov 5, 2026
- Forks
- 148
- Open issues
- 9
- Project activity
- Active
Rank over the last 12 weeks
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81 earlier periods
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Before you install
Network or broad shellAutomated signals, not a guarantee
Checked Nov 3, 2026
Not fully analyzed: some files were too long, unreadable or missing. This never lowers the level.
Show 202 notes
skills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-engineer-tabular-features/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/matlab-cosimulate-sumo-simulink/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/matlab-cosimulate-sumo-simulink/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/matlab-use-scenario-builder/SKILL.md:205Analysis incomplete: physical or joined line exceeds character limitskills-catalog/automotive/matlab-use-scenario-builder/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/matlab-use-scenario-builder/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/roadrunner-asset-mapping/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/roadrunner-asset-mapping/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzedskills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md:1Analysis incomplete: Referenced executable target unavailable; not analyzed
- 3 broad permissionsin 3 files: matlab-apply-theme/SKILL.md:1 matlab-build-app/SKILL.md:1 matlab-build-chart/SKILL.md:1
- 31 dangerous shell commandsin 13 files: matlab-modernize-code/references/core-functions-guidance.md:343 matlab-set-up-usrp-radio/SKILL.md:223 matlab-modernize-code/references/statistics-ml-guidance.md:28 and 10 more
- 1,470 network referencesin 400 files: matlab-evaluate-acoustic-metrics/references/noise-compliance.md:11 matlab-use-duckdb/SKILL.md:2 matlab-evaluate-acoustic-metrics/SKILL.md:11 and 397 more
- No hidden or obfuscated text
- 3 instruction override signalsin 2 files: matlab-use-experiment-manager/references/common.md:205 matlab-connect-arduino/SKILL.md:108
- 12 executable scriptsin 12 files: matlab-apply-theme/references/component-colors.md:1 matlab-apply-theme/references/external-schemes.md:1 matlab-apply-theme/references/theme-api.md:1 and 9 more
- 19 references to secretsin 7 files: matlab-use-package-manager/references/api-and-gotchas.md:33 matlab-import-external-ai-model/references/keras-tf-keras-downgrade.md:27 matlab-use-package-manager/SKILL.md:242 and 4 more
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.claude-plugin/marketplace.json
skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md
- Network accessline 11
orientation parameters for aerospace vehicle analysis, spacecraft environment modeling, or navigation corrections. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
modeling, or navigation corrections. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/aerospace/matlab-compute-aerospace-environment/manifest.yaml
skills-catalog/aerospace/matlab-convert-aerospace-coordinates/SKILL.md
- Network accessline 11
Rodrigues vector). Also use when the user asks about aerospace coordinate systems, reference frames, or rotation conventions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
systems, reference frames, or rotation conventions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/aerospace/matlab-convert-aerospace-coordinates/manifest.yaml
skills-catalog/aerospace/matlab-convert-aerospace-coordinates/references/coordinate-systems.md
skills-catalog/ai-and-statistics/matlab-analyze-reliability/SKILL.md
- Network accessline 2
name: matlab-analyze-reliability description: Use this skill when fitting accelerated life models, computing mean time to failure (MTTF), B10 life and similar quantities, fitting life distributions like Weibull for reliability analysis, com - Network accessline 3
description: Use this skill when fitting accelerated life models, computing mean time to failure (MTTF), B10 life and similar quantities, fitting life distributions like Weibull for reliability analysis, comparing distribution fits, computi - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-analyze-reliability/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-classify-tabular-data/SKILL.md
- Network accessline 12
or wants cost-sensitive learning or an arbitrary class-prior vector (this skill only supports the built-in uniform-prior toggle for imbalanced data). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
built-in uniform-prior toggle for imbalanced data). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-classify-tabular-data/manifest.yaml
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/SKILL.md
- Network accessline 14
importNetworkFromONNX, importNetworkFromTensorFlow, importNetworkFromKeras, dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
dlquantizer, exportNetworkToSimulink, or Embedded Coder with AI models. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 196
- **Look up function signatures from MATLAB's help or the online reference page, not from this skill.** Argument lists, name-value pair (NVP) defaults, and supported-layer enumerations live in MATLAB's `help <function>` output and on the fu - Network accessline 197
1. **First** try `help <function>` in the live MATLAB session. Fast and reflects the actually-installed release of the toolbox or support package. 2. If `help` returns only a stub like "Run doc <function> for more information." — common f - Network accessline 198
2. If `help` returns only a stub like "Run doc <function> for more information." — common for support-package functions whose help redirects to the browser doc — **fall back to the agent's web browsing of the online reference page** at `htt - Network accessline 249
MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See [www.mathworks.com/trademarks](https://www.mathworks.com/trademarks) for a list of additional trademarks. Other product or brand names may be trademarks or registered
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/manifest.yaml
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md
- Network accessline 38
| Standard `dlnetwork` | Supported (float32 C) | Supported (float32 C) | | Projected network (`lstmProjectedLayer`, `gruProjectedLayer`, or `ProjectedLayer` over conv/FC/stateful-I/O LSTM/GRU) | **Supported** — generic C/C++ only, no MKL-DN - Network accessline 40
| Quantized network from `quantize()` | **NOT supported** — use the pre-quantized network | **SUPPORTED** — generates fixed-point C (int8/int16/int32). This is the recommended path for quantized deployment. See [Export Quantized Network to - Network accessline 328
Sources: - [Supported Deep Learning Toolbox Blocks with CMSIS for ARM Cortex-M](https://www.mathworks.com/help/ecoder/armcortexm/ug/supported-deep-learning-blocks-with-cmsis-for-armcortexm.html) — Simulink block replacement (INT8 CMSIS-NN) - Network accessline 329
- [Supported Deep Learning Toolbox Blocks with CMSIS for ARM Cortex-M](https://www.mathworks.com/help/ecoder/armcortexm/ug/supported-deep-learning-blocks-with-cmsis-for-armcortexm.html) — Simulink block replacement (INT8 CMSIS-NN) - Network accessline 330
- [Code Generation for Matrix Multiplication in DL Layers with CMSIS](https://www.mathworks.com/help/ecoder/armcortexm/ug/code-generation-for-matrix-multiplication-in-dl-layers-with-cmsis-for-armcortexm.html) — float32 mat-mult replacement
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/references/pattern1/compression-projection.md
- Network accessline 5
release-specific limitations (such as restrictions on layers that share learnable parameters via weight tying), see the [`compressNetworkUsingProjection` reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingpr - Network accessline 7
[`compressNetworkUsingProjection` reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingprojection.html). - Network accessline 103
layer (e.g., `featureInputLayer`, `sequenceInputLayer`) or specify a format that includes `"B"` during import. For the full list of name-value arguments see the [`compressNetworkUsingProjection` reference page](https://www.mathworks.com/hel - Network accessline 105
[`compressNetworkUsingProjection` reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingprojection.html).
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/references/pattern1/compression-pruning.md
- Network accessline 28
For the full list of name-value arguments, defaults, and behavior, consult the function's help (`help compressNetworkUsingTaylorPruning`) or the [reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingtaylorprun - Network accessline 29
function's help (`help compressNetworkUsingTaylorPruning`) or the [reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingtaylorpruning.html) rather than relying on a list in this file. Two name-value arguments - Network accessline 30
[reference page](https://www.mathworks.com/help/deeplearning/ref/compressnetworkusingtaylorpruning.html)
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/references/pattern1/compression-quantization.md
- Network accessline 29
1. **Doc:** [Supported Layers for Quantization](https://www.mathworks.com/help/deeplearning/ug/supported-layers-for-quantization.html) — authoritative, release-versioned. - Network accessline 141
Embedded Coder then generates integer C code (int8/int16/int32) via `slbuild`. This is the recommended path for fixed-point embedded deployment. See: https://www.mathworks.com/help/deeplearning/ug/export-quantized-network-to-simulink. - Network accessline 143
See: https://www.mathworks.com/help/deeplearning/ug/export-quantized-network-to-simulink.html - Network accessline 221
This pseudo-code mirrors the structure of the [Compress Sequence Classification Network for Road Damage Detection](https://www.mathworks.com/help/deeplearning/ug/compress-sequence-classification-network-for-road-damage-detection.html) - Network accessline 222
[Compress Sequence Classification Network for Road Damage Detection](https://www.mathworks.com/help/deeplearning/ug/compress-sequence-classification-network-for-road-damage-detection.html)
skills-catalog/ai-and-statistics/matlab-deploy-embedded-ai/references/pattern1/simulink-integration.md
- Network accessline 71
Reference: https://www.mathworks.com/help/deeplearning/ug/export-quantized-network-to-simulink.html
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/SKILL.md
- Network accessline 7
assesses, and delivers on the resulting table. Not for multi-response problems, model training, or raw data acquisition. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 8
problems, model training, or raw data acquisition. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 9
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 345
MATLAB and Simulink are registered trademarks of The MathWorks, Inc. See [www.mathworks.com/trademarks](https://www.mathworks.com/trademarks) for a list - Network accessline 346
[www.mathworks.com/trademarks](https://www.mathworks.com/trademarks) for a list
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/manifest.yaml
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/assess.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/deliver.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/domain-routing.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/feature-pool.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/intake.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/provider-protocol.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/report.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/reproduce-pool.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/references/select.md
skills-catalog/ai-and-statistics/matlab-engineer-tabular-features/scripts/nogueiraStability.m
- Network accessline 41
% Nogueira S, Sechidis K, Brown G. "On the Stability of Feature Selection % Algorithms." Journal of Machine Learning Research, 18(174):1-54, 2018. % https://jmlr.org/papers/v18/17-514.html (estimator: eq. 2, Sec. 2) - Network accessline 43
% https://jmlr.org/papers/v18/17-514.html (estimator: eq. 2, Sec. 2)
skills-catalog/ai-and-statistics/matlab-fit-curve/SKILL.md
- Network accessline 2
name: matlab-fit-curve description: Fit curves and surfaces interactively with the Curve Fitter app for a complete no-code fitting workflow. Invoke this skill when the Curve Fitter app, cftool, curveFitter, or "curve fitting tool/app" is me - Network accessline 3
description: Fit curves and surfaces interactively with the Curve Fitter app for a complete no-code fitting workflow. Invoke this skill when the Curve Fitter app, cftool, curveFitter, or "curve fitting tool/app" is mentioned in any way. Als - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-fit-curve/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-import-external-ai-model/SKILL.md
- Network accessline 11
when user mentions any of these functions, file formats, or encounters import errors, unsupported operator warnings, 0 learnables, or uninitialized networks. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
errors, unsupported operator warnings, 0 learnables, or uninitialized networks. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Access to secretsline 249
[Credential-related source omitted]
skills-catalog/ai-and-statistics/matlab-import-external-ai-model/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-import-external-ai-model/references/keras-tf-keras-downgrade.md
skills-catalog/ai-and-statistics/matlab-import-external-ai-model/references/pytorch-export-guidance.md
skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model/SKILL.md
- Network accessline 2
name: matlab-interpret-machine-learning-model description: Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the mod - Network accessline 3
description: Interpret and explain a trained tabular machine-learning model (classification or regression) in MATLAB. Find which predictors, features, or columns matter most; explain why the model made a specific prediction, including diagn - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-interpret-machine-learning-model/manifest.yaml
skills-catalog/ai-and-statistics/matlab-train-network/SKILL.md
- Network accessline 11
DO NOT reason from your training data about dlaccelerate and tracing correctness. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
correctness. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-train-network/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-use-experiment-manager/SKILL.md
- Network accessline 6
asks to add/delete/edit experiments, or wants parameter changes reflected in the UI. Combines experiment creation (from code analysis) with frontend UI synchronization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl - Network accessline 7
Combines experiment creation (from code analysis) with frontend UI synchronization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 8
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-use-experiment-manager/manifest.yaml
skills-catalog/ai-and-statistics/matlab-use-experiment-manager/references/common.md
- Network accessline 34
what this skill documents. If the user asks about details not covered here, refer them to the official documentation: - General-Purpose: https://www.mathworks.com/help/matlab/ref/experimentmanager-app.html - Network accessline 35
the official documentation: - General-Purpose: https://www.mathworks.com/help/matlab/ref/experimentmanager-app.html - Deep Learning: https://www.mathworks.com/help/deeplearning/ref/experimentmanager-app.html - Network accessline 36
- General-Purpose: https://www.mathworks.com/help/matlab/ref/experimentmanager-app.html - Network accessline 37
- Deep Learning: https://www.mathworks.com/help/deeplearning/ref/experimentmanager-app.html - Instruction override signalline 205
Not every step applies to every operation. Low-stakes ops skip confirmation. Simple requests - Instruction override signalline 337
changes, nTrials changes, etc. No update is too small to skip confirmation.
skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps/SKILL.md
- Network accessline 2
name: matlab-use-machine-learning-apps description: "Use when the user wants to train, compare, or export machine learning models using Classification Learner or Regression Learner — including opening the app, loading data, training models, - Network accessline 3
description: "Use when the user wants to train, compare, or export machine learning models using Classification Learner or Regression Learner — including opening the app, loading data, training models, evaluating metrics, comparing results, - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/ai-and-statistics/matlab-use-machine-learning-apps/manifest.yaml
skills-catalog/automotive/matlab-cosimulate-sumo-simulink/SKILL.md
- Network accessline 9
Also use when the user mentions SumoInterfaceLibrary, .sumocfg files, or wants to connect Simulink to an external traffic simulator. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
or wants to connect Simulink to an external traffic simulator. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/matlab-cosimulate-sumo-simulink/manifest.yaml
skills-catalog/automotive/matlab-import-driving-data/SKILL.md
- Network accessline 2
name: matlab-import-driving-data description: "Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run prepr - Network accessline 3
description: "Import recorded driving sensor data (GPS, camera, lidar, actor tracks, lanes) into scenariobuilder.* objects (GPSData, CameraData, LidarData, ActorTrackData, Trajectory, laneData) and run preprocessing — synchronize, offset co - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/matlab-import-driving-data/manifest.yaml
skills-catalog/automotive/matlab-use-ncap-protocol/SKILL.md
- Network accessline 8
ScenarioDescriptor, ScenarioDescriptorPlot, ncapScore, ncapReport, exportReport, configureVUT, assessmentTable, Euro NCAP, CCRs, CCRm, CCRb, CCFtap, CCCscp, CPNA, CPFA, CBNA, variant generation. license: https://www.mathworks.com/content/ - Network accessline 9
assessmentTable, Euro NCAP, CCRs, CCRm, CCRb, CCFtap, CCCscp, CPNA, CPFA, CBNA, variant generation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/matlab-use-ncap-protocol/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/matlab-use-scenario-builder/SKILL.md
- Network accessline 2
name: matlab-use-scenario-builder description: "Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BU - Network accessline 3
description: "Generate driving scenes, scenarios, road surfaces, and 3D content from scenariobuilder.* sensor data (GPS, camera, lidar, actor tracks) using Scenario Builder for Automated Driving Toolbox. BUILD, EXPORT, or AUGMENT a virtual - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/matlab-use-scenario-builder/manifest.yaml
skills-catalog/automotive/matlab-use-scenario-builder/references/example-roadrunner-scenario.md
- Network accessline 11
dataFolder = tempdir; dataFilename = "PandasetSeq90_94.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename; - Network accessline 12
dataFilename = "PandasetSeq90_94.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename; filePath = fullfile(dataFolder,dataFilename); - Network accessline 13
url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename;
skills-catalog/automotive/matlab-use-scenario-builder/references/example-scenario-from-gps-and-tracks.md
- Network accessline 13
dataFolder = tempdir; dataFilename = "PandasetSeq90_94.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename; - Network accessline 14
dataFilename = "PandasetSeq90_94.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename; filePath = fullfile(dataFolder,dataFilename); - Network accessline 15
url = "https://ssd.mathworks.com/supportfiles/driving/data/" + dataFilename;
skills-catalog/automotive/matlab-use-scenario-builder/references/visualization-patterns.md
- Dangerous shell operationline 76
When running video composition through MCP eval (each call ~90s timeout), reduce frame targets:
skills-catalog/automotive/matlab-use-scenario-builder/references/workflow-08-lane-localization.md
- Network accessline 11
> > **Official MathWorks docs:** > - Lane extraction: <https://www.mathworks.com/help/driving/ug/extract-lane-information-from-recorded-camera-data-for-scene-generation.html> - Network accessline 12
> **Official MathWorks docs:** > - Lane extraction: <https://www.mathworks.com/help/driving/ug/extract-lane-information-from-recorded-camera-data-for-scene-generation.html> > - `localizeEgoUsingLanes` reference: <https://www.mathworks.com/h - Network accessline 13
> - Lane extraction: <https://www.mathworks.com/help/driving/ug/extract-lane-information-from-recorded-camera-data-for-scene-generation.html> - Network accessline 14
> - `localizeEgoUsingLanes` reference: <https://www.mathworks.com/help/driving/ref/localizeegousinglanes.html>
skills-catalog/automotive/matlab-use-scenario-builder/references/workflow-13-event-extraction.md
- Network accessline 10
Identify critical driving events (lane changes, hard braking, cut-ins, turns) from recorded sensor data. There is no single public function — use the helper-based pipeline from the [example](https://www.mathworks.com/help/driving/ug/extract
skills-catalog/automotive/matlab-use-scenario-builder/references/workflow-16-aerial-lidar-augmentation.md
- Network accessline 31
| User has | Entry point | Notes | |----------|-------------|-------| | Single lat/lon (or lat/lon/alt) in US | **USGS 3DEP** (`https://apps.nationalmap.gov/lidar-explorer/`) — Ctrl-drag a rectangular AOI, download the LAZ tile | Free, well - Network accessline 32
|----------|-------------|-------| | Single lat/lon (or lat/lon/alt) in US | **USGS 3DEP** (`https://apps.nationalmap.gov/lidar-explorer/`) — Ctrl-drag a rectangular AOI, download the LAZ tile | Free, well-tested. The MathWorks doc example - Network accessline 33
| Single lat/lon (or lat/lon/alt) in US | **USGS 3DEP** (`https://apps.nationalmap.gov/lidar-explorer/`) — Ctrl-drag a rectangular AOI, download the LAZ tile | Free, well-tested. The MathWorks doc example uses a prepackaged AOI: `https://ss - Network accessline 58
dataFolder = tempdir; lidarDataFileName = "USGSLidarExplorerData.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + lidarDataFileName; - Network accessline 59
lidarDataFileName = "USGSLidarExplorerData.zip"; url = "https://ssd.mathworks.com/supportfiles/driving/data/" + lidarDataFileName; zipPath = fullfile(dataFolder, lidarDataFileName); - Network accessline 60
url = "https://ssd.mathworks.com/supportfiles/driving/data/" + lidarDataFileName;
skills-catalog/automotive/roadrunner-asset-mapping/SKILL.md
- Network accessline 5
signs, signals, barriers, objects, and lane types to RoadRunner asset paths. Use when converting map formats to RRHD, resolving asset paths, or assigning visual assets to HD Map objects. license: https://www.mathworks.com/content/dam/math - Network accessline 6
map formats to RRHD, resolving asset paths, or assigning visual assets to HD Map objects. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md user-invocable: false - Network accessline 7
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-asset-mapping/manifest.yaml
skills-catalog/automotive/roadrunner-build-scenario-from-osc/SKILL.md
- Network accessline 12
to world coordinates), construct mapping, relative references, trajectory/route handling, parameter expressions, catalog references, and phase logic topology. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.m - Network accessline 13
handling, parameter expressions, catalog references, and phase logic topology. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-build-scenario-from-osc/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-convert-lanelet2-to-rrhd/SKILL.md
- Network accessline 5
converting Lanelet2 maps into RoadRunner Scene Builder, building driving scenes from open-source map data, or transforming road network definitions for simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/lice - Network accessline 6
open-source map data, or transforming road network definitions for simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 7
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-convert-lanelet2-to-rrhd/manifest.yaml
skills-catalog/automotive/roadrunner-core/SKILL.md
- Network accessline 2
name: roadrunner-core description: "Foundation skill for all RoadRunner workflows: MATLAB path setup, connection, project/scene/scenario lifecycle, world settings, handle management, status, and close. Use when connecting to RoadRunner, man - Network accessline 3
description: "Foundation skill for all RoadRunner workflows: MATLAB path setup, connection, project/scene/scenario lifecycle, world settings, handle management, status, and close. Use when connecting to RoadRunner, managing projects/scenes/ - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-core/manifest.yaml
skills-catalog/automotive/roadrunner-import-scene/SKILL.md
- Network accessline 6
OpenDRIVE, or other RoadRunner-supported formats for simulation, or verifying Lanelet2-to-RRHD conversion results visually. Requires rrApp handle from roadrunner-core. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/ - Network accessline 7
Lanelet2-to-RRHD conversion results visually. Requires rrApp handle from roadrunner-core. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 8
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-import-scene/manifest.yaml
skills-catalog/automotive/roadrunner-rrhd-authoring/SKILL.md
- Network accessline 6
networks for simulation and testing automated driving systems, or assembling RRHD maps from Lanelet2 or other HD map sources. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 7
from Lanelet2 or other HD map sources. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 8
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-rrhd-authoring/manifest.yaml
skills-catalog/automotive/roadrunner-scenario-authoring/SKILL.md
- Network accessline 8
Triggers on: roadrunnerAPI, scenario authoring, add actor, create route, phase logic, cut-in scenario, pedestrian crossing, scenario from MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
phase logic, cut-in scenario, pedestrian crossing, scenario from MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-scenario-authoring/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-scenario-simulating/SKILL.md
- Network accessline 10
Simulink co-sim blocks, and publishActorBehavior. NOT for project setup, scene building, scenario authoring, or trajectory export. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
NOT for project setup, scene building, scenario authoring, or trajectory export. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/automotive/roadrunner-scenario-simulating/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/cloud-solutions/matlab-share-content/SKILL.md
- Network accessline 10
or when an AI agent has generated MATLAB code locally and the user wants to share it or run it in MATLAB Online. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
share it or run it in MATLAB Online. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 75
[](URL_HERE) - Network accessline 83
https://matlab.mathworks.com/open/github/v1?repo=<owner>/<repo>&file=<relative-path> - Network accessline 86
| Parameter | Required | Description | |-----------|----------|-------------| | `repo` | Yes | `owner/reponame` (no `https://github.com/` prefix) | - Network accessline 87
|-----------|----------|-------------| | `repo` | Yes | `owner/reponame` (no `https://github.com/` prefix) | | `host` | No | GitHub host (default: `github.com`). Required for GitHub Enterprise (e.g., `github.mathworks.com`) | - Network accessline 88
| `repo` | Yes | `owner/reponame` (no `https://github.com/` prefix) | - Network accessline 97
**URL generator tool:** Users can also generate these URLs interactively at `https://www.mathworks.com/products/matlab-online/git.html` - Network accessline 102
https://matlab.mathworks.com/open/matlabdrive/v1?namespace=SHARED&id=<share-uuid>&file=<filename> - Network accessline 116
https://matlab.mathworks.com/open/fileexchange/v1?id=<submission-id> - Network accessline 137
If `gh` is not installed, guide the user to install it (e.g., `brew install gh` on macOS, or visit https://cli.github.com). If not authenticated, have the user run `gh auth login` before proceeding. - Network accessline 158
https://matlab.mathworks.com/open/github/v1?repo=<owner>/<repo>&file=<filename> - Network accessline 169
1. Go to `https://drive.mathworks.com/` - Network accessline 177
https://drive.matlab.com/sharing/<uuid>/<filename> - Network accessline 182
https://matlab.mathworks.com/open/matlabdrive/v1?namespace=SHARED&id=<uuid>&file=<filename> - Network accessline 195
1. Go to `https://www.mathworks.com/matlabcentral/fileexchange/` - Network accessline 201
https://www.mathworks.com/matlabcentral/fileexchange/<ID>-<title-slug> - Network accessline 206
https://matlab.mathworks.com/open/fileexchange/v1?id=<ID> - Network accessline 211
https://matlab.mathworks.com/open/fileexchange/v1?id=<ID>&file=<filename> - Network accessline 224
| Using `?sharing=<uuid>` for MATLAB Drive | Wrong parameter format | Use `?namespace=SHARED&id=<uuid>&file=...` | | Omitting `namespace` for Drive URLs | URL won't resolve without it | Always include `namespace=SHARED` | | Including `https - Network accessline 225
| Omitting `namespace` for Drive URLs | URL won't resolve without it | Always include `namespace=SHARED` | | Including `https://github.com/` in the `repo` param | Format is `owner/repo` only | Strip the domain: `aanithap/my-project` not `ht - Network accessline 226
| Including `https://github.com/` in the `repo` param | Format is `owner/repo` only | Strip the domain: `aanithap/my-project` not `https://github.com/aanithap/my-project` |
skills-catalog/cloud-solutions/matlab-share-content/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-deploy-ai-model/SKILL.md
- Network accessline 13
LiteRT, TFLite, TensorFlow Lite, Simulink, slbuild, PyTorch ExportedProgram block, MATLAB Function block, dlosslib, loadLiteRTModel. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 14
MATLAB Function block, dlosslib, loadLiteRTModel. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 15
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-deploy-ai-model/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-deploy-ai-model/references/pytorch-data-layout.md
skills-catalog/code-generation/matlab-deploy-embedded-code/SKILL.md
- Network accessline 8
processor-in-the-loop testing, memory constraints, and the MEX→SIL→PIL verification progression. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
progression. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-deploy-embedded-code/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-generate-code/SKILL.md
- Network accessline 14
host-target InstructionSetExtensions, SIMDAcceleration, OptimizeReductions, host SIMD tuning, host OpenMP, codegen performance. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
host SIMD tuning, host OpenMP, codegen performance. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-generate-code/manifest.yaml
skills-catalog/code-generation/matlab-generate-code/references/write-numerical-style.md
- Network accessline 122
Adhere to the [MathWorks MATLAB Coding Guidelines](https://github.com/mathworks/MATLAB-Coding-Guidelines):
skills-catalog/code-generation/matlab-optimize-gpu-codegen/SKILL.md
- Network accessline 9
GPU memory transfers, improve kernel parallelism, rewrite MATLAB for CUDA, or run gpuPerformanceAnalyzer. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
or run gpuPerformanceAnalyzer. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-optimize-gpu-codegen/manifest.yaml
skills-catalog/code-generation/matlab-review-fi-object-code/SKILL.md
- Network accessline 2
name: matlab-review-fi-object-code description: Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, n - Network accessline 3
description: Reviews MATLAB fixed-point (fi) code for performance, code generation efficiency, and correctness. Identifies antipatterns and suggests idiomatic improvements. Use when reviewing fi, fimath, numerictype, or quantizenumeric code - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/code-generation/matlab-review-fi-object-code/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-review-fi-object-code schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-build-model/SKILL.md
- Network accessline 2
name: simbiology-build-model description: "Build, modify, and diagram SimBiology models — API reference, helper functions, and layout patterns. Use when constructing or editing models programmatically or visually." license: https://www.math - Network accessline 3
description: "Build, modify, and diagram SimBiology models — API reference, helper functions, and layout patterns. Use when constructing or editing models programmatically or visually." license: https://www.mathworks.com/content/dam/mathwor - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-build-model/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-fit-model/SKILL.md
- Network accessline 2
name: simbiology-fit-model description: "Fit SimBiology model parameters to data — fitproblem, population NLME, virtual patients, and NCA. Use when asked to fit, estimate, calibrate, or compute PK metrics." license: https://www.mathworks.co - Network accessline 3
description: "Fit SimBiology model parameters to data — fitproblem, population NLME, virtual patients, and NCA. Use when asked to fit, estimate, calibrate, or compute PK metrics." license: https://www.mathworks.com/content/dam/mathworks/lic - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-fit-model/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-simulate-model/SKILL.md
- Network accessline 2
name: simbiology-simulate-model description: "Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters." license: - Network accessline 3
description: "Simulate SimBiology models — ODE, stochastic (SSA), scenarios, and sensitivity analysis. Use when asked to run, simulate, predict, explore what-if, or identify influential parameters." license: https://www.mathworks.com/conten - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-biology/simbiology-simulate-model/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-access-datafeed/SKILL.md
- Network accessline 7
and LSEG Datastream (historical data via datastreamws). Use when connecting to any of these data providers from MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 8
data providers from MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 9
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-access-datafeed/manifest.yaml
- Network accessline 1
# manifest.yaml — Tooling metadata for matlab-access-datafeed schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-access-datafeed/references/bloomberg.md
- Access to secretsline 170
[Credential-related source omitted]
skills-catalog/computational-finance/matlab-access-datafeed/references/fred.md
- Network accessline 20
% Using fetch — returns timetable via d.DATA{1} d = fetch(c, "GNP"); - Network accessline 21
d = fetch(c, "GNP"); - Network accessline 24
% Both support date ranges d = series(c, "GNP", "observations", "01/01/2020", "12/31/2024"); d = fetch(c, "GNP", "01/01/2020", "12/31/2024"); - Network accessline 26
d = fetch(c, "GNP", "01/01/2020", "12/31/2024");
skills-catalog/computational-finance/matlab-access-datafeed/references/haver.md
- Network accessline 65
% haver/haverdirect — fetch with frequency as 5th positional argument % Frequency codes: "D" (daily), "M" (monthly), "Q" (quarterly), "A" (annual), "W" (weekly) d = fetch(c, "GDPQ", datetime(2020,1,1), datetime(2024,12,31), "Q"); - Network accessline 66
% Frequency codes: "D" (daily), "M" (monthly), "Q" (quarterly), "A" (annual), "W" (weekly) d = fetch(c, "GDPQ", datetime(2020,1,1), datetime(2024,12,31), "Q"); % ↑conn ↑var ↑startDate ↑endDate ↑freq (5th arg) - Network accessline 67
d = fetch(c, "GDPQ", datetime(2020,1,1), datetime(2024,12,31), "Q"); - Network accessline 70
% haverview — fetch without frequency (no frequency argument) d = fetch(c, "GDPQ", datetime(2020,1,1), datetime(2024,12,31)); - Network accessline 71
d = fetch(c, "GDPQ", datetime(2020,1,1), datetime(2024,12,31));
skills-catalog/computational-finance/matlab-optimize-portfolio/SKILL.md
- Network accessline 2
name: matlab-optimize-portfolio description: Help users formulate and solve portfolio optimization problems using Financial Toolbox's Portfolio object. Covers mean-variance (Markowitz), maximum Sharpe ratio (tangency), and efficient frontie - Network accessline 3
description: Help users formulate and solve portfolio optimization problems using Financial Toolbox's Portfolio object. Covers mean-variance (Markowitz), maximum Sharpe ratio (tangency), and efficient frontier workflows. Use when users ask - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-optimize-portfolio/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-price-instrument/SKILL.md
- Network accessline 12
Black-Derman-Toy, Cox-Ingersoll-Ross, Linear Gaussian 2 Factor (G2PP), Brace-Gatarek-Musiela (BGM), SABR-BGM, RoughBergomi, RoughHeston. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
Brace-Gatarek-Musiela (BGM), SABR-BGM, RoughBergomi, RoughHeston. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-price-instrument/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-use-spreadsheet-link/SKILL.md
- Network accessline 2
name: matlab-use-spreadsheet-link description: Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPut - Network accessline 3
description: Exchange data between Excel and MATLAB using Spreadsheet Link VBA macros and worksheet functions. Use when writing Excel VBA macros that call MLPutMatrix, MLGetMatrix, MLPutVar, MLGetVar, MLPutRanges, MLEvalString, MLGetFigure, - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/computational-finance/matlab-use-spreadsheet-link/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-extract-battery-features/SKILL.md
- Network accessline 10
Triggers on battery* functions such as batteryTestDataParser, batteryTestFeatureExtractor, batteryPulseFeatures, batteryEISFeatures. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
batteryTestFeatureExtractor, batteryPulseFeatures, batteryEISFeatures. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-extract-battery-features/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/SKILL.md
- Network accessline 2
name: matlab-extract-rotating-machinery-features description: "Extract features from signals collected on rotating machinery components, including motors, pumps, fans, gears, bearings, and shafts. Signals can include vibration, electrical, - Network accessline 3
description: "Extract features from signals collected on rotating machinery components, including motors, pumps, fans, gears, bearings, and shafts. Signals can include vibration, electrical, or environmental sensor measurements. Use when de - Network accessline 4
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/references/bearings.md
- Network accessline 58
- `[es,f,env,t] = envspectrum(x,fs)` — pass a timetable `xt` in place of `(x,fs)`; returns envelope spectrum, frequency vector, envelope signal, and time vector. - Name-value: `Method` (`"demod"` default | `"hilbert"`), `Band` (two-elemen - Network accessline 60
- Docs: <https://www.mathworks.com/help/signal/ref/envspectrum.html> - Network accessline 62
- **`envelope`** (Signal Processing Toolbox, R2015b) — signal envelope. - `[yupper,ylower] = envelope(x)` (analytic, default); other methods: `envelope(x,fl,'analytic')` / `envelope(x,wl,'rms')` / `envelope(x,np,'peak')`. - Docs: <https - Network accessline 64
- Docs: <https://www.mathworks.com/help/signal/ref/envelope.html> - Network accessline 66
- **`kurtogram`** (Signal Processing Toolbox, R2018a) — fast kurtogram to select a bandpass band. - `[kgram,f,w,fc,wc,bw] = kurtogram(x,sampx)` — `sampx` is sample rate or sample time (or pass a timetable `xt`). `fc` is the center frequen - Network accessline 68
- Docs: <https://www.mathworks.com/help/signal/ref/kurtogram.html> - Network accessline 70
- **`spectralKurtosis`** (Signal Processing Toolbox, R2019a) — spectral kurtosis of a signal. - `kurtosis = spectralKurtosis(x,f)` — `f` is the sample rate/time or frequency vector (or pass a timetable `xt`). - Docs: <https://www.mathwo - Network accessline 72
- Docs: <https://www.mathworks.com/help/signal/ref/spectralkurtosis.html> - Network accessline 77
- `[FB,info] = bearingFaultBands(FR,NB,DB,DP,beta)` — `FR` shaft/inner-race speed (positive scalar), `NB` number of balls/rollers (positive integer), `DB` ball/roller diameter, `DP` pitch diameter, `beta` contact angle **in degrees** (non-n - Network accessline 79
- Docs: <https://www.mathworks.com/help/predmaint/ref/bearingfaultbands.html> - Network accessline 81
- **`faultBands`** (Predictive Maintenance Toolbox, R2019b) — generic fault frequency bands from a fundamental and its sidebands. - `[FB,info] = faultBands(F0,N0)`, or add sideband spacing/orders with `faultBands(F0,N0,F1,N1)`. - Docs: - Network accessline 83
- Docs: <https://www.mathworks.com/help/predmaint/ref/faultbands.html> - Network accessline 88
- `spectralMetrics = faultBandMetrics(psd,freqGrid,FB)` — `psd` power spectral density, `freqGrid` matching frequency vector, `FB` the Nx2 band array from `bearingFaultBands`/`faultBands`. **Three positional inputs; do not pass labels or an - Network accessline 90
- Docs: <https://www.mathworks.com/help/predmaint/ref/faultbandmetrics.html> - Network accessline 94
- When applicable, fetch [Vibration Analysis of Rotating Machinery](https://www.mathworks.com/help/signal/ug/vibration-analysis-of-rotating-machinery.html). - Network accessline 95
- When applicable, fetch [Rolling Element Bearing Fault Diagnosis](https://www.mathworks.com/help/predmaint/ug/Rolling-Element-Bearing-Fault-Diagnosis.html).
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/references/gears.md
- Network accessline 49
- `[FB,info] = gearMeshFaultBands(FR,Ni,No)` — `FR` input-gear rotational speed (positive scalar, Hz), `Ni` teeth on input gear, `No` teeth on output gear (both positive integers). **`Ni` and `No` are separate scalars, not a vector.** `FB` - Network accessline 51
- Docs: <https://www.mathworks.com/help/predmaint/ref/gearmeshfaultbands.html> - Network accessline 53
- **`faultBands`** (Predictive Maintenance Toolbox, R2019b) — generic fault frequency bands from a fundamental and its sidebands. - `[FB,info] = faultBands(F0,N0)` — `F0` fundamental frequency, `N0` harmonics; add sideband spacing/orders - Network accessline 55
- Docs: <https://www.mathworks.com/help/predmaint/ref/faultbands.html> - Network accessline 60
- `spectralMetrics = faultBandMetrics(psd,freqGrid,FB)` — `psd` power spectral density (vector/array), `freqGrid` matching frequency vector, `FB` the Nx2 fault-band array from `gearMeshFaultBands`/`faultBands`. **Three positional inputs; do - Network accessline 62
- Docs: <https://www.mathworks.com/help/predmaint/ref/faultbandmetrics.html> - Network accessline 69
- To feed the difference/regular/residual signals too, put each in its own **timetable variable** and name them: `gearConditionMetrics(TT,sigVar,diffVar,regVar,resVar)` where `TT` is a multi-variable timetable. **Pass `''` (empty char), not - Network accessline 71
- Docs: <https://www.mathworks.com/help/predmaint/ref/gearconditionmetrics.html> - Network accessline 73
### Additional References - When applicable, fetch [Condition Indicators for Gear Condition Monitoring](https://www.mathworks.com/help/predmaint/ug/condition-indicators-for-gear-condition-monitoring.html) - Network accessline 74
- When applicable, fetch [Condition Indicators for Gear Condition Monitoring](https://www.mathworks.com/help/predmaint/ug/condition-indicators-for-gear-condition-monitoring.html)
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/references/spectral.md
- Network accessline 35
- `[es,f,env,t] = envspectrum(x,fs)` — pass a timetable `xt` in place of `(x,fs)`; returns envelope spectrum, frequency vector, envelope signal, and time vector. - Name-value: `Method` (`"demod"` default | `"hilbert"`), `Band` (two-elemen - Network accessline 37
- Docs: <https://www.mathworks.com/help/signal/ref/envspectrum.html> - Network accessline 39
- **`envelope`** (Signal Processing Toolbox, R2015b) — signal envelope. - `[yupper,ylower] = envelope(x)`; other methods: `envelope(x,fl,'analytic')` / `envelope(x,wl,'rms')` / `envelope(x,np,'peak')`. - Docs: <https://www.mathworks.com - Network accessline 41
- Docs: <https://www.mathworks.com/help/signal/ref/envelope.html> - Network accessline 44
- `[y,d] = bandpass(x,fpass,fs)` — `fpass` is a two-element `[low high]` band in Hz (elements in `(0, fs/2)`); pass a timetable `xt` in place of `(x,fs)`. `d` is the `digitalFilter` object. - Name-value: `ImpulseResponse` (`"auto"` defaul - Network accessline 46
- Docs: <https://www.mathworks.com/help/signal/ref/bandpass.html> - Network accessline 48
- **`kurtogram`** (Signal Processing Toolbox, R2018a) — fast kurtogram to select a bandpass band. - `[kgram,f,w,fc,wc,bw] = kurtogram(x,sampx)` — `sampx` is sample rate or sample time (or pass a timetable `xt`); `fc` is the center frequen - Network accessline 50
- Docs: <https://www.mathworks.com/help/signal/ref/kurtogram.html> - Network accessline 52
- **`spectralKurtosis`** (Signal Processing Toolbox, R2019a) — spectral kurtosis of a signal. - `kurtosis = spectralKurtosis(x,f)` — `f` is the sample rate/time or frequency vector (or pass a timetable `xt`). - Docs: <https://www.mathwo - Network accessline 54
- Docs: <https://www.mathworks.com/help/signal/ref/spectralkurtosis.html> - Network accessline 56
- **`bandpower`** (Signal Processing Toolbox, R2013a) — average band power. - `p = bandpower(x,Fs,freqRange)` from a time series (`freqRange` a two-element `[low high]` vector or M-by-2 matrix), or `p = bandpower(pxx,f,freqRange,"psd")` f - Network accessline 58
- Docs: <https://www.mathworks.com/help/signal/ref/bandpower.html> - Network accessline 63
- `spectralMetrics = faultBandMetrics(psd,freqGrid,FB)` — `psd` power spectral density, `freqGrid` matching frequency vector, `FB` the Nx2 fault-band array from `bearingFaultBands`/`gearMeshFaultBands`/`faultBands`. **Three positional input - Network accessline 65
- Docs: <https://www.mathworks.com/help/predmaint/ref/faultbandmetrics.html>
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/references/tsa.md
- Network accessline 37
- Name-value: `PulsesPerRev` (default 1) — note the spelling (`PulsesPerRev`, not `PulsesPerRevolution`), `StateLevels`, `OutputFs`, `FitType`. - **Do not call this on a vector of pulse times** — it will report "no pulses detected". Pulse - Network accessline 39
- Docs: <https://www.mathworks.com/help/signal/ref/tachorpm.html> - Network accessline 43
- `[ta,t,p,rpm] = tsa(___)` also returns sample times, phase, and the constant rotational speed. - Name-value: `Method` (`"linear"`|`"spline"`|`"pchip"`|`"fft"`), `NumRotations`, `PulsesPerRotation`, `ResampleFactor`. - Docs: <https://w - Network accessline 45
- Docs: <https://www.mathworks.com/help/signal/ref/tsa.html> - Network accessline 49
- `[Y,S] = tsaresidual(___)` also returns the amplitude spectrum. - Name-value: `NumHarmonics` (default 2), `NumRotations`, `Domain` (`'order'` default | `'frequency'`). - Docs: <https://www.mathworks.com/help/predmaint/ref/tsaresidual. - Network accessline 51
- Docs: <https://www.mathworks.com/help/predmaint/ref/tsaresidual.html> - Network accessline 54
- `Y = tsadifference(X,fs,rpm,orderList)` — same argument pattern as `tsaresidual` (timetable form: `tsadifference(XT,rpm,orderList)`); `[Y,S] = tsadifference(___)` also returns the amplitude spectrum. - Name-value: `NumHarmonics`, `NumSi - Network accessline 56
- Docs: <https://www.mathworks.com/help/predmaint/ref/tsadifference.html> - Network accessline 59
- `Y = tsaregular(X,fs,rpm,orderList)` — same argument pattern (timetable form: `tsaregular(XT,rpm,orderList)`); here `orderList` is the orders to *retain*. `[Y,S] = tsaregular(___)` also returns the amplitude spectrum. - Name-value: `Num - Network accessline 61
- Docs: <https://www.mathworks.com/help/predmaint/ref/tsaregular.html> - Network accessline 63
### Reference Examples - [Vibration Analysis of Rotating Machinery](https://www.mathworks.com/help/signal/ug/vibration-analysis-of-rotating-machinery.html) - Network accessline 64
- [Vibration Analysis of Rotating Machinery](https://www.mathworks.com/help/signal/ug/vibration-analysis-of-rotating-machinery.html)
skills-catalog/control-systems/matlab-extract-rotating-machinery-features/references/vibration.md
- Network accessline 33
- Name-value: `Type` (`"acceleration"` default | `"velocity"` | `"displacement"`), `Fmin` (default `Fs/500`), `Fmax` (default `Fs/5`). - **Available from R2024a** — for earlier releases, condition the signal manually. - Docs: <https://w - Network accessline 35
- Docs: <https://www.mathworks.com/help/signal/ref/convertVibration.html> - Network accessline 37
### Reference Examples - [Vibration Analysis of Rotating Machinery](https://www.mathworks.com/help/signal/ug/vibration-analysis-of-rotating-machinery.html) - Network accessline 38
- [Vibration Analysis of Rotating Machinery](https://www.mathworks.com/help/signal/ug/vibration-analysis-of-rotating-machinery.html)
skills-catalog/control-systems/matlab-identify-linear-system/SKILL.md
- Network accessline 3
description: > Identify a linear dynamic model from input-output or time-series data using MATLAB System Identification Toolbox. Use when estimating transfer function, state-space, ARX, ARMAX, BJ, OE polynomial or process models from meas - Network accessline 4
Identify a linear dynamic model from input-output or time-series data using MATLAB System Identification Toolbox. Use when estimating transfer function, state-space, ARX, ARMAX, BJ, OE polynomial or process models from measurement data. lic - Network accessline 5
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-identify-linear-system/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/control-systems/matlab-identify-linear-system/references/estimation.md
skills-catalog/control-systems/matlab-identify-linear-system/references/special-topics.md
skills-catalog/image-processing-and-computer-vision/matlab-analyze-spectral-images/SKILL.md
- Network accessline 10
Use when reading, writing, processing, analyzing, classifying, labeling, or applying deep learning to hyperspectral or multispectral images. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
deep learning to hyperspectral or multispectral images. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-analyze-spectral-images/manifest.yaml
skills-catalog/image-processing-and-computer-vision/matlab-display-image/SKILL.md
- Network accessline 2
name: matlab-display-image description: Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest - Network accessline 3
description: Display images and annotations for image processing, computer vision, and visual inspection. Use when displaying images with imageshow, creating image viewers with viewer2d, adding Regions of Interest (ROI) or annotations, over - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-display-image/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-display-volume/SKILL.md
- Network accessline 2
name: matlab-display-volume description: Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with vi - Network accessline 3
description: Display 3-D image volumes, medical image volumes, surface meshes, and annotations for 3-D image processing. Use when displaying 3-D images or isosurfaces with volshow, creating volume viewers with viewer3d, adding Regions of In - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-display-volume/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/SKILL.md
- Network accessline 10
Do NOT use for general-purpose Python-MATLAB interfacing, non-vision models (NLP, tabular, audio), model deployment/serving, or MATLAB-only image processing workflows. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/ - Network accessline 11
tabular, audio), model deployment/serving, or MATLAB-only image processing workflows. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 43
1. **Download MPyReq** from the MATLAB File Exchange: https://mathworks.com/matlabcentral/fileexchange/182230-matlab-based-python-requirements-manager - Network accessline 44
https://mathworks.com/matlabcentral/fileexchange/182230-matlab-based-python-requirements-manager - Network accessline 105
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.12"); MPyReq.pipPackage("git+https://github.com/<org>/<repo>.git", Name="<RepoName>"); - Network accessline 107
MPyReq.pipPackage("git+https://github.com/<org>/<repo>.git", Name="<RepoName>"); - Network accessline 113
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.11"); MPyReq.gitrepo("https://github.com/<org>/<repo>.git"); - Network accessline 114
MPyReq.python("3.11"); MPyReq.gitrepo("https://github.com/<org>/<repo>.git"); reqTxt = MPyReq.pathTo("<repo>") + filesep + "requirements.txt"; - Network accessline 115
MPyReq.gitrepo("https://github.com/<org>/<repo>.git");
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/references/demo-birefnet.md
- Network accessline 9
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.11"); MPyReq.gitrepo("https://github.com/ZhengPeng7/BiRefNet.git"); - Network accessline 10
MPyReq.python("3.11"); MPyReq.gitrepo("https://github.com/ZhengPeng7/BiRefNet.git"); recTxt = MPyReq.pathTo("BiRefNet") + filesep + "requirements.txt"; - Network accessline 11
MPyReq.gitrepo("https://github.com/ZhengPeng7/BiRefNet.git"); - Network accessline 12
recTxt = MPyReq.pathTo("BiRefNet") + filesep + "requirements.txt"; MPyReq.requirementTextFile(recTxt, Name="BiRefNetPackages"); MPyReq.weights("https://github.com/ZhengPeng7/BiRefNet/releases/download/v1/BiRefNet-general-bb_swin_v1_tiny-epo - Network accessline 14
MPyReq.weights("https://github.com/ZhengPeng7/BiRefNet/releases/download/v1/BiRefNet-general-bb_swin_v1_tiny-epoch_232.pth");
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/references/demo-depthpro.md
- Network accessline 11
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.9"); MPyReq.gitrepo("https://github.com/apple/ml-depth-pro", Name="DepthPro"); - Network accessline 12
MPyReq.python("3.9"); MPyReq.gitrepo("https://github.com/apple/ml-depth-pro", Name="DepthPro"); MPyReq.pipPackage("git+https://github.com/apple/ml-depth-pro", Name="DepthProPackages"); - Network accessline 13
MPyReq.gitrepo("https://github.com/apple/ml-depth-pro", Name="DepthPro"); - Network accessline 14
MPyReq.pipPackage("git+https://github.com/apple/ml-depth-pro", Name="DepthProPackages"); - Network accessline 15
MPyReq.weights("https://ml-site.cdn-apple.com/models/depth-pro/depth_pro.pt", ...
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/references/demo-sam2.md
- Network accessline 11
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.12"); MPyReq.pipPackage("git+https://github.com/facebookresearch/sam2.git", ... - Network accessline 12
MPyReq.python("3.12"); MPyReq.pipPackage("git+https://github.com/facebookresearch/sam2.git", ... Name="SAM2"); - Network accessline 13
MPyReq.pipPackage("git+https://github.com/facebookresearch/sam2.git", ... - Network accessline 14
Name="SAM2"); MPyReq.weights("https://dl.fbaipublicfiles.com/segment_anything_2/092824/" + ... "sam2.1_hiera_tiny.pt", ... - Network accessline 15
MPyReq.weights("https://dl.fbaipublicfiles.com/segment_anything_2/092824/" + ...
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/references/demo-stardist.md
skills-catalog/image-processing-and-computer-vision/matlab-integrate-pytorch-vision/references/demo-vggt.md
- Network accessline 11
MPyReq.autoAcceptDownloadPrompts(true); MPyReq.python("3.12"); MPyReq.gitrepo("https://github.com/facebookresearch/vggt.git"); - Network accessline 12
MPyReq.python("3.12"); MPyReq.gitrepo("https://github.com/facebookresearch/vggt.git"); reqTxt = MPyReq.pathTo("vggt") + filesep + "requirements.txt"; - Network accessline 13
MPyReq.gitrepo("https://github.com/facebookresearch/vggt.git");
skills-catalog/image-processing-and-computer-vision/matlab-model-optics/SKILL.md
- Network accessline 4
Build, import, analyze, tolerate, and optimize optical systems using the Optical Design and Simulation Library. Use when the user asks about optical systems, ray tracing, geometric optics, Zemax import, optical coatings, tolerancing, or o - Network accessline 5
Use when the user asks about optical systems, ray tracing, geometric optics, Zemax import, optical coatings, tolerancing, or optical design optimization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metad - Network accessline 6
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-model-optics/manifest.yaml
skills-catalog/image-processing-and-computer-vision/matlab-process-images/SKILL.md
- Network accessline 16
generation or GPU deployment of a network, or point clouds. Hyperspectral and visual inspection have sibling skills. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 17
and visual inspection have sibling skills. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 18
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-process-images/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-read-write-point-cloud-file/SKILL.md
- Network accessline 2
name: matlab-read-write-point-cloud-file description: "Read and write 3-D point cloud data using Lidar Toolbox file I/O. Covers PLY, PCD, LAS/LAZ, PCAP (Velodyne/Ouster/Hesai), E57, and IDC (Ibeo) formats. Use when loading point clouds from - Network accessline 3
description: "Read and write 3-D point cloud data using Lidar Toolbox file I/O. Covers PLY, PCD, LAS/LAZ, PCAP (Velodyne/Ouster/Hesai), E57, and IDC (Ibeo) formats. Use when loading point clouds from disk, saving to disk, choosing the corre - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-read-write-point-cloud-file/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-recognize-text/SKILL.md
- Network accessline 9
extract text from image, character recognition, document scanning, meter reading, gauge reading, receipt scanning, digitize text from photo. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
gauge reading, receipt scanning, digitize text from photo. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-recognize-text/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-register-point-clouds/SKILL.md
- Network accessline 2
name: matlab-register-point-clouds description: Register 3-D point clouds using ICP, NDT, LOAM, FGR, phase correlation, and CPD algorithms. Use when registering or aligning 3-D point clouds, choosing a registration algorithm, tuning registr - Network accessline 3
description: Register 3-D point clouds using ICP, NDT, LOAM, FGR, phase correlation, and CPD algorithms. Use when registering or aligning 3-D point clouds, choosing a registration algorithm, tuning registration parameters, preprocessing poi - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-register-point-clouds/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/image-processing-and-computer-vision/matlab-use-visual-inspection/SKILL.md
- Network accessline 12
deterministic, AI-based tools when defect appearance varies, and hybrid pipelines combining both. license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" - Network accessline 13
combining both. license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" metadata: - Network accessline 14
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/image-processing-and-computer-vision/matlab-use-visual-inspection/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" - Network accessline 2
schema-version: 1 license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" scope: cross-product - Network accessline 3
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/math-and-optimization/matlab-solve-optimization/SKILL.md
- Network accessline 8
violations). Covers problem-based and solver-based approaches, solver tuning, and solution verification. license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" - Network accessline 9
and solution verification. license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" metadata: - Network accessline 10
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/math-and-optimization/matlab-solve-optimization/manifest.yaml
skills-catalog/math-and-optimization/matlab-solve-optimization/references/improving-results.md
- Network accessline 5
Doc reference: https://www.mathworks.com/help/optim/improving-results.html
skills-catalog/math-and-optimization/matlab-solve-optimization/references/problem-based-guide.md
skills-catalog/math-and-optimization/matlab-solve-optimization/references/solver-tuning.md
- Network accessline 181
Doc references: - https://www.mathworks.com/help/gads/specify-multistart-start-points-problem.html - Network accessline 182
- https://www.mathworks.com/help/gads/specify-multistart-start-points-problem.html - Network accessline 183
- https://www.mathworks.com/help/gads/multiple-local-solutions-problem.html - Network accessline 200
Doc reference: https://www.mathworks.com/help/gads/multiobjective-optimization-problem-based.html
skills-catalog/math-and-optimization/matlab-solve-optimization/references/validation-checklist.md
- Network accessline 5
Doc reference: https://www.mathworks.com/help/optim/solver-outputs-and-iterative-display.html
skills-catalog/math-and-optimization/matlab-solve-pde/SKILL.md
- Network accessline 15
analysis, electromagnetic analysis, femodel, mesh, boundary conditions, stress, displacement, heat transfer, post-processing. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 16
displacement, heat transfer, post-processing. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 17
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Dangerous shell operationline 368
Rm = solve(model, FrequencyRange=[-Inf, 2*pi*500]); % Modal superposition...
skills-catalog/math-and-optimization/matlab-solve-pde/manifest.yaml
skills-catalog/math-and-optimization/matlab-solve-pde/references/damping-reference.md
- Dangerous shell operationline 29
Rm = solve(model, FrequencyRange=[-Inf, 2*pi*500]);
skills-catalog/math-and-optimization/matlab-use-symbolic-math/SKILL.md
- Network accessline 9
symbolic matrix variables (symmatrix), physical units and constants (symunit, newUnit), or rewriting/combining algebraic expressions (rewrite, combine). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
or rewriting/combining algebraic expressions (rewrite, combine). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 226
% Gradient, Hessian, Jacobian, Laplacian, Divergence, Curl — use dedicated functions, not manual diff - Network accessline 291
| Hard-coding physical constants as numbers | Use `u = symunit; u.hc; u.c_0; u.m_e` | | Using `combine(expr, 'power')` | Invalid target — valid: `'atan'`, `'exp'`, `'gamma'`, `'int'`, `'log'`, `'sincos'`, `'sinhcosh'` | | Computing gradient - Network accessline 292
| Using `combine(expr, 'power')` | Invalid target — valid: `'atan'`, `'exp'`, `'gamma'`, `'int'`, `'log'`, `'sincos'`, `'sinhcosh'` | | Computing gradient/Hessian/Jacobian/Laplacian/divergence/curl manually with `diff` | Use `gradient`, `he - Network accessline 293
| Computing gradient/Hessian/Jacobian/Laplacian/divergence/curl manually with `diff` | Use `gradient`, `hessian`, `jacobian`, `laplacian`, `divergence`, `curl` |
skills-catalog/math-and-optimization/matlab-use-symbolic-math/manifest.yaml
skills-catalog/matlab-app-building/matlab-apply-theme/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 1
--- name: matlab-apply-theme license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
name: matlab-apply-theme license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-apply-theme/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-apply-theme schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-apply-theme/references/component-colors.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-apply-theme/references/external-schemes.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-apply-theme/references/theme-api.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-app/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 1
--- name: matlab-build-app license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
name: matlab-build-app license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-build-app/assets/standalone-chart-template.html
- Network accessline 8
For uihtml (UIHTML app): 1. Download chart.js locally: https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js - Network accessline 9
1. Download chart.js locally: https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js - Network accessline 10
2. Place it in ./lib/chart.umd.min.js (same folder as your HTML) 3. Replace the <script src="https://cdn..."> below with <script src="./lib/chart.umd.min.js"> 4. Add setup(htmlComponent) and wire DataChanged → renderCharts(data) - Network accessline 11
3. Replace the <script src="https://cdn..."> below with <script src="./lib/chart.umd.min.js"> - Network accessline 18
<meta name="viewport" content="width=device-width, initial-scale=1.0"> <title>Chart Template</title> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script> - Network accessline 19
<title>Chart Template</title> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script> <style> - Network accessline 20
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script>
skills-catalog/matlab-app-building/matlab-build-app/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-build-app schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-build-app/references/app-designer/plaintext/matlabAppSchema.xsd
skills-catalog/matlab-app-building/matlab-build-app/references/timers.md
- Network accessline 34
% Timer callback — keep it cheap; it runs on the UI thread: function onTick(app, ~, ~) data = webread("https://example.com/latest.json"); % quick read - Network accessline 35
function onTick(app, ~, ~) data = webread("https://example.com/latest.json"); % quick read plot(app.UIAxes, data.time, data.value, "ob"); % direct UI update - Network accessline 36
data = webread("https://example.com/latest.json"); % quick read
skills-catalog/matlab-app-building/matlab-build-app/references/uihtml/chart-bridge-integration.md
- Network accessline 24
Download once: `https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js`
skills-catalog/matlab-app-building/matlab-build-app/references/uihtml/charting-guide.md
- Network accessline 25
<head> <meta charset="UTF-8"> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script> - Network accessline 26
<meta charset="UTF-8"> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script> <style> - Network accessline 27
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js"></script>
skills-catalog/matlab-app-building/matlab-build-app/references/uihtml/chartjs-setup.md
- Network accessline 10
<!-- Chart.js UMD bundle — provides global `Chart` --> <script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js" - Network accessline 11
<script src="https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js" - Network accessline 15
<!-- Date adapter — add ONLY if using a time scale axis --> <script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns@3.0.0/dist/chartjs-adapter-date-fns.bundle.min.js" - Network accessline 16
<script src="https://cdn.jsdelivr.net/npm/chartjs-adapter-date-fns@3.0.0/dist/chartjs-adapter-date-fns.bundle.min.js" - Network accessline 27
Download URL (for user to fetch manually or via curl): `https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js` - Network accessline 28
`https://cdn.jsdelivr.net/npm/chart.js@4.5.1/dist/chart.umd.min.js`
skills-catalog/matlab-app-building/matlab-build-app/references/uihtml/platform-limitations.md
- Network accessline 42
# Example: download any minified JS library curl -sL "https://example.com/library/dist/library.min.js" -o "libs/library.min.js" - Network accessline 43
curl -sL "https://example.com/library/dist/library.min.js" -o "libs/library.min.js" - Network accessline 53
<!-- This will NOT work in uihtml --> <script src="https://cdn.example.com/library.min.js"></script> - Network accessline 54
<script src="https://cdn.example.com/library.min.js"></script>
skills-catalog/matlab-app-building/matlab-build-chart/SKILL.md
- Broad permissionsline 1
Bash - Network accessline 1
--- name: matlab-build-chart license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
name: matlab-build-chart license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-build-chart/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-build-chart schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-app-building/matlab-build-chart/references/animation.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/annotations.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/axes-config.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/chart-palettes.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/data-tips.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/interactive-plots.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/multiple-axes.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/performance.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-app-building/matlab-build-chart/references/plot-types.md
- Executable scriptline 1
Executable file
skills-catalog/matlab-core/matlab-create-live-script/SKILL.md
- Network accessline 2
name: matlab-create-live-script description: Create, edit, and run plain-text MATLAB live scripts (.m files) with rich text formatting, LaTeX equations, section breaks, and inline figures. Use when generating tutorials, analysis notebooks, - Network accessline 3
description: Create, edit, and run plain-text MATLAB live scripts (.m files) with rich text formatting, LaTeX equations, section breaks, and inline figures. Use when generating tutorials, analysis notebooks, reports, documentation, or educa - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-create-live-script/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for creating-live-scripts schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-debug-code/SKILL.md
- Network accessline 2
name: matlab-debug-code description: Diagnose MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or - Network accessline 3
description: Diagnose MATLAB errors and unexpected behavior. Breakpoints, workspace inspection, try-catch diagnostics, and common error patterns. Use when debugging functions, tracing errors, inspecting variables, or diagnosing runtime fail - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-debug-code/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for debugging schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-install-products/SKILL.md
- Network accessline 2
name: matlab-install-products description: "Deterministic workflow to download MATLAB Package Manager (mpm) and install MathWorks products from the OS command line with consistent, repeatable behavior. Use when installing MATLAB, Simulink, - Network accessline 3
description: "Deterministic workflow to download MATLAB Package Manager (mpm) and install MathWorks products from the OS command line with consistent, repeatable behavior. Use when installing MATLAB, Simulink, toolboxes, or support packages - Network accessline 4
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" - Dangerous shell operationline 57
The only Bash tool commands allowed in this protocol are: `mkdir -p` (create the working folder), `powershell.exe ... -File` (invoke a script), `test -f` (verify artifacts), and `rm -rf` (cleanup). Any Bash command that would create or writ - Network accessline 71
Do not ask the user for the exact product name or identifier. Look it up using the appropriate mpm input file from https://www.mathworks.com/products/mpm.html - Network accessline 121
<if support packages requested> Verify support packages via: <SUPPORTPKGROOT>/appdata/prodcontents.json Delete working folder: <working folder> <if MATLAB included> Show release notes: https://www.mathworks.com/help/matlab/release-notes - Network accessline 123
<if MATLAB included> Show release notes: https://www.mathworks.com/help/matlab/release-notes.html?startrelease=<RELEASE>&endrelease=<RELEASE> - Network accessline 129
Official documentation: - Get mpm: https://www.mathworks.com/help/install/ug/get-mpm-os-command-line.html - Network accessline 130
- Get mpm: https://www.mathworks.com/help/install/ug/get-mpm-os-command-line.html - Network accessline 131
- mpm install: https://www.mathworks.com/help/install/ug/mpminstall.html - Network accessline 161
If the file exists at that path, reuse it. Otherwise download from: - Windows: https://www.mathworks.com/mpm/win64/mpm - Network accessline 162
- Windows: https://www.mathworks.com/mpm/win64/mpm - Network accessline 163
- Linux: https://www.mathworks.com/mpm/glnxa64/mpm - Network accessline 164
- macOS: https://www.mathworks.com/mpm/maca64/mpm - Network accessline 184
Write-Host "mpm already present at $Destination" } else { Write-Host "Downloading mpm from https://www.mathworks.com/mpm/win64/mpm - this may take a few minutes..." - Network accessline 185
} else { Write-Host "Downloading mpm from https://www.mathworks.com/mpm/win64/mpm - this may take a few minutes..." Invoke-WebRequest -Uri "https://www.mathworks.com/mpm/win64/mpm" -OutFile $Destination -UseBasicParsing - Network accessline 186
Write-Host "Downloading mpm from https://www.mathworks.com/mpm/win64/mpm - this may take a few minutes..." Invoke-WebRequest -Uri "https://www.mathworks.com/mpm/win64/mpm" -OutFile $Destination -UseBasicParsing if (-not (Test-Path -Lite - Network accessline 187
Invoke-WebRequest -Uri "https://www.mathworks.com/mpm/win64/mpm" -OutFile $Destination -UseBasicParsing if (-not (Test-Path -LiteralPath $Destination)) { throw "mpm download failed: $Destination" } Write-Host "mpm downloaded to $Destina - Network accessline 201
See `reference/linux-macos-steps.md` for full shell scripts. Summary: create working folder at `/tmp/mpm-YYYYMMDD-HHMMSS`, download mpm with `curl -fL -o` to `~/Downloads/mpm`, and `chmod +x`. - Network accessline 205
Always use a release template input file from: https://www.mathworks.com/products/mpm.html - Network accessline 206
https://www.mathworks.com/products/mpm.html - Network accessline 264
$releaseLower = $Release.ToLower() $inputUrl = "https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/products/mpm/mpm-input-${releaseLower}.txt" - Network accessline 265
$inputUrl = "https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/products/mpm/mpm-input-${releaseLower}.txt" - Dangerous shell operationline 418
rm -rf "C:/Users/<username>/AppData/Local/Temp/mpm-YYYYMMDD-HHMMSS" - Network accessline 426
https://www.mathworks.com/help/matlab/release-notes.html?startrelease=<RELEASE>&endrelease=<RELEASE>&rntext=&groupby=release&sortby=descending&searchHighlight= - Network accessline 431
> View the MATLAB R2025b Release Notes by visiting this link: > https://www.mathworks.com/help/matlab/release-notes.html?startrelease=R2025b&endrelease=R2025b&rntext=&groupby=release&sortby=descending&searchHighlight= - Network accessline 432
> https://www.mathworks.com/help/matlab/release-notes.html?startrelease=R2025b&endrelease=R2025b&rntext=&groupby=release&sortby=descending&searchHighlight= - Network accessline 450
| `Start-Process -Verb RunAs -Wait` | Elevated execution on Windows (UAC) | | `Invoke-WebRequest -OutFile` | Download files in PowerShell | | `curl -fL -o` | Download files on Linux/macOS | - Network accessline 452
| `curl -fL -o` | Download files on Linux/macOS | - Network accessline 456
- Licensing and activation are separate workflows. Do not ask the user about licensing or activation at the end of the install. - Always use a release input file from: https://www.mathworks.com/products/mpm.html - Network accessline 458
https://www.mathworks.com/products/mpm.html
skills-catalog/matlab-core/matlab-install-products/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-install-products/reference/linux-macos-steps.md
- Network accessline 5
Create the working folder with `mkdir -p /tmp/mpm-YYYYMMDD-HHMMSS`, then print a progress message (`echo "Downloading mpm - this may take a few minutes..."`), use `curl -fL -o` to download mpm to `<user home>/Downloads/mpm`, and `chmod +x` - Network accessline 15
else echo "Downloading mpm - this may take a few minutes..." curl -fL -o "$mpm_path" "https://www.mathworks.com/mpm/glnxa64/mpm" # Linux - Network accessline 16
echo "Downloading mpm - this may take a few minutes..." curl -fL -o "$mpm_path" "https://www.mathworks.com/mpm/glnxa64/mpm" # Linux # macOS: curl -fL -o "$mpm_path" "https://www.mathworks.com/mpm/maca64/mpm" - Network accessline 17
curl -fL -o "$mpm_path" "https://www.mathworks.com/mpm/glnxa64/mpm" # Linux - Network accessline 18
# macOS: curl -fL -o "$mpm_path" "https://www.mathworks.com/mpm/maca64/mpm" - Network accessline 28
release="R2025b" working_folder="/tmp/mpm-YYYYMMDD-HHMMSS" input_url="https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/products/mpm/mpm-input-${release,,}.txt" - Network accessline 29
working_folder="/tmp/mpm-YYYYMMDD-HHMMSS" input_url="https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/products/mpm/mpm-input-${release,,}.txt" input_file="${working_folder}/mpm_input_${release,,}.txt" - Network accessline 30
input_url="https://www.mathworks.com/content/dam/mathworks/mathworks-dot-com/products/mpm/mpm-input-${release,,}.txt" - Network accessline 33
curl -fL -o "$input_file" "$input_url"
skills-catalog/matlab-core/matlab-list-products/SKILL.md
- Network accessline 2
name: matlab-list-products description: "Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation - Network accessline 3
description: "Show all installed MATLAB products and support packages for a given MATLAB installation folder. Use when listing, checking, or verifying what products or support packages are in a MATLAB installation." license: "https://www.ma - Network accessline 4
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/matlab-core/matlab-list-products/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-read-documentation/SKILL.md
- Network accessline 3
keywords: docs documentation mathworks webread fetch lookup api reference function description: "Guides the agent to reference official MathWorks Documentation and Help. Determine correct function syntax and workflows from user guides when - Network accessline 4
description: "Guides the agent to reference official MathWorks Documentation and Help. Determine correct function syntax and workflows from user guides when deeper context is needed. Minimize iterations and repetitive trial and error. Use - Network accessline 5
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 36
| Task | Fast Path | Skip | | ------------------------------- - Network accessline 37
| ------------------------------------ | ------------------------------------------------------------------------------------------------------------------------------ | ---------------------------------- | | Release notes / what's new - Network accessline 38
| Release notes / what's new | Fetch `https://www.mathworks.com/help/{product}/release-notes.md` directly via `webread`, then extract the `## R20XXx` section | Steps 0-2 — no script needed | - Network accessline 45
Release notes are available as clean markdown at `https://www.mathworks.com/help/{product}/release-notes.md`. Fetch this URL with `webread`, then extract the section between `## R20XXx` and the next `## R` header. No HTML parsing needed. Co - Network accessline 115
`baseUrl` already includes the product path (e.g., `https://www.mathworks.com/help/releases/R2026a/autosar/`). Append only the sub-path: `baseUrl + "ref/name.html"` or `baseUrl + "ug/topic.html"`. Never re-add the product name. - Network accessline 119
| Page type | Pattern | Example | | --------------- | ------------------------------------------- | --------------------------- - Network accessline 120
| --------------- | ------------------------------------------- | ------------------------------------------------------------------------------ | | Product index | `{base}/{product}/index.html` | `https://www.mathworks.com/ - Network accessline 121
| Product index | `{base}/{product}/index.html` | `https://www.mathworks.com/help/releases/R2025b/simulink/index.html` | - Network accessline 122
| Section index | `{base}/{product}/{section-slug}.html` | `https://www.mathworks.com/help/releases/R2025b/simulink/block-libraries.html` | - Network accessline 123
| User guide page | `{base}/{product}/ug/{page-slug}.html` | `https://www.mathworks.com/help/releases/R2025b/simulink/ug/some-topic.html` | - Network accessline 124
| Reference page | `{base}/{product}/ref/{function-name}.html` | `https://www.mathworks.com/help/releases/R2025b/matlab/ref/plot.html` |
skills-catalog/matlab-core/matlab-read-documentation/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-review-code/SKILL.md
- Network accessline 2
name: matlab-review-code description: Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, f - Network accessline 3
description: Review MATLAB code for quality, performance, maintainability, and adherence to MathWorks coding standards. Uses check_matlab_code and matlab_coding_guidelines. Use when reviewing code, checking style, finding code smells, asses - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-core/matlab-review-code/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for reviewing-code schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-data-import-and-analysis/matlab-analyze-data/SKILL.md
- Network accessline 2
name: matlab-analyze-data description: Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, row filtering, sor - Network accessline 3
description: Analyze data using MATLAB. Use when the task involves tables, timetables, time-series data, numeric arrays, sensor matrices, or gridded data — including but not limited to exploring, row filtering, sorting, cleaning, transformi - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-data-import-and-analysis/matlab-analyze-data/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-data-import-and-analysis/matlab-analyze-data/references/tables-and-timetables.md
skills-catalog/matlab-data-import-and-analysis/matlab-choose-big-data-solution/SKILL.md
- Network accessline 14
extensible datastore, or integrating a new file format with tall arrays or parallel computing. Do NOT use for MAT files (use matfile instead). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
parallel computing. Do NOT use for MAT files (use matfile instead). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 159
conn = duckdb(); result = fetch(conn, "SELECT * FROM read_csv_auto('large.csv') WHERE Region = 'West'"); - Network accessline 160
result = fetch(conn, "SELECT * FROM read_csv_auto('large.csv') WHERE Region = 'West'");
skills-catalog/matlab-data-import-and-analysis/matlab-choose-big-data-solution/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-data-import-and-analysis/matlab-choose-big-data-solution/references/custom-datastore/testing-guidelines.md
- Network accessline 6
Reference: https://www.mathworks.com/help/matlab/import_export/testing-guidelines-for-custom-datastores.html
skills-catalog/matlab-data-import-and-analysis/matlab-import-export-data/SKILL.md
- Network accessline 9
and modernizing legacy file I/O code. MATLAB provides built-in functions for these workflows with no additional products required. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
for these workflows with no additional products required. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 163
T = readtable("https://example.com/api/v2/export/measurements", "FileType", "text");
skills-catalog/matlab-data-import-and-analysis/matlab-import-export-data/manifest.yaml
skills-catalog/matlab-data-import-and-analysis/matlab-secure-credentials/SKILL.md
- Network accessline 10
Does NOT cover third-party secret managers (HashiCorp Vault, AWS Secrets Manager), OS-level key management, or the connection/query logic itself. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
OS-level key management, or the connection/query logic itself. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 132
HeaderFields = ["Authorization", "Bearer " + token], ... ContentType = "json"); data = webread("https://api.example.com/v1/data", opts); - Network accessline 134
data = webread("https://api.example.com/v1/data", opts); - Network accessline 141
[Credential-related source omitted] - Network accessline 143
data = webread("https://api.example.com/v1/data", opts); - Network accessline 218
config = struct( ... "BaseUrl", "https://api.example.com/v1", ... - Network accessline 219
"BaseUrl", "https://api.example.com/v1", ... - Access to secretsline 251
[Credential-related source omitted]
skills-catalog/matlab-data-import-and-analysis/matlab-secure-credentials/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-external-language-interfaces/matlab-call-python/SKILL.md
- Network accessline 9
setting up Python environments for MATLAB, creating virtual environments, or installing Python packages for use with MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
environments, or installing Python packages for use with MATLAB. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-external-language-interfaces/matlab-call-python/manifest.yaml
skills-catalog/matlab-external-language-interfaces/matlab-upgrade-mex-ic/SKILL.md
- Network accessline 12
Fortran MEX, .F MEX file, C++ MEX, .cpp MEX file, MEX performance, MEX slow complex, MEX call overhead, improve MEX performance complex. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
MEX slow complex, MEX call overhead, improve MEX performance complex. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-external-language-interfaces/matlab-upgrade-mex-ic/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-programming/matlab-validate-function-arguments/SKILL.md
- Network accessline 16
Designer callbacks, Simulink mask parameters, class inheritance, or runtime validation outside function or property declarations. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 17
validation outside function or property declarations. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 18
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-programming/matlab-validate-function-arguments/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-configure-toml-project/SKILL.md
- Network accessline 6
declaring MATLAB package dependencies or reference projects, setting up paths, lifecycle scripts, shortcuts, MATLAB packages, or asking about project structure. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license - Network accessline 7
lifecycle scripts, shortcuts, MATLAB packages, or asking about project structure. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 8
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-configure-toml-project/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-configure-toml-project/references/format-reference.md
- Network accessline 356
id = "4919a5e0-b81e-43dc-a238-ea92bcbd4d39" package-root = "toolbox" provider = {name = "Jane Doe", organization = "Acme Corp", email = "jane@acme.com", url = "https://acme.com"} - Network accessline 358
provider = {name = "Jane Doe", organization = "Acme Corp", email = "jane@acme.com", url = "https://acme.com"} - Network accessline 377
name = "Python" platform = "linux" download-url = "https://www.python.org/downloads/" - Network accessline 378
platform = "linux" download-url = "https://www.python.org/downloads/" license-url = "https://docs.python.org/3/license.html" - Network accessline 379
download-url = "https://www.python.org/downloads/" - Network accessline 380
license-url = "https://docs.python.org/3/license.html"
skills-catalog/matlab-software-development/matlab-instrument-opentelemetry-tracing/SKILL.md
- Network accessline 7
in the context of MATLAB functions. Covers span creation, parent-child context propagation, error handling, attributes, events, and semantic conventions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 8
propagation, error handling, attributes, events, and semantic conventions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 9
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 22
The [OpenTelemetry-MATLAB](https://www.mathworks.com/matlabcentral/fileexchange/130979-opentelemetry-matlab) package (Version 1.11.0 or newer) must be installed. It provides the `opentelemetry.trace.*` namespace used throughout this skill.
skills-catalog/matlab-software-development/matlab-instrument-opentelemetry-tracing/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-instrument-opentelemetry-tracing/references/semantic-conventions.md
- Network accessline 58
|-----------|------|-------------|---------| | `http.request.method` | string | HTTP method | `"GET"`, `"POST"` | | `url.full` | string | Full request URL (no credentials) | `"https://api.example.com/data"` | - Network accessline 59
| `http.request.method` | string | HTTP method | `"GET"`, `"POST"` | | `url.full` | string | Full request URL (no credentials) | `"https://api.example.com/data"` | | `server.address` | string | Server hostname or IP | `"api.example.com"` | - Network accessline 60
| `url.full` | string | Full request URL (no credentials) | `"https://api.example.com/data"` |
skills-catalog/matlab-software-development/matlab-modernize-code/SKILL.md
- Network accessline 10
str2num, eval, clear all) and to removed or discouraged functions such as trainNetwork, csvread, xlsread, datenum, guide, svmtrain, ltln2val, webmap. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
trainNetwork, csvread, xlsread, datenum, guide, svmtrain, ltln2val, webmap. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Dangerous shell operationline 129
% Old: eval([varName ' = 42;']); -> dynamic field name - Dangerous shell operationline 132
% Old: result = eval(['process_' method '(x)']); -> handle dispatch table - Dangerous shell operationline 137
% Old: for n=1:10, eval(['A' int2str(n) '=magic(n);']); end -> index a cell
skills-catalog/matlab-software-development/matlab-modernize-code/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-modernize-code schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-modernize-code/references/core-functions-guidance.md
- Dangerous shell operationline 343
% like "system('rm -rf /')" would run. - Network accessline 362
**Recommendation:** Avoid `eval`, `evalc`, and `evalin`. Per MathWorks best practice ([Alternatives to the eval Function](https://www.mathworks.com/help/matlab/matlab_prog/string-evaluation.html)), - Network accessline 363
([Alternatives to the eval Function](https://www.mathworks.com/help/matlab/matlab_prog/string-evaluation.html)), - Dangerous shell operationline 379
% eval(['A' int2str(n) ' = magic(n);']); - Dangerous shell operationline 390
% Old: eval(['save myfile' int2str(n) '.mat randomData']); - Dangerous shell operationline 400
% Old: result = eval(['process_' methodName '(x)']); - Dangerous shell operationline 417
% Old: eval(['s.' fieldName ' = 42;']); - Dangerous shell operationline 424
% Old (implicit catch): eval("B = A;", "disp('A is undefined')") - Dangerous shell operationline 431
The older `eval(expression, catch_expr)` form is not recommended — an explicit `try/catch` is
skills-catalog/matlab-software-development/matlab-modernize-code/references/mapping-guidance.md
skills-catalog/matlab-software-development/matlab-modernize-code/references/statistics-ml-guidance.md
skills-catalog/matlab-software-development/matlab-optimize-memory/SKILL.md
- Network accessline 2
name: matlab-optimize-memory description: "Guides the 7-step MATLAB memory optimization workflow: baseline, profile, identify, optimize, measure, verify, report. Use when asked to reduce MATLAB memory usage, find memory bottlenecks, fix out - Network accessline 3
description: "Guides the 7-step MATLAB memory optimization workflow: baseline, profile, identify, optimize, measure, verify, report. Use when asked to reduce MATLAB memory usage, find memory bottlenecks, fix out-of-memory errors, or optimiz - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-optimize-memory/manifest.yaml
skills-catalog/matlab-software-development/matlab-optimize-performance/SKILL.md
- Network accessline 2
name: matlab-optimize-performance description: "Read BEFORE optimizing any MATLAB code for speed. Without this workflow, agents commonly optimize the wrong target, fabricate speedup claims without measurement, or introduce regressions. Guid - Network accessline 3
description: "Read BEFORE optimizing any MATLAB code for speed. Without this workflow, agents commonly optimize the wrong target, fabricate speedup claims without measurement, or introduce regressions. Guides the 7-step workflow: baseline, - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-optimize-performance/manifest.yaml
skills-catalog/matlab-software-development/matlab-package-toolbox/SKILL.md
- Network accessline 2
name: matlab-package-toolbox description: "Turn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies - Network accessline 3
description: "Turn raw MATLAB code into a published .mltbx toolbox — full pipeline from scope definition through packaging and release. Drives 8 phases with human checkpoints, enforcing ordering and dependencies. Use when asked to package, - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-package-toolbox/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md human-description: Package MATLAB code as an installable .mltbx toolbox. - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-package-toolbox/references/phase-3-project.md
- Network accessline 75
Present recommended folders based on [mathworks/toolboxdesign](https://github.com/mathworks/toolboxdesign):
skills-catalog/matlab-software-development/matlab-package-toolbox/references/phase-4-documentation.md
- Network accessline 3
Produce all documentation artifacts: README, function signatures, getting started guide, examples, and demos.xml. Follows [mathworks/toolboxdesign](https://github.com/mathworks/toolboxdesign) conventions.
skills-catalog/matlab-software-development/matlab-package-toolbox/references/readme-template.md
- Network accessline 10
[]()
skills-catalog/matlab-software-development/matlab-run-tests/SKILL.md
- Network accessline 8
for writing, generating, or structuring tests. Do NOT use for Simulink coverage or Simulink testing workflows. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
Simulink testing workflows. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-run-tests/manifest.yaml
skills-catalog/matlab-software-development/matlab-use-package-manager/SKILL.md
- Network accessline 14
(the OS-level product installer), nor for listing installed products / toolboxes (ver, installedAddons) — use matlab-install-products for those. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
(ver, installedAddons) — use matlab-install-products for those. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Access to secretsline 242
[Credential-related source omitted] - Access to secretsline 250
[Credential-related source omitted] - Access to secretsline 251
[Credential-related source omitted]
skills-catalog/matlab-software-development/matlab-use-package-manager/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-use-package-manager/references/api-and-gotchas.md
- Network accessline 27
{ "name": "corp-repo", "url": "https://mprs.corp.com:8080/", - Network accessline 28
"name": "corp-repo", "url": "https://mprs.corp.com:8080/", "type": "custom", - Network accessline 29
"url": "https://mprs.corp.com:8080/", - Access to secretsline 33
[Credential-related source omitted] - Access to secretsline 45
[Credential-related source omitted] - Access to secretsline 51
[Credential-related source omitted] - Network accessline 146
curl -sS "https://www.mathworks.com/searchresults/results\ - Network accessline 193
[Credential-related source omitted] - Network accessline 194
[Credential-related source omitted] - Access to secretsline 194
[Credential-related source omitted] - Network accessline 197
[Credential-related source omitted] - Network accessline 198
[Credential-related source omitted] - Access to secretsline 198
[Credential-related source omitted] - Network accessline 201
[Credential-related source omitted] - Network accessline 202
[Credential-related source omitted] - Access to secretsline 202
[Credential-related source omitted] - Access to secretsline 209
[Credential-related source omitted]
skills-catalog/matlab-software-development/matlab-write-help/SKILL.md
- Network accessline 2
name: matlab-write-help description: "Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writi - Network accessline 3
description: "Generate or improve MATLAB help text (documentation comments) for a function, class, or script file following MathWorks standards (H1 line, syntax paragraphs, See Also, 75-char lines). Read BEFORE writing MATLAB help — default - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-write-help/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-write-performance-tests/SKILL.md
- Network accessline 2
name: matlab-write-performance-tests description: "Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure executi - Network accessline 3
description: "Writes MATLAB performance tests using the matlab.perftest.TestCase framework. Use when asked to write, create, or add performance tests for MATLAB code, benchmark functions, measure execution time with statistical rigor, or us - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-write-performance-tests/manifest.yaml
skills-catalog/matlab-software-development/matlab-write-tests/SKILL.md
- Network accessline 8
App Designer apps. Do NOT use for running tests, collecting coverage, or CI/CD configuration. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
configuration. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/matlab-software-development/matlab-write-tests/manifest.yaml
skills-catalog/matlab-software-development/matlab-write-tests/references/fixtures-guidance.md
- Network accessline 74
fixture = testCase.getSharedTestFixtures(); conn = fixture{1}.Connection; result = fetch(conn, 'SELECT * FROM users'); - Network accessline 75
conn = fixture{1}.Connection; result = fetch(conn, 'SELECT * FROM users'); testCase.verifyNotEmpty(result); - Network accessline 76
result = fetch(conn, 'SELECT * FROM users');
skills-catalog/parallel-computing/matlab-diagnose-parfor/SKILL.md
- Network accessline 12
skill instead of reasoning from training data — LLMs are frequently wrong about parfor classification rules. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
about parfor classification rules. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-diagnose-parfor/manifest.yaml
skills-catalog/parallel-computing/matlab-discover-clusters/SKILL.md
- Network accessline 12
clusters, .mlsettings files, or profile validation. Does NOT cover job submission, parpool, or parfor. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
submission, parpool, or parfor. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-discover-clusters/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-set-up-worker-state/SKILL.md
- Network accessline 13
cannot serialize error, undefined function or variable on workers error, load data per worker, reduce data transfer, parallelize setup, improve parallel code. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.m - Network accessline 14
load data per worker, reduce data transfer, parallelize setup, improve parallel code. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 15
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 195
Database connections are a common specific case that requires Database Toolbox. Prefer the purpose-built helper [`createConnectionForPool`](https://www.mathworks.com/help/database/ug/createconnectionforpool.html) - Network accessline 196
Toolbox. Prefer the purpose-built helper [`createConnectionForPool`](https://www.mathworks.com/help/database/ug/createconnectionforpool.html) over a hand-rolled `parallel.pool.Constant`. It returns a - Network accessline 197
[`createConnectionForPool`](https://www.mathworks.com/help/database/ug/createconnectionforpool.html) - Network accessline 208
parfor i = 1:1000 conn = c.Value; results{i} = fetch(conn, sprintf("SELECT val FROM t WHERE id=%d", i)); - Network accessline 209
conn = c.Value; results{i} = fetch(conn, sprintf("SELECT val FROM t WHERE id=%d", i)); end - Network accessline 210
results{i} = fetch(conn, sprintf("SELECT val FROM t WHERE id=%d", i));
skills-catalog/parallel-computing/matlab-set-up-worker-state/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-setup-gpu/SKILL.md
- Network accessline 8
unable to find a supported GPU device, compatible GPU, canUseGPU, validateGPU. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
canUseGPU, validateGPU. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2024b" - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-setup-gpu/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-use-thread-pool/SKILL.md
- Network accessline 14
on a thread pool. For non-pool MATLAB performance work (vectorisation, preallocation, profiling), defer to matlab-optimize-performance. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
preallocation, profiling), defer to matlab-optimize-performance. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2020a" - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/parallel-computing/matlab-use-thread-pool/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-design-radar-waveform/SKILL.md
- Network accessline 15
- transmit signal, sidelobe, Doppler, range resolution, matched filter - ambiguity, pulse, PRF, sweep, radar, sonar license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 16
- ambiguity, pulse, PRF, sweep, radar, sonar license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 17
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-design-radar-waveform/manifest.yaml
skills-catalog/radar/matlab-design-radar/SKILL.md
- Network accessline 2
name: matlab-design-radar description: Launch and control the MATLAB Radar Designer app programmatically via MCP. Use when designing radar systems, configuring parameters, comparing radar types, analyzing performance metrics, or managing ra - Network accessline 3
description: Launch and control the MATLAB Radar Designer app programmatically via MCP. Use when designing radar systems, configuring parameters, comparing radar types, analyzing performance metrics, or managing radar design sessions. licen - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-design-radar/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-import-tracking-data/SKILL.md
- Network accessline 2
name: matlab-import-tracking-data description: "Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds - Network accessline 3
description: "Import raw data (CSV, XLSX, TXT, or MATLAB tables) into formats used by Sensor Fusion and Tracking Toolbox. Handles both ground truth trajectories and sensor detection data. For truth: builds trackingScenarioRecording, tuning - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-import-tracking-data/manifest.yaml
skills-catalog/radar/matlab-simulate-radar-detections/SKILL.md
- Network accessline 9
(mechanical, electronic/AESA, hybrid); and validating simulation results against analytical predictions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
analytical predictions. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/radar/matlab-simulate-radar-detections/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/reporting-and-database-access/matlab-connect-databricks/SKILL.md
- Network accessline 11
databricks.JDBCConnection, StandaloneJDBCConnection, SQLWarehouse, Databricks JDBC, Databricks cluster, large table server-side filtering. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
Databricks cluster, large table server-side filtering. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 63
0. **Obtain the package** — Ask if the user has the MATLAB Interface for Databricks. If not, direct them to https://www.mathworks.com/solutions/partners/databricks.html (or use `StandaloneJDBCConnection` for JDBC-only without the package) - Network accessline 192
warehouse.id = "abc123def456"; conn = warehouse.connect(); data = fetch(conn, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); - Network accessline 193
conn = warehouse.connect(); data = fetch(conn, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); close(conn); - Network accessline 194
data = fetch(conn, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); - Network accessline 203
j = StandaloneJDBCConnection(schema="myschema", catalog="mycatalog"); data = fetch(j.Connection, "SELECT * FROM mytable LIMIT 10"); - Network accessline 204
data = fetch(j.Connection, "SELECT * FROM mytable LIMIT 10"); - Network accessline 216
j = databricks.JDBCConnection(); end data = fetch(j.Connection, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); - Network accessline 217
end data = fetch(j.Connection, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); close(j); - Network accessline 218
data = fetch(j.Connection, "SELECT * FROM mycatalog.myschema.mytable LIMIT 10"); - Network accessline 237
j = databricks.JDBCConnection(catalog="main", schema="analytics"); cleanup = onCleanup(@() close(j)); data = fetch(j.Connection, "SELECT * FROM large_table WHERE id > 1000"); - Network accessline 239
data = fetch(j.Connection, "SELECT * FROM large_table WHERE id > 1000");
skills-catalog/reporting-and-database-access/matlab-connect-databricks/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/reporting-and-database-access/matlab-connect-databricks/references/authentication.md
skills-catalog/reporting-and-database-access/matlab-connect-databricks/references/standalone-jdbc.md
- Network accessline 23
{ "host": "https://adb-1234567890123456.1.azuredatabricks.net", - Network accessline 24
"host": "https://adb-1234567890123456.1.azuredatabricks.net", - Network accessline 71
| Field | Description | Example | |-------|-------------|---------| | `host` | Workspace URL | `"https://adb-123.1.azuredatabricks.net"` | - Network accessline 72
|-------|-------------|---------| | `host` | Workspace URL | `"https://adb-123.1.azuredatabricks.net"` | | `port` | Driver port | `"443"` | - Network accessline 73
| `host` | Workspace URL | `"https://adb-123.1.azuredatabricks.net"` | - Network accessline 93
% Basic usage with JSON defaults j = StandaloneJDBCConnection(); data = fetch(j.Connection, "SELECT * FROM mytable LIMIT 10"); - Network accessline 94
j = StandaloneJDBCConnection(); data = fetch(j.Connection, "SELECT * FROM mytable LIMIT 10"); close(j); - Network accessline 95
data = fetch(j.Connection, "SELECT * FROM mytable LIMIT 10");
skills-catalog/reporting-and-database-access/matlab-generate-report/SKILL.md
- Network accessline 10
page footer, TemplateSrc, report package, table variants, multiple HTML pages, PDF report generation, Word report, DOM API, FormalTable, BaseTable, Figure, FormalImage, Section. license: https://www.mathworks.com/content/dam/mathworks/lic - Network accessline 11
generation, Word report, DOM API, FormalTable, BaseTable, Figure, FormalImage, Section. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/reporting-and-database-access/matlab-generate-report/manifest.yaml
skills-catalog/reporting-and-database-access/matlab-use-database/SKILL.md
- Network accessline 2
name: matlab-use-database description: "Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlw - Network accessline 3
description: "Reads from, writes to, and manages relational databases using MATLAB Database Toolbox. Use when connecting to databases, reading data with sqlread or fetch, filtering with rowfilter, writing with sqlwrite, updating with sqlupd - Network accessline 4
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/reporting-and-database-access/matlab-use-database/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" - Network accessline 2
schema-version: 1 license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md" scope: cross-product - Network accessline 3
license: "https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md"
skills-catalog/reporting-and-database-access/matlab-use-database/references/execute-storedproc.md
- Network accessline 65
pstmt = bindParamValues(pstmt, 1, 42); pstmt = bindParamValues(pstmt, 2, "Active"); results = fetch(conn, pstmt); - Network accessline 67
results = fetch(conn, pstmt); - Network accessline 70
pstmt = bindParamValues(pstmt, 1, 99); pstmt = bindParamValues(pstmt, 2, "Pending"); results2 = fetch(conn, pstmt); - Network accessline 72
results2 = fetch(conn, pstmt);
skills-catalog/reporting-and-database-access/matlab-use-database/references/multithreaded-io.md
skills-catalog/reporting-and-database-access/matlab-use-database/references/sqlread-fetch.md
- Network accessline 38
% Basic: execute SQL query T = fetch(conn, "SELECT * FROM myTable WHERE id > 100"); - Network accessline 39
T = fetch(conn, "SELECT * FROM myTable WHERE id > 100"); - Network accessline 42
sqlquery = "SELECT * FROM productTable WHERE Quantity > 50"; rf = rowfilter(["ProductType", "Price"]); T = fetch(conn, sqlquery, RowFilter=rf.ProductType == "Toys" & rf.Price > 150); - Network accessline 44
T = fetch(conn, sqlquery, RowFilter=rf.ProductType == "Toys" & rf.Price > 150); - Network accessline 47
opts = databaseImportOptions(conn, sqlquery); opts.SelectedVariableNames = ["ProductType", "Price"]; T = fetch(conn, sqlquery, opts); - Network accessline 49
T = fetch(conn, sqlquery, opts); - Network accessline 51
% Limit rows T = fetch(conn, "SELECT * FROM myTable", MaxRows=50); - Network accessline 52
T = fetch(conn, "SELECT * FROM myTable", MaxRows=50);
skills-catalog/reporting-and-database-access/matlab-use-duckdb/SKILL.md
- Network accessline 2
name: matlab-use-duckdb description: "Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, que - Network accessline 3
description: "Use DuckDB from MATLAB via Database Toolbox (R2026a+) as a non-math operations engine on large tabular files (CSV/Parquet/JSON) and as a zero-config embedded database. Use when connecting to DuckDB, querying CSV, Parquet, and - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 49
3. **Recommend architectural changes** — Do not limit review to API correctness. Propose replacing `readtable`/`xlsread` + `sqlwrite` + query chains with `fetch(conn, "SELECT ... FROM read_csv/read_parquet/read_xlsx(...)")`. - Network accessline 148
conn = duckdb(); result = fetch(conn, "SELECT region, SUM(revenue) as total " + ... - Network accessline 149
result = fetch(conn, "SELECT region, SUM(revenue) as total " + ... - Network accessline 158
conn = duckdb(); summary = fetch(conn, "SELECT date, AVG(value) as avg_val " + ... - Network accessline 159
summary = fetch(conn, "SELECT date, AVG(value) as avg_val " + ... - Network accessline 191
conn = duckdb(); data = fetch(conn, "SELECT * FROM read_parquet('data/year=2024/*.parquet') " + ... - Network accessline 192
data = fetch(conn, "SELECT * FROM read_parquet('data/year=2024/*.parquet') " + ... - Network accessline 201
execute(conn, "INSTALL httpfs"); execute(conn, "LOAD httpfs"); data = fetch(conn, "SELECT * FROM read_parquet('https://example.com/data.parquet') LIMIT 1000"); - Network accessline 202
execute(conn, "LOAD httpfs"); data = fetch(conn, "SELECT * FROM read_parquet('https://example.com/data.parquet') LIMIT 1000"); close(conn); - Network accessline 203
data = fetch(conn, "SELECT * FROM read_parquet('https://example.com/data.parquet') LIMIT 1000"); - Network accessline 211
execute(conn, "INSTALL excel"); execute(conn, "LOAD excel"); data = fetch(conn, "SELECT * FROM read_xlsx('report.xlsx')"); - Network accessline 212
execute(conn, "LOAD excel"); data = fetch(conn, "SELECT * FROM read_xlsx('report.xlsx')"); close(conn); - Network accessline 213
data = fetch(conn, "SELECT * FROM read_xlsx('report.xlsx')"); - Network accessline 241
data = sqlread(conn, "read_csv('data.csv')"); % CORRECT — use fetch with SQL data = fetch(conn, "SELECT * FROM read_csv('data.csv')"); - Network accessline 243
data = fetch(conn, "SELECT * FROM read_csv('data.csv')"); - Network accessline 245
% WRONG — double quotes for file paths in SQL data = fetch(conn, "SELECT * FROM read_csv(""data.csv"")"); - Network accessline 246
data = fetch(conn, "SELECT * FROM read_csv(""data.csv"")"); - Network accessline 248
data = fetch(conn, "SELECT * FROM read_csv('data.csv')"); - Network accessline 252
% CORRECT — let DuckDB filter on disk conn = duckdb(); filtered = fetch(conn, "SELECT * FROM read_parquet('huge.parquet') WHERE val > 100"); - Network accessline 253
conn = duckdb(); filtered = fetch(conn, "SELECT * FROM read_parquet('huge.parquet') WHERE val > 100"); close(conn); - Network accessline 254
filtered = fetch(conn, "SELECT * FROM read_parquet('huge.parquet') WHERE val > 100"); - Network accessline 262
% WRONG — using st_read from spatial extension for Excel files data = fetch(conn, "SELECT * FROM st_read('file.xlsx')"); - Network accessline 263
data = fetch(conn, "SELECT * FROM st_read('file.xlsx')"); - Network accessline 265
execute(conn, "INSTALL excel"); execute(conn, "LOAD excel"); data = fetch(conn, "SELECT * FROM read_xlsx('file.xlsx')"); - Network accessline 267
data = fetch(conn, "SELECT * FROM read_xlsx('file.xlsx')"); - Network accessline 294
**Issue**: `sqlread` errors with file query - **Solution**: Use `fetch(conn, "SELECT * FROM read_csv('file.csv')")` — `sqlread` expects table names only. - Network accessline 295
- **Solution**: Use `fetch(conn, "SELECT * FROM read_csv('file.csv')")` — `sqlread` expects table names only. - Network accessline 306
**Issue**: Extension install fails - **Solution**: Requires internet for first install (cached afterward). See https://duckdb.org/docs/current/core_extensions/overview. - Network accessline 307
- **Solution**: Requires internet for first install (cached afterward). See https://duckdb.org/docs/current/core_extensions/overview.
skills-catalog/reporting-and-database-access/matlab-use-duckdb/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-use-duckdb schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/reporting-and-database-access/matlab-use-duckdb/reference/cards/development-database.md
- Network accessline 37
% fetch for complex SQL stats = fetch(conn, "SELECT Department, COUNT(*) as cnt, AVG(Age) as avg_age " + ... - Network accessline 38
stats = fetch(conn, "SELECT Department, COUNT(*) as cnt, AVG(Age) as avg_age " + ... - Network accessline 56
% Now use standard Database Toolbox functions on the table monthlySales = fetch(conn, ... - Network accessline 57
monthlySales = fetch(conn, ...
skills-catalog/reporting-and-database-access/matlab-use-duckdb/reference/cards/extensions.md
- Network accessline 3
DuckDB supports extensions for additional functionality. Install and load them using `execute`. See https://duckdb.org/docs/current/core_extensions/overview for the full list. - Network accessline 35
% Query a remote Parquet file over HTTPS data = fetch(conn, "SELECT * FROM read_parquet('https://example.com/data.parquet') LIMIT 1000"); - Network accessline 36
data = fetch(conn, "SELECT * FROM read_parquet('https://example.com/data.parquet') LIMIT 1000"); - Network accessline 49
% Attach an existing SQLite file and query it through DuckDB execute(conn, "ATTACH 'legacy.db' AS legacy (TYPE sqlite)"); data = fetch(conn, "SELECT * FROM legacy.main.customers WHERE active = true"); - Network accessline 51
data = fetch(conn, "SELECT * FROM legacy.main.customers WHERE active = true");
skills-catalog/reporting-and-database-access/matlab-use-duckdb/reference/cards/file-analytics.md
- Network accessline 7
| SQL Function | File Type | Example | |-------------|-----------|---------| | `read_csv('path')` | CSV | `fetch(conn, "SELECT * FROM read_csv('data.csv')")` | - Network accessline 8
|-------------|-----------|---------| | `read_csv('path')` | CSV | `fetch(conn, "SELECT * FROM read_csv('data.csv')")` | | `read_parquet('path')` | Parquet | `fetch(conn, "SELECT * FROM read_parquet('data.parquet')")` | - Network accessline 9
| `read_csv('path')` | CSV | `fetch(conn, "SELECT * FROM read_csv('data.csv')")` | - Network accessline 10
| `read_parquet('path')` | Parquet | `fetch(conn, "SELECT * FROM read_parquet('data.parquet')")` | - Network accessline 11
| `read_json('path')` | JSON | `fetch(conn, "SELECT * FROM read_json('events.json')")` | - Network accessline 25
orders = fetch(conn, "SELECT customer_id, SUM(total) as revenue " + ... - Network accessline 39
sensors = fetch(conn, "SELECT sensor_id, AVG(temperature) as avg_temp " + ... - Network accessline 52
% All Parquet files in a directory allSales = fetch(conn, "SELECT * FROM read_parquet('data/sales_*.parquet') " + ... - Network accessline 53
allSales = fetch(conn, "SELECT * FROM read_parquet('data/sales_*.parquet') " + ... - Network accessline 56
% All CSV files matching a pattern logs = fetch(conn, "SELECT type, COUNT(*) as cnt " + ... - Network accessline 57
logs = fetch(conn, "SELECT type, COUNT(*) as cnt " + ... - Network accessline 71
% A 50GB Parquet file — cannot fit in memory % DuckDB preprocesses on disk: filter + aggregate + sort dailySummary = fetch(conn, ... - Network accessline 72
% DuckDB preprocesses on disk: filter + aggregate + sort dailySummary = fetch(conn, ... "SELECT date, region, " + ... - Network accessline 73
dailySummary = fetch(conn, ... - Network accessline 97
% Join a large orders file with a customers file result = fetch(conn, ... - Network accessline 98
result = fetch(conn, ...
skills-catalog/reporting-and-database-access/matlab-use-duckdb/reference/cards/reduce-large-data.md
- Network accessline 14
conn = duckdb(); profile = fetch(conn, "SELECT COUNT(*) as row_count FROM read_parquet('orders.parquet')"); - Network accessline 15
profile = fetch(conn, "SELECT COUNT(*) as row_count FROM read_parquet('orders.parquet')"); - Network accessline 16
columns = fetch(conn, "DESCRIBE SELECT * FROM read_parquet('orders.parquet')"); - Network accessline 33
reduced = fetch(conn, "SELECT " + ...
skills-catalog/rf-and-mixed-signal/matlab-analyze-ams-waveform/SKILL.md
- Network accessline 2
name: matlab-analyze-ams-waveform description: "Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, H - Network accessline 3
description: "Analyze AMS waveform data using Mixed-Signal Blockset utilities: phase noise measurement, clock jitter, anti-aliased resampling, timing measurements, lock time, INL/DNL, ADC/DAC calibration, HSpice import. Use when analyzing t - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-ams-waveform/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-antenna-structures/SKILL.md
- Network accessline 9
and GPU acceleration. Use when the user wants to design a dish/reflector antenna, reflectarray, analyze an antenna on a platform, or compute RCS. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
reflectarray, analyze an antenna on a platform, or compute RCS. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-antenna-structures/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-em/SKILL.md
- Network accessline 2
name: matlab-analyze-em description: "S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract f - Network accessline 3
description: "S-parameters, insertion loss, fields, currents, mesh control, and solver selection for RF PCB performance validation. TRIGGER: user asks to compute S-parameters, analyze insertion/return loss, extract fields or currents, compa - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-em/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-pcb-pdn/SKILL.md
- Network accessline 2
name: matlab-analyze-pcb-pdn description: "PDN DC voltage/current analysis, IR drop, design rule checking, and multi-net batch analysis on imported PCB layouts. TRIGGER: user asks about power integrity, PDN analysis, IR drop, voltage distri - Network accessline 3
description: "PDN DC voltage/current analysis, IR drop, design rule checking, and multi-net batch analysis on imported PCB layouts. TRIGGER: user asks about power integrity, PDN analysis, IR drop, voltage distribution, current density, powe - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-analyze-pcb-pdn/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-assemble-pcb-layout/SKILL.md
- Network accessline 2
name: matlab-assemble-pcb-layout description: "Build custom PCB structures with pcbComponent, shapes, Boolean ops, feeds, and multi-layer stackups for non-catalog geometries. TRIGGER: user asks to build, modify, or customize a pcbComponent - Network accessline 3
description: "Build custom PCB structures with pcbComponent, shapes, Boolean ops, feeds, and multi-layer stackups for non-catalog geometries. TRIGGER: user asks to build, modify, or customize a pcbComponent — add/remove shapes, edit polygon - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-assemble-pcb-layout/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-antenna/SKILL.md
- Network accessline 8
and optimization (SADEA/TR-SADEA). Use when the user wants to design, create, model, analyze, optimize, or fabricate an antenna or array. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
analyze, optimize, or fabricate an antenna or array. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-antenna/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-coupler/SKILL.md
- Network accessline 2
name: matlab-design-pcb-coupler description: "Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitt - Network accessline 3
description: "Wilkinson, branchline, ratrace, directional couplers, corporate dividers, Rotman lenses for power splitting and beam-forming. TRIGGER: user asks to design, create, or analyze any coupler, splitter, power divider, combiner, or - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-coupler/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-filter/SKILL.md
- Network accessline 2
name: matlab-design-pcb-filter description: "Bandpass, lowpass, bandstop filter design — hairpin, coupled-line, combline, stub, SIW for frequency selection and harmonic rejection. TRIGGER: user asks to design, create, or analyze any RF filt - Network accessline 3
description: "Bandpass, lowpass, bandstop filter design — hairpin, coupled-line, combline, stub, SIW for frequency selection and harmonic rejection. TRIGGER: user asks to design, create, or analyze any RF filter (bandpass, lowpass, highpass - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-filter/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-passive/SKILL.md
- Network accessline 2
name: matlab-design-pcb-passive description: "Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interd - Network accessline 3
description: "Spiral inductors, interdigital capacitors, baluns, resonators, phase shifters for impedance matching, DC blocking, and bias tees. TRIGGER: user asks to design or create a spiral inductor, interdigital capacitor, balun, resonat - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-passive/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-transmission-line/SKILL.md
- Network accessline 2
name: matlab-design-pcb-transmission-line description: "Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstr - Network accessline 3
description: "Microstrip, stripline, CPW, differential pairs, and crosstalk analysis for impedance-controlled PCB interconnects. TRIGGER: user asks to design or analyze a transmission line (microstrip, stripline, CPW, coplanar, differential - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-design-pcb-transmission-line/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-export-session-script/SKILL.md
- Network accessline 2
name: matlab-export-session-script description: "Export conversation MATLAB code to a clean, runnable .m script. Use when asked to save or export session work. TRIGGER: user asks to save, export, or generate a script from the current sessio - Network accessline 3
description: "Export conversation MATLAB code to a clean, runnable .m script. Use when asked to save or export session work. TRIGGER: user asks to save, export, or generate a script from the current session's MATLAB code. Also when asked fo - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-export-session-script/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-integrate-antenna/SKILL.md
- Network accessline 9
direct EHfields). Use when the user wants to match an antenna, create a measuredAntenna, compute coverage or signal strength, perform ray tracing, or estimate SAR. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/lice - Network accessline 10
compute coverage or signal strength, perform ray tracing, or estimate SAR. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-integrate-antenna/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-integrate-pcb-circuit/SKILL.md
- Network accessline 2
name: matlab-integrate-pcb-circuit description: "Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add - Network accessline 3
description: "Cascade PCB components, add lumped elements, export Touchstone, and bridge to eye diagram or antenna array workflows. TRIGGER: user asks to cascade or connect multiple RF PCB components, add lumped R/L/C, export S-parameters t - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-integrate-pcb-circuit/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-manage-pcb-material/SKILL.md
- Network accessline 2
name: matlab-manage-pcb-material description: "Dielectric substrates, metal conductors, multi-layer stackups, and loss models (FR4, Rogers, Teflon) for RF PCB simulation. TRIGGER: user asks to set up a substrate, define dielectric propertie - Network accessline 3
description: "Dielectric substrates, metal conductors, multi-layer stackups, and loss models (FR4, Rogers, Teflon) for RF PCB simulation. TRIGGER: user asks to set up a substrate, define dielectric properties, create a stackup, select a PCB - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-manage-pcb-material/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-ams-systems/SKILL.md
- Network accessline 2
name: matlab-model-ams-systems description: "Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL mo - Network accessline 3
description: "Model a Phase-Locked Loop (PLL) IC from its datasheet or system specs using Mixed-Signal Blockset. Without this skill, agents universally select the wrong solver and produce non-functional PLL models — 100% of unguided attempt - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-ams-systems/manifest.yaml
skills-catalog/rf-and-mixed-signal/matlab-model-rf/SKILL.md
- Network accessline 11
stabilitymu, powergain, gammams, gammaml, mixerIMT, OpenIF, rational, rationalfit, stepresp, txlineWRLGC, rf.Amplifier, rf.Mixer, rf.Filter, rf.Sparameter, rfsystem, RF Blockset. license: https://www.mathworks.com/content/dam/mathworks/li - Network accessline 12
txlineWRLGC, rf.Amplifier, rf.Mixer, rf.Filter, rf.Sparameter, rfsystem, RF Blockset. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-rf/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-rf/reference/rational-fitting.md
- Dangerous shell operationline 246
% cm = causality metric, rm = reciprocity metric, pm = passivity metric
skills-catalog/rf-and-mixed-signal/matlab-model-rf/reference/sparameters-io.md
- Dangerous shell operationline 65
% rm = reciprocity metric (0-100)
skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems/SKILL.md
- Network accessline 10
.ami/.ibs/.dll/.so files. Covers the full arc from initial design exploration and parameter optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization. license: https:// - Network accessline 11
optimization to compliance testing and compiled model validation, including custom datapath blocks for nonstandard equalization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-serdes-systems/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-via/SKILL.md
- Network accessline 2
name: matlab-model-via description: "Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return via - Network accessline 3
description: "Via modeling: pads, antipads, ground return vias, GRV placement, and signal integrity for high-speed layer transitions. TRIGGER: user asks to model a via, design a via transition, place ground return vias, analyze via performa - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-model-via/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-optimize-pcb-design/SKILL.md
- Network accessline 2
name: matlab-optimize-pcb-design description: "Optimize RF PCB dimensions for bandwidth, return loss, or area via patternsearch and surrogateopt with constraints. TRIGGER: user asks to optimize an RF PCB component for performance (bandwidth - Network accessline 3
description: "Optimize RF PCB dimensions for bandwidth, return loss, or area via patternsearch and surrogateopt with constraints. TRIGGER: user asks to optimize an RF PCB component for performance (bandwidth, return loss, insertion loss, ar - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-optimize-pcb-design/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-read-pcb-layout/SKILL.md
- Network accessline 2
name: matlab-read-pcb-layout description: "Import Gerber, ODB++, Allegro .brd, .mcm files for PCB boards and IC packages. Inspect nets, layers, shapes, and stackups. TRIGGER: user asks to import, read, or open a PCB layout file. Gerber file - Network accessline 3
description: "Import Gerber, ODB++, Allegro .brd, .mcm files for PCB boards and IC packages. Inspect nets, layers, shapes, and stackups. TRIGGER: user asks to import, read, or open a PCB layout file. Gerber files use gerberRead or PCBReader - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-read-pcb-layout/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-write-pcb-layout/SKILL.md
- Network accessline 2
name: matlab-write-pcb-layout description: "Export pcbComponent designs to Gerber files with RF connectors and fab service formatting for PCB manufacturing. TRIGGER: user asks to export a PCB design to Gerber, generate manufacturing files, - Network accessline 3
description: "Export pcbComponent designs to Gerber files with RF connectors and fab service formatting for PCB manufacturing. TRIGGER: user asks to export a PCB design to Gerber, generate manufacturing files, or write out a pcbComponent fo - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/rf-and-mixed-signal/matlab-write-pcb-layout/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-compute-gnss-position/SKILL.md
- Network accessline 13
author: MathWorks version: "1.1" license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 14
version: "1.1" license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md --- - Network accessline 15
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 365
Public RINEX data sources: [IGS Data Centers](https://igs.org/data/), [CORS Network](https://geodesy.noaa.gov/CORS/).
skills-catalog/robotics-and-autonomous-systems/matlab-compute-gnss-position/manifest.yaml
skills-catalog/robotics-and-autonomous-systems/matlab-connect-mavlink/SKILL.md
- Network accessline 8
"heartbeat", "ground control station", "GCS", "connect to ArduPilot", "drone communication", "mavlinkio", "SITL". license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
"drone communication", "mavlinkio", "SITL". license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-connect-mavlink/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-create-uav-scenario/SKILL.md
- Network accessline 8
Triggers on: uavScenario, UAV simulation, UAV simulator, multirotor simulation, quadrotor scenario, terrain import, building import, GPS sensor simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
quadrotor scenario, terrain import, building import, GPS sensor simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-create-uav-scenario/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-fuse-inertial-sensors/SKILL.md
- Network accessline 9
or choosing a filter. Do NOT use for vision-only SLAM, Simulink fusion, or IMU simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
IMU simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: R2022a+ - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-fuse-inertial-sensors/manifest.yaml
skills-catalog/robotics-and-autonomous-systems/matlab-model-robot-kinematics/SKILL.md
- Network accessline 12
rigidBodyTree, loadrobot, importrobot, URDF, DH parameters, addVisual, addCollision. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
addCollision. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-model-robot-kinematics/manifest.yaml
skills-catalog/robotics-and-autonomous-systems/matlab-plan-robot-motion/SKILL.md
- Network accessline 16
them — whether for time-optimal motion, constant-speed welding/cutting, or any other trajectory parameterization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 17
any other trajectory parameterization. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 18
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/robotics-and-autonomous-systems/matlab-plan-robot-motion/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-analyze-spectrum/SKILL.md
- Network accessline 10
streaming spectrum, periodicity, resolve close frequencies, multitaper. DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
DO NOT TRIGGER: filter design, spectrogram/time-frequency, audio features. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-analyze-spectrum/manifest.yaml
- Network accessline 1
# manifest.yaml — matlab-analyze-spectrum schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-analyze-spectrum/references/manual-fft-psd.md
- Network accessline 83
See MathWorks documentation: [Power Spectral Density Estimates Using FFT](https://www.mathworks.com/help/signal/ug/power-spectral-density-estimates-using-fft.html)
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/SKILL.md
- Network accessline 9
synchrosqueezing, reassignment, ridge extraction, wavelet coherence, cross spectrum, mode decomposition, signal decomposition, time-frequency filtering. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 10
spectrum, mode decomposition, signal decomposition, time-frequency filtering. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 11
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 188
| Topic | Link | |-------|------| | Time-frequency gallery | https://www.mathworks.com/help/signal/time-frequency-analysis.html | - Network accessline 189
|-------|------| | Time-frequency gallery | https://www.mathworks.com/help/signal/time-frequency-analysis.html | | Wavelet time-frequency | https://www.mathworks.com/help/wavelet/time-frequency-analysis.html | - Network accessline 190
| Time-frequency gallery | https://www.mathworks.com/help/signal/time-frequency-analysis.html | - Network accessline 191
| Wavelet time-frequency | https://www.mathworks.com/help/wavelet/time-frequency-analysis.html | - Network accessline 192
| CWT reference | https://www.mathworks.com/help/wavelet/ref/cwt.html | - Network accessline 193
| STFT reference | https://www.mathworks.com/help/signal/ref/stft.html | - Network accessline 194
| Synchrosqueezing example | https://www.mathworks.com/help/wavelet/ug/time-frequency-reassignment-and-mode-extraction-with-synchrosqueezing.html | - Network accessline 195
| Wavelet coherence example | https://www.mathworks.com/help/wavelet/ug/compare-time-frequency-content-in-signals-with-wavelet-coherence.html |
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/manifest.yaml
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/references/cross-analysis-guide.md
- Network accessline 238
| Topic | Link | |-------|------| | `wcoherence` reference | https://www.mathworks.com/help/wavelet/ref/wcoherence.html | - Network accessline 239
|-------|------| | `wcoherence` reference | https://www.mathworks.com/help/wavelet/ref/wcoherence.html | | `xspectrogram` reference | https://www.mathworks.com/help/signal/ref/xspectrogram.html | - Network accessline 240
| `wcoherence` reference | https://www.mathworks.com/help/wavelet/ref/wcoherence.html | - Network accessline 241
| `xspectrogram` reference | https://www.mathworks.com/help/signal/ref/xspectrogram.html | - Network accessline 242
| `cpsd` reference | https://www.mathworks.com/help/signal/ref/cpsd.html | - Network accessline 243
| `mscohere` reference | https://www.mathworks.com/help/signal/ref/mscohere.html | - Network accessline 244
| Wavelet coherence example | https://www.mathworks.com/help/wavelet/ug/compare-time-frequency-content-in-signals-with-wavelet-coherence.html | - Network accessline 245
| Seismic velocity changes via coherence | https://www.mathworks.com/help/wavelet/ug/relative-velocity-changes-in-seismic-waves-using-time-frequency-analysis.html |
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/references/cwt-guide.md
- Network accessline 460
| Topic | Link | |-------|------| | `cwt` function reference | https://www.mathworks.com/help/wavelet/ref/cwt.html | - Network accessline 461
|-------|------| | `cwt` function reference | https://www.mathworks.com/help/wavelet/ref/cwt.html | | `cwtfilterbank` reference | https://www.mathworks.com/help/wavelet/ref/cwtfilterbank.html | - Network accessline 462
| `cwt` function reference | https://www.mathworks.com/help/wavelet/ref/cwt.html | - Network accessline 463
| `cwtfilterbank` reference | https://www.mathworks.com/help/wavelet/ref/cwtfilterbank.html | - Network accessline 464
| `icwt` function reference | https://www.mathworks.com/help/wavelet/ref/icwt.html | - Network accessline 465
| Practical introduction to CWT | https://www.mathworks.com/help/wavelet/ug/practical-introduction-to-time-frequency-analysis-using-the-continuous-wavelet-transform.html | - Network accessline 466
| Morse wavelet family | https://www.mathworks.com/help/wavelet/ug/morse-wavelets.html |
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/references/reassignment-guide.md
- Network accessline 255
| Topic | Link | |-------|------| | `fsst` reference | https://www.mathworks.com/help/signal/ref/fsst.html | - Network accessline 256
|-------|------| | `fsst` reference | https://www.mathworks.com/help/signal/ref/fsst.html | | `ifsst` reference | https://www.mathworks.com/help/signal/ref/ifsst.html | - Network accessline 257
| `fsst` reference | https://www.mathworks.com/help/signal/ref/fsst.html | - Network accessline 258
| `ifsst` reference | https://www.mathworks.com/help/signal/ref/ifsst.html | - Network accessline 259
| `tfridge` reference | https://www.mathworks.com/help/signal/ref/tfridge.html | - Network accessline 260
| `wsst` reference | https://www.mathworks.com/help/wavelet/ref/wsst.html | - Network accessline 261
| `iwsst` reference | https://www.mathworks.com/help/wavelet/ref/iwsst.html | - Network accessline 262
| `wsstridge` reference | https://www.mathworks.com/help/wavelet/ref/wsstridge.html | - Network accessline 263
| Time-frequency reassignment and mode extraction | https://www.mathworks.com/help/wavelet/ug/time-frequency-reassignment-and-mode-extraction-with-synchrosqueezing.html |
skills-catalog/signal-processing/matlab-analyze-time-frequency-content/references/stft-guide.md
- Network accessline 350
For a visual comparison of all time-frequency methods (STFT, CWT, Wigner-Ville, synchrosqueezing, constant-Q, data-adaptive MRA), see the [Time-Frequency Gallery](https://www.mathworks.com/help/signal/ug/time-frequency-gallery.html).
skills-catalog/signal-processing/matlab-configure-scope-object/SKILL.md
- Network accessline 2
name: matlab-configure-scope-object description: Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks - Network accessline 3
description: Prevents crashes due to problematic scope-related API misuse caused by agent escalation into internal scope framework objects. Use when configuring properties of scope-related Simulink blocks or MATLAB objects — constrains the - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-configure-scope-object/manifest.yaml
skills-catalog/signal-processing/matlab-design-adaptive-filter/SKILL.md
- Network accessline 10
and algorithm selection for adaptive filtering problems. Replaces deprecated adaptfilt.* objects (removed R2020a). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
adaptfilt.* objects (removed R2020a). license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2024b" - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-design-adaptive-filter/manifest.yaml
skills-catalog/signal-processing/matlab-design-digital-filter/SKILL.md
- Network accessline 5
removing interference, filtering signals, designing FIR/IIR filters (lowpass/highpass/bandpass/bandstop/notch), or comparing filters in Filter Analyzer. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 6
(lowpass/highpass/bandpass/bandstop/notch), or comparing filters in Filter Analyzer. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 7
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-design-digital-filter/manifest.yaml
skills-catalog/signal-processing/matlab-design-dsphdl-ddc/SKILL.md
- Network accessline 2
name: matlab-design-dsphdl-ddc description: Use when designing a Digital Down Converter (DDC) using dsphdl System objects. Triggers on requests involving DDC design, frequency down-conversion for FPGA/ASIC, NCO + mixer + decimation filter c - Network accessline 3
description: Use when designing a Digital Down Converter (DDC) using dsphdl System objects. Triggers on requests involving DDC design, frequency down-conversion for FPGA/ASIC, NCO + mixer + decimation filter chains, fractional/non-integer s - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-design-dsphdl-ddc/manifest.yaml
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/SKILL.md
- Network accessline 11
quality or noise compliance. Covers calibration, standard selection, signal alignment, and the complete function inventory including what does NOT exist. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
alignment, and the complete function inventory including what does NOT exist. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 25
- Computing psychoacoustic metrics (loudness, sharpness, roughness, fluctuation) - Evaluating speech quality or intelligibility (ViSQOL, STOI, STI, SII) - Assessing noise compliance (NC rating, RC rating, RNC, SIL) - Network accessline 26
- Evaluating speech quality or intelligibility (ViSQOL, STOI, STI, SII) - Assessing noise compliance (NC rating, RC rating, RNC, SIL) - Measuring SPL from recordings (offline, calibrated) - Network accessline 27
- Assessing noise compliance (NC rating, RC rating, RNC, SIL) - Network accessline 64
- **Calibration:** Do they have a CalibrationFactor? Did they calibrate with `calibrateMicrophone`? (See Calibration section) - **Standard:** Which standard or method applies? (ISO 532-1 vs 532-2, NC vs RC vs RNC) - Network accessline 65
- **Standard:** Which standard or method applies? (ISO 532-1 vs 532-2, NC vs RC vs RNC) - Network accessline 67
- **Application context:** What space type? What's the concern? (Drives NC vs RC vs RNC selection) - Network accessline 98
| `stipaExcitation` | Generate STI/STIPA test signals | IEC 60268-16 | R2026a | | `siiExcitation` | Generate SII test signals | ANSI/ASA S3.5-1997 | R2026b | | `noiseCriteria` | NC rating + SIL + spectrum imbalance + rattle risk | ANSI/ASA - Network accessline 99
| `siiExcitation` | Generate SII test signals | ANSI/ASA S3.5-1997 | R2026b | | `noiseCriteria` | NC rating + SIL + spectrum imbalance + rattle risk | ANSI/ASA S12.2 | R2026b | | `roomNoiseCriteria` | RNC rating (detects surging/fluctuation - Network accessline 100
| `noiseCriteria` | NC rating + SIL + spectrum imbalance + rattle risk | ANSI/ASA S12.2 | R2026b | - Network accessline 101
| `roomNoiseCriteria` | RNC rating (detects surging/fluctuations) | ANSI/ASA S12.2 | R2026b | | `roomCriteria` | RC Mark II rating (HVAC systems) | ANSI/ASA S12.2 | R2026b | | `noiseCriteriaCurves` | Look up NC curve values | ANSI/ASA S12.2 - Network accessline 102
| `roomCriteria` | RC Mark II rating (HVAC systems) | ANSI/ASA S12.2 | R2026b | | `noiseCriteriaCurves` | Look up NC curve values | ANSI/ASA S12.2 | R2026b | | `noiseCriteriaRecommendations` | Recommended NC levels by room type | ANSI/ASA S - Network accessline 103
| `noiseCriteriaCurves` | Look up NC curve values | ANSI/ASA S12.2 | R2026b | - Network accessline 104
| `noiseCriteriaRecommendations` | Recommended NC levels by room type | ANSI/ASA S12.2 | R2026b | - Network accessline 191
| Situation | Function | Why | |-----------|----------|-----| | General background noise rating | `noiseCriteria` | Standard NC curves (ANSI/ASA S12.2) | - Network accessline 192
|-----------|----------|-----| | General background noise rating | `noiseCriteria` | Standard NC curves (ANSI/ASA S12.2) | | HVAC system noise specifically | `roomCriteria` | RC Mark II designed for HVAC evaluation | - Network accessline 193
| General background noise rating | `noiseCriteria` | Standard NC curves (ANSI/ASA S12.2) | - Network accessline 216
- `SIL` and `LMF` are double scalars (dB) - `QAI` is a double scalar (dB; 0 = ideal neutral) - `specImbalance` and `rattleRisk` are structs with `.Summary` (string) and `.Details` (table) — access `.Summary` for display. **Exception:** `spe - Network accessline 217
- `QAI` is a double scalar (dB; 0 = ideal neutral) - `specImbalance` and `rattleRisk` are structs with `.Summary` (string) and `.Details` (table) — access `.Summary` for display. **Exception:** `specImbalance` degrades to a `char` scalar (n - Network accessline 218
- `specImbalance` and `rattleRisk` are structs with `.Summary` (string) and `.Details` (table) — access `.Summary` for display. **Exception:** `specImbalance` degrades to a `char` scalar (not a struct) when NC exceeds the curve range (e.g., - Network accessline 405
| `stoi(reference, processed, fs)` | Wrong argument order | `stoi(processed, reference, fs)` — processed FIRST | | `acousticFluctuationStrength(...)` | Wrong function name | `acousticFluctuation(audioIn, fs, calFactor)` | | Implement NC fro - Network accessline 406
| `acousticFluctuationStrength(...)` | Wrong function name | `acousticFluctuation(audioIn, fs, calFactor)` | | Implement NC from scratch with hardcoded curves | Misses SIL, spectrum imbalance, rattle risk | `noiseCriteria(audioIn, fs, Calib - Network accessline 407
| Implement NC from scratch with hardcoded curves | Misses SIL, spectrum imbalance, rattle risk | `noiseCriteria(audioIn, fs, CalibrationFactor=cf)` | - Network accessline 412
| Use `acousticLoudness` for broadcast loudness | Wrong standard (ISO 532 = sones, not LUFS) | `integratedLoudness` for EBU R 128 compliance | | `string(rattleRisk)` or `fprintf("%s", specImbalance)` | These are structs, not strings | Acces - Network accessline 413
| `string(rattleRisk)` or `fprintf("%s", specImbalance)` | These are structs, not strings | Access `.Summary` field: `rattleRisk.Summary` | | `specImbalance.Summary` when NC is out of curve range | `specImbalance` degrades to `char` (not st - Network accessline 414
| `specImbalance.Summary` when NC is out of curve range | `specImbalance` degrades to `char` (not struct) when "Above NC-70" or below NC-15 | Guard: `if isstruct(specImbalance), disp(specImbalance.Summary); end` | - Network accessline 415
| `roomNoiseCriteria` on recordings shorter than 15 s | ANSI/ASA S12.2-2019 requires ≥150 Lt samples at 100 ms intervals | Ensure recording is at least 15 seconds; use `noiseCriteria` for shorter clips | | `round(NC)` or arithmetic on NC/RC - Network accessline 416
| `round(NC)` or arithmetic on NC/RC output | NC and RC are strings, not numbers | Use directly: `fprintf("%s\n", NC)` |
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/manifest.yaml
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/references/noise-compliance.md
- Network accessline 11
| HVAC (fans, ducts, diffusers) | Use `roomCriteria` for spectral quality; `noiseCriteria` for compliance | | Variable-speed drives or cycling equipment | Use `roomNoiseCriteria` — fluctuation penalty likely applies | | General background ( - Network accessline 12
| Variable-speed drives or cycling equipment | Use `roomNoiseCriteria` — fluctuation penalty likely applies | | General background (multiple sources) | Use `noiseCriteria` for a standard NC rating | | Unknown / complaint investigation | Run - Network accessline 13
| General background (multiple sources) | Use `noiseCriteria` for a standard NC rating | - Network accessline 30
NC and RNC share the same recommendation targets — use RNC in place of NC when temporal variation is a concern. RC targets are from a separate table with different occupancy categories. - Network accessline 36
- **Steady:** NC or RC is sufficient - Network accessline 37
- **Fluctuating (surging, throbbing, cycling):** Use `roomNoiseCriteria` — it penalizes temporal variation that NC misses. RNC ≥ NC always (RNC is stricter). If RNC significantly exceeds NC, the fluctuation is the problem. - Network accessline 44
| Simple compliance check against spec | `noiseCriteria` → compare to target | | Diagnose spectral problems in HVAC | `roomCriteria` → read QAI and classification | | Investigate occupant complaints | Run all three; compare NC vs RNC for fl - Network accessline 45
| Diagnose spectral problems in HVAC | `roomCriteria` → read QAI and classification | | Investigate occupant complaints | Run all three; compare NC vs RNC for fluctuation penalty | | Set design targets for new construction | `noiseCriteriaR - Network accessline 46
| Investigate occupant complaints | Run all three; compare NC vs RNC for fluctuation penalty | - Network accessline 62
| Function | Standard | Best For | Key Outputs | |----------|----------|----------|-------------| | `noiseCriteria` | ANSI/ASA S12.2-2019 (NC) | General background noise assessment | NC level, SIL, spectrum imbalance, rattle risk | - Network accessline 63
|----------|----------|----------|-------------| | `noiseCriteria` | ANSI/ASA S12.2-2019 (NC) | General background noise assessment | NC level, SIL, spectrum imbalance, rattle risk | | `roomNoiseCriteria` | ANSI/ASA S12.2-2019 (RNC) | Noise - Network accessline 64
| `noiseCriteria` | ANSI/ASA S12.2-2019 (NC) | General background noise assessment | NC level, SIL, spectrum imbalance, rattle risk | - Network accessline 66
| `roomCriteria` | ANSI/ASA S12.2-2019 (RC Mark II) | HVAC system noise evaluation | RC level, LMF, QAI, rattle risk | | `speechInterferenceLevel` | ANSI/ASA S12.65-2006 | Quick speech interference check | SIL value (dB) | | `noiseCriteriaC - Network accessline 67
| `speechInterferenceLevel` | ANSI/ASA S12.65-2006 | Quick speech interference check | SIL value (dB) | | `noiseCriteriaCurves` | ANSI/ASA S12.2-2019 | Look up NC curve SPL values | SPL values at octave bands for given NC level | | `noiseCr - Network accessline 68
| `noiseCriteriaCurves` | ANSI/ASA S12.2-2019 | Look up NC curve SPL values | SPL values at octave bands for given NC level | - Network accessline 84
- `NC` — NC level as string (e.g., `"NC-35"`) - Network accessline 85
- `SIL` — Speech interference level (average of 500/1k/2k/4k Hz bands) - `spectrumImbalance` — Structure with `Summary` (string) and `Details` (table showing deviation from reference NC curve per band) - `rattleRisk` — Structure with `Summa - Network accessline 86
- `spectrumImbalance` — Structure with `Summary` (string) and `Details` (table showing deviation from reference NC curve per band) - Network accessline 119
Use when the noise has audible temporal variation (surging, random fluctuations). RNC is a stricter criterion than NC — it penalizes unsteady noise. Returns 2 outputs (not 4 like `noiseCriteria`): - Network accessline 191
**Edge case:** `specImbalance` degrades to a plain `char` string (not a struct) when NC exceeds the curve range (e.g., "Above NC-70") or falls below NC-15 — spectrum imbalance is undefined in both cases. Always guard before dot-indexing: - Network accessline 213
### NC Rating Interpretation - Network accessline 215
The NC algorithm: compute SIL (average of 500/1k/2k/4k Hz bands) → select the NC curve corresponding to that SIL value → check if any measured bands exceed that curve → if so, apply the tangency method and append the tangent frequency. - Network accessline 217
Output formats: - `"NC-35"` — SIL-based rating; no band exceeds the SIL-selected curve - `"NC-42 (1000 Hz)"` — Tangency method drove the rating; the noted band exceeds the SIL-selected NC curve. This indicates spectral imbalance at that fre - Network accessline 218
- `"NC-35"` — SIL-based rating; no band exceeds the SIL-selected curve - `"NC-42 (1000 Hz)"` — Tangency method drove the rating; the noted band exceeds the SIL-selected NC curve. This indicates spectral imbalance at that frequency. - `"Belo - Network accessline 219
- `"NC-42 (1000 Hz)"` — Tangency method drove the rating; the noted band exceeds the SIL-selected NC curve. This indicates spectral imbalance at that frequency. - Network accessline 222
The output is always an integer NC value. When the tangency-based NC exceeds the SIL-based NC by more than 3 dB, the spectrum has an imbalance. Check `specImbalance.Details` to see which bands deviate from the reference curve. - Network accessline 238
### RNC vs NC — Diagnosing Fluctuation - Network accessline 240
When RNC significantly exceeds NC for the same recording, the noise has temporal variation causing additional annoyance. The larger the difference, the more the temporal variation contributes to the overall noise problem. - Network accessline 260
| Observation | Likely Cause | Action | |-------------|-------------|--------| | NC seems fine but occupants complain | Noise fluctuates — NC averages away the annoyance | Run `roomNoiseCriteria` to quantify fluctuation penalty | - Network accessline 261
|-------------|-------------|--------| | NC seems fine but occupants complain | Noise fluctuates — NC averages away the annoyance | Run `roomNoiseCriteria` to quantify fluctuation penalty | | NC exceeds target by 1–2 dB | One band drives ta - Network accessline 262
| NC seems fine but occupants complain | Noise fluctuates — NC averages away the annoyance | Run `roomNoiseCriteria` to quantify fluctuation penalty | - Network accessline 263
| NC exceeds target by 1–2 dB | One band drives tangency while SIL is within target | Check `specImbalance.Details` — treatment may be needed in one band only | - Network accessline 264
| RC shows "(RV)" | Severe low-frequency excess at 16 or 31.5 Hz | Do not attempt to mask with absorption — isolate the vibration source | | RNC errors on short recording | Surging or fluctuation detected but recording under 15 s (correctio - Network accessline 265
| RNC errors on short recording | Surging or fluctuation detected but recording under 15 s (correction needs 150 samples) | Re-record ≥15 s, or set `IsSurging=false, IsFluctuating=false` to bypass correction (result will not account for tem - Network accessline 266
| NC/RC ratings differ significantly | They use different band ranges (NC: 63–8kHz, RC: 16–4kHz) and methods | Normal; RC captures low-frequency problems NC misses |
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/references/spl-measurement.md
- Network accessline 175
### Scenario: Background Noise Survey for NC Rating
skills-catalog/signal-processing/matlab-evaluate-acoustic-metrics/references/sti-measurement.md
- Network accessline 40
These significantly affect the result -- ask about: - **Ambient noise level:** What NC rating (or octave-band levels) is expected during normal operation? Default is NC-35. Changing from NC-25 to NC-45 can reduce STI by 0.10-0.20. - Network accessline 41
- **Ambient noise level:** What NC rating (or octave-band levels) is expected during normal operation? Default is NC-35. Changing from NC-25 to NC-45 can reduce STI by 0.10-0.20. - Network accessline 140
**Ask the user about:** - What is the expected operational noise level? (NC rating or octave-band levels) - Network accessline 141
- What is the expected operational noise level? (NC rating or octave-band levels)
skills-catalog/signal-processing/matlab-extract-signal-features/SKILL.md
- Network accessline 15
audio-specific feature extraction (use audioFeatureExtractor in Audio Toolbox instead), batch dataset orchestration, or 2D / image features. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 16
Toolbox instead), batch dataset orchestration, or 2D / image features. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 17
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-extract-signal-features/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-extract-signal-features/references/gpu-patterns.md
- Network accessline 107
For more information, see [Run MATLAB Functions on a GPU](https://www.mathworks.com/help/parallel-computing/run-matlab-functions-on-a-gpu.html) (Parallel Computing Toolbox).
skills-catalog/signal-processing/matlab-play-record-audio/SKILL.md
- Network accessline 2
name: matlab-play-record-audio description: Reference for MATLAB audiostreamer (Audio Toolbox R2025a+). Without this skill, agents consistently default to legacy audioDeviceWriter/audioDeviceReader or base MATLAB sound(), producing less cap - Network accessline 3
description: Reference for MATLAB audiostreamer (Audio Toolbox R2025a+). Without this skill, agents consistently default to legacy audioDeviceWriter/audioDeviceReader or base MATLAB sound(), producing less capable code. Use when writing cod - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-play-record-audio/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-prepare-signal-data/SKILL.md
- Network accessline 17
`signalDatastore`, `labeledSignalSet`, `filenames2labels`, `folders2labels`, `splitlabels`, `framesig`, `framelbl`, `createDatastores`. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 18
`splitlabels`, `framesig`, `framelbl`, `createDatastores`. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 19
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-prepare-signal-data/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-prepare-signal-data/references/fn-signaldatastore.md
skills-catalog/signal-processing/matlab-process-streaming-audio/SKILL.md
- Network accessline 14
"MIDI control", "convolution reverb", "impulse response streaming", "frequency-domain filter", or asks to process audio frame-by-frame. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
"frequency-domain filter", or asks to process audio frame-by-frame. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-process-streaming-audio/manifest.yaml
skills-catalog/signal-processing/matlab-write-audio-plugin/SKILL.md
- Network accessline 6
or generator plugins, writing classdef files inheriting from audioPlugin, or troubleshooting validateAudioPlugin failures. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 7
validateAudioPlugin failures. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 8
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/signal-processing/matlab-write-audio-plugin/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-build-industrial-hmi/SKILL.md
- Network accessline 15
setpoint, write safeguards, alarm visualization, OSIsoft PI, AVEVA PI, PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 16
PI Server, PI Data Archive, PI AF, PI Asset Framework, piclient, afclient. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 17
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-build-industrial-hmi/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-call-nidaqmx/SKILL.md
- Network accessline 13
shared timebase, export signal, connect terminals, external sample clock, trigger configuration, NI driver, C function translation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 14
trigger configuration, NI driver, C function translation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2026a" - Network accessline 15
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-call-nidaqmx/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-connect-arduino/SKILL.md
- Network accessline 14
readDigitalPin, writeDigitalPin, readVoltage, writePWMVoltage, temperature sensor, air pressure, pin read, pin write, analog input. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
temperature sensor, air pressure, pin read, pin write, analog input. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 97
`arduino` object, restart MATLAB and reconnect - For detailed troubleshooting, refer the user to: https://www.mathworks.com/help/matlab/supportpkg/arduino-connection-failure.html - Network accessline 98
- For detailed troubleshooting, refer the user to: https://www.mathworks.com/help/matlab/supportpkg/arduino-connection-failure.html 4. **STOP and wait.** Do not proceed to Step 2 or beyond until the user - Network accessline 99
https://www.mathworks.com/help/matlab/supportpkg/arduino-connection-failure.html - Instruction override signalline 108
Serial port names alone do not tell the user what device is connected.
skills-catalog/test-and-measurement/matlab-connect-arduino/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-connect-bluetooth-low-energy-device/SKILL.md
- Network accessline 11
service UUID, scan for devices, BLE sensor, subscribe notify, BLE read, BLE write, peripheral device, BLE connect, wireless sensor. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
BLE write, peripheral device, BLE connect, wireless sensor. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-connect-bluetooth-low-energy-device/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-create-custom-arduino-library/SKILL.md
- Network accessline 10
class, C++ header files, DependentLibraries, arduinoioaddons namespace, I2C/SPI/GPIO peripheral wrappers. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
peripheral wrappers. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 93
arduinoio.customLibrary.downloadLibrary("DHT22") arduinoio.customLibrary.downloadLibrary("U8g2") arduinoio.customLibrary.downloadLibrary("https://github.com/olikraus/u8g2") - Network accessline 95
arduinoio.customLibrary.downloadLibrary("https://github.com/olikraus/u8g2")
skills-catalog/test-and-measurement/matlab-create-custom-arduino-library/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-discover-hardware/SKILL.md
- Network accessline 2
name: matlab-discover-hardware description: "Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device - Network accessline 3
description: "Discovers connected MATLAB-supported hardware devices, searches by capability, and checks required support packages and add-ons. Use when the user asks what hardware is connected, finds a device that supports a capability (e.g - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-discover-hardware/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-enhance-camera-image/SKILL.md
- Network accessline 10
a user wants to improve camera image quality, troubleshoot dark/blurry/noisy/grainy/ overexposed/washed out/color cast images, or optimize camera settings. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
overexposed/washed out/color cast images, or optimize camera settings. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-enhance-camera-image/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-find-pi-assets/SKILL.md
- Network accessline 8
tags, asset hierarchies, element templates, attribute lookup, or historical data from OSIsoft PI systems. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 9
OSIsoft PI systems. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 10
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-find-pi-assets/manifest.yaml
skills-catalog/test-and-measurement/matlab-import-export-vehicle-data/SKILL.md
- Network accessline 2
name: matlab-import-export-vehicle-data description: Use when importing or exporting vehicle data from/to log files (MDF/MF4/DAT, BLF, ASC/TXT), decoding CAN/CAN FD/LIN messages to signals via DBC, ARXML, or LDF databases, writing timetable - Network accessline 3
description: Use when importing or exporting vehicle data from/to log files (MDF/MF4/DAT, BLF, ASC/TXT), decoding CAN/CAN FD/LIN messages to signals via DBC, ARXML, or LDF databases, writing timetable data to MDF or BLF files, or calling bl - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-import-export-vehicle-data/manifest.yaml
skills-catalog/test-and-measurement/matlab-modernize-daq/SKILL.md
- Network accessline 14
queueOutputData, DataAvailable, evt.Data, evt.TimeStamps, wait(d), preload, discouraged, legacy, modernize, R2020a. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 15
discouraged, legacy, modernize, R2020a. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 16
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-modernize-daq/manifest.yaml
skills-catalog/test-and-measurement/matlab-modernize-daq/references/session-to-modern-mapping.md
- Network accessline 3
The official MathWorks transition guide — [Transition Your Code from the Session-Based Interface to the DataAcquisition Interface](https://www.mathworks.com/help/daq/transition-your-code-from-session-to-dataacquisition-interface.html) — is
skills-catalog/test-and-measurement/matlab-use-cameras/SKILL.md
- Network accessline 10
Always prefer videoinput from Image Acquisition Toolbox over webcam support package or gigecam. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
package or gigecam. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-use-cameras/manifest.yaml
skills-catalog/test-and-measurement/matlab-use-cameras/references/gentl-setup.md
- Network accessline 14
For detailed setup instructions on obtaining and configuring the correct GenTL producer for your camera, refer to: https://www.mathworks.com/matlabcentral/answers/2089171-how-can-i-use-my-gige-vision-or-usb3-vision-camera-in-matlab - Network accessline 15
https://www.mathworks.com/matlabcentral/answers/2089171-how-can-i-use-my-gige-vision-or-usb3-vision-camera-in-matlab
skills-catalog/test-and-measurement/matlab-use-opcua-client/SKILL.md
- Network accessline 17
findNodeById, opcuanode, browse OPC UA, find node, OPC UA namespace, OPC UA method node, Industrial Communication Toolbox. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 18
OPC UA method node, Industrial Communication Toolbox. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 19
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-use-opcua-client/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-use-vehicle-network/SKILL.md
- Network accessline 2
name: matlab-use-vehicle-network description: Use when setting up vehicle network communication in MATLAB using Vehicle Network Toolbox. Covers CAN/CAN FD (fully implemented), with architecture for J1939, XCP, and future protocols. Handles - Network accessline 3
description: Use when setting up vehicle network communication in MATLAB using Vehicle Network Toolbox. Covers CAN/CAN FD (fully implemented), with architecture for J1939, XCP, and future protocols. Handles hardware discovery, channel creat - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-use-vehicle-network/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/test-and-measurement/matlab-use-vehicle-network/references/shared/limitations.md
skills-catalog/wireless-communications/matlab-add-awgn/SKILL.md
- Network accessline 2
name: matlab-add-awgn description: "Read BEFORE writing any code that adds Additive White Gaussian Noise (AWGN) to signals and converts between SNR, Eb/No, Es/No, and per-subcarrier SNR for communications simulations, using awgn(), convertS - Network accessline 3
description: "Read BEFORE writing any code that adds Additive White Gaussian Noise (AWGN) to signals and converts between SNR, Eb/No, Es/No, and per-subcarrier SNR for communications simulations, using awgn(), convertSNR(), berawgn(). The d - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-add-awgn/manifest.yaml
skills-catalog/wireless-communications/matlab-add-awgn/references/snr-conversion-guide.md
- Network accessline 15
All other conversions (Eb/No↔Es/No, Eb/No↔SNR, Es/No↔SNR) are handled by `convertSNR` (available since R2022a). Always use `convertSNR` — never compute these manually. For details, refer to the [`convertSNR` documentation](https://www.mathw
skills-catalog/wireless-communications/matlab-design-ofdm-system/SKILL.md
- Network accessline 2
name: matlab-design-ofdm-system description: "Read BEFORE writing any code that builds or simulates OFDM systems. The default MATLAB patterns for OFDM (e.g., direct ifft/fft, awgn with 0 dBW power, missing symOffset) produce subtly incorrec - Network accessline 3
description: "Read BEFORE writing any code that builds or simulates OFDM systems. The default MATLAB patterns for OFDM (e.g., direct ifft/fft, awgn with 0 dBW power, missing symOffset) produce subtly incorrect results — always use ofdmmod/o - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-design-ofdm-system/manifest.yaml
- Network accessline 1
# Copyright 2026 The MathWorks, Inc. schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 2
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: product-specific - Network accessline 3
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-detect-capture-usrp/SKILL.md
- Network accessline 2
name: matlab-detect-capture-usrp description: Smart triggered RF capture on NI USRP radios with Wireless Testbench — record only when a signal of interest appears, not continuously (triggered spectrum sensing). Use energy detection to captu - Network accessline 3
description: Smart triggered RF capture on NI USRP radios with Wireless Testbench — record only when a signal of interest appears, not continuously (triggered spectrum sensing). Use energy detection to capture when signal power rises above - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-detect-capture-usrp/manifest.yaml
skills-catalog/wireless-communications/matlab-generate-5g-waveform/SKILL.md
- Network accessline 11
TDD, FDD, and multi-bandwidth-part setups. Use for signal generation, RF instrument playback, or IQ baseband synthesis. Requires 5G Toolbox. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
instrument playback, or IQ baseband synthesis. Requires 5G Toolbox. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-generate-5g-waveform/manifest.yaml
skills-catalog/wireless-communications/matlab-generate-5g-waveform/references/documentation-links.md
- Network accessline 5
- [nrWaveformGenerator](https://mathworks.com/help/5g/ref/nrwaveformgenerator.html) — Generate 5G NR waveform - Network accessline 6
- [5G Waveform Generator app](https://mathworks.com/help/5g/ref/5gwaveformgenerator-app.html) — Interactive waveform generation GUI - Network accessline 10
- [nrDLCarrierConfig](https://mathworks.com/help/5g/ref/nrdlcarrierconfig.html) — Downlink carrier configuration - Network accessline 11
- [nrULCarrierConfig](https://mathworks.com/help/5g/ref/nrulcarrierconfig.html) — Uplink carrier configuration - Network accessline 12
- [nrSCSCarrierConfig](https://mathworks.com/help/5g/ref/nrscscarrierconfig.html) — SCS carrier configuration - Network accessline 16
- [nrWavegenBWPConfig](https://mathworks.com/help/5g/ref/nrwavegenbwpconfig.html) — Bandwidth part configuration - Network accessline 17
- [nrWavegenPDSCHConfig](https://mathworks.com/help/5g/ref/nrwavegenpdschconfig.html) — PDSCH configuration for waveform generation - Network accessline 18
- [nrWavegenPUSCHConfig](https://mathworks.com/help/5g/ref/nrwavegenpuschconfig.html) — PUSCH configuration for waveform generation - Network accessline 19
- [nrWavegenPDCCHConfig](https://mathworks.com/help/5g/ref/nrwavegenpdcchconfig.html) — PDCCH configuration for waveform generation - Network accessline 20
- [nrWavegenSSBurstConfig](https://mathworks.com/help/5g/ref/nrwavegenssburstconfig.html) — SS burst configuration - Network accessline 21
- [nrWavegenCSIRSConfig](https://mathworks.com/help/5g/ref/nrwavegencsirsconfig.html) — CSI-RS configuration - Network accessline 22
- [nrCORESETConfig](https://mathworks.com/help/5g/ref/nrcoresetconfig.html) — CORESET configuration - Network accessline 23
- [nrSearchSpaceConfig](https://mathworks.com/help/5g/ref/nrsearchspaceconfig.html) — Search space configuration - Network accessline 27
- [5G NR TM Waveform Generation (example)](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html) — hNRReferenceWaveformGenerator usage and source - Network accessline 31
- [5G NR Downlink Carrier Waveform Generation](https://mathworks.com/help/5g/ug/downlink-carrier-waveform-generation.html) - Network accessline 32
- [5G NR Uplink Carrier Waveform Generation](https://mathworks.com/help/5g/ug/uplink-carrier-waveform-generation.html) - Network accessline 33
- [EVM Measurement of 5G NR Downlink Waveforms](https://mathworks.com/help/5g/ug/evm-measurement-of-5g-nr-downlink-waveforms.html) - Network accessline 34
- [5G NR Downlink ACLR Measurement](https://mathworks.com/help/5g/ug/nr-downlink-ACLR-measurement.html)
skills-catalog/wireless-communications/matlab-generate-5g-waveform/references/test-models-and-frc.md
- Network accessline 4
(TM) and fixed reference channel (FRC) waveforms. This is an example helper shipped with 5G Toolbox (see the [5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html) - Network accessline 5
shipped with 5G Toolbox (see the [5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html) example). - Network accessline 6
[5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html) - Network accessline 144
- **Function does not exist:** If `hNRReferenceWaveformGenerator` is not found, open the example first: [5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html). - Network accessline 145
open the example first: [5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html). This adds the helper to the MATLAB path. - Network accessline 146
[5G NR TM Waveform Generation](https://mathworks.com/help/5g/ug/5g-nr-tm-waveform-generation.html).
skills-catalog/wireless-communications/matlab-generate-ble-waveform/SKILL.md
- Network accessline 7
bleAngleEstimate, bluetoothTestWaveform for LE1M/LE2M/LE500K/LE125K. Bluetooth Toolbox R2022a+. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 8
Bluetooth Toolbox R2022a+. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2022a" - Network accessline 9
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-generate-ble-waveform/manifest.yaml
skills-catalog/wireless-communications/matlab-generate-gnss-waveform/SKILL.md
- Network accessline 12
satellite scenario, GNSS simulation, receiver test signal, baseband GNSS, L-band satellite signal, navigation signal generation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 13
L-band satellite signal, navigation signal generation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2026a" - Network accessline 14
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-generate-gnss-waveform/manifest.yaml
skills-catalog/wireless-communications/matlab-generate-gnss-waveform/references/navic-pipeline.md
- Network accessline 78
~exist('NavICL1LDPCParityCheckMatrixIndices.mat','file') if ~exist('L1Dataset.zip','file') url = 'https://ssd.mathworks.com/supportfiles/spc/satcom/NavIC/L1Dataset.zip'; - Network accessline 79
if ~exist('L1Dataset.zip','file') url = 'https://ssd.mathworks.com/supportfiles/spc/satcom/NavIC/L1Dataset.zip'; websave('L1Dataset.zip', url); - Network accessline 80
url = 'https://ssd.mathworks.com/supportfiles/spc/satcom/NavIC/L1Dataset.zip'; - Network accessline 90
**Terms of Use:** The NavIC L1 PRN codes and LDPC matrices are governed by the [NavIC ICD Terms of Use](https://ssd.mathworks.com/supportfiles/spc/satcom/NavIC/TermsOfUse.pdf). - Network accessline 91
the [NavIC ICD Terms of Use](https://ssd.mathworks.com/supportfiles/spc/satcom/NavIC/TermsOfUse.pdf).
skills-catalog/wireless-communications/matlab-generate-wlan-waveform/SKILL.md
- Network accessline 11
configure OFDMA resource units, build trigger-based uplink transmissions, target a specific transmit duration, or build multi-packet waveforms. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 12
target a specific transmit duration, or build multi-packet waveforms. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 13
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 492
| **VHT GroupID** | 0/63 = SU. 1-62 = MU-MIMO. Silently accepts wrong values. | | **`wlanAPEPLength` is SU-only** | Works for VHT-SU, HE-SU, and EHT-MU single-user (non-OFDMA). Errors on any MU/OFDMA config — use iterative `transmitTime` lo - Network accessline 494
| **Do not fabricate IEEE versions** | Direct the user to the [WLAN Toolbox Release Notes](https://mathworks.com/help/wlan/release-notes.html). |
skills-catalog/wireless-communications/matlab-generate-wlan-waveform/manifest.yaml
skills-catalog/wireless-communications/matlab-generate-wlan-waveform/references/documentation-links.md
- Network accessline 5
- [wlanWaveformGenerator](https://mathworks.com/help/wlan/ref/wlanwaveformgenerator.html) — Generate WLAN waveform - Network accessline 6
- [wlanSampleRate](https://mathworks.com/help/wlan/ref/wlansamplerate.html) — Get sample rate for config - Network accessline 10
- [wlanNonHTConfig](https://mathworks.com/help/wlan/ref/wlannonhtconfig.html) — Non-HT (802.11a/g/b) - Network accessline 11
- [wlanHTConfig](https://mathworks.com/help/wlan/ref/wlanhtconfig.html) — HT (802.11n) - Network accessline 12
- [wlanVHTConfig](https://mathworks.com/help/wlan/ref/wlanvhtconfig.html) — VHT (802.11ac) - Network accessline 13
- [wlanHESUConfig](https://mathworks.com/help/wlan/ref/wlanhesuconfig.html) — HE-SU (802.11ax) - Network accessline 14
- [wlanHEMUConfig](https://mathworks.com/help/wlan/ref/wlanhemuconfig.html) — HE-MU OFDMA/MU-MIMO (802.11ax) - Network accessline 15
- [wlanHETBConfig](https://mathworks.com/help/wlan/ref/wlanhetbconfig.html) — HE trigger-based uplink (802.11ax) - Network accessline 16
- [wlanEHTMUConfig](https://mathworks.com/help/wlan/ref/wlanehtmuconfig.html) — EHT-MU OFDMA/MU-MIMO (802.11be) - Network accessline 17
- [wlanEHTTBConfig](https://mathworks.com/help/wlan/ref/wlanehttbconfig.html) — EHT trigger-based uplink (802.11be) - Network accessline 24
- [wlanMACFrame](https://mathworks.com/help/wlan/ref/wlanmacframe.html) — Generate MAC frame bits - Network accessline 25
- [wlanMACFrameConfig](https://mathworks.com/help/wlan/ref/wlanmacframeconfig.html) — MAC frame configuration - Network accessline 26
- [wlanMSDULengths](https://mathworks.com/help/wlan/ref/wlanmsdulengths.html) — Compute MSDU sizes for A-MPDU - Network accessline 30
- [wlanAPEPLength](https://mathworks.com/help/wlan/ref/wlanapeplength.html) — APEP length for target duration - Network accessline 31
- [wlanPSDULength](https://mathworks.com/help/wlan/ref/wlanpsdulength.html) — PSDU length for target duration - Network accessline 35
- [802.11ax Waveform Generation](https://mathworks.com/help/wlan/ug/802-11ax-waveform-generation.html) - Network accessline 36
- [802.11be Waveform Generation](https://mathworks.com/help/wlan/ug/802-11be-waveform-generation.html) - Network accessline 37
- [802.11ac Waveform Generation with MAC Frames](https://mathworks.com/help/wlan/ug/802-11ac-waveform-generation-with-mac-frames.html)
skills-catalog/wireless-communications/matlab-set-up-usrp-radio/SKILL.md
- Network accessline 10
USRP setup, radio not found, connection errors, dropped samples, or network configuration for SDR hardware. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
configuration for SDR hardware. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2026a" - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 39
- FPGA targeting or HDL workflows — check for a dedicated skill, or see [Target NI USRP Radios](https://www.mathworks.com/help/wireless-testbench/target-ni-usrp-devices.html) - Network accessline 40
- Generating or transmitting waveforms — check for a dedicated skill, or see [Transmit and Capture](https://www.mathworks.com/help/wireless-testbench/transmit-and-capture-RF-signals.html) - Network accessline 41
- Triggered (wake-on-signal) capture with preamble/energy detection — use the **matlab-detect-capture-usrp** skill - Multi-device synchronization — check for a dedicated skill, or see [Radio Management](https://www.mathworks.com/help/wirele - Network accessline 42
- Multi-device synchronization — check for a dedicated skill, or see [Radio Management](https://www.mathworks.com/help/wireless-testbench/radio-management.html) - Network accessline 158
Before running discovery, confirm with the user that the radio is powered on, cabled, and the Ethernet link LED is lit. E320 and N3xx devices take 30–60 seconds to boot after power-on — `findsdru` returns empty until the device finishes boo - Dangerous shell operationline 223
sudo ip addr add 192.168.10.1/24 dev <iface> - Dangerous shell operationline 224
sudo ip link set <iface> up - Dangerous shell operationline 227
sudo ip link set <iface> mtu 9000 - Dangerous shell operationline 230
sudo sysctl -w net.core.rmem_max=33554432 - Dangerous shell operationline 231
sudo sysctl -w net.core.wmem_max=33554432 - Network accessline 331
Create a `basebandTransceiver` to confirm the full pipeline works. The `basebandTransceiver` loads its own FPGA bitstream onto the device — do not use `sdruload` for streaming (that is the legacy `comm.SDRuReceiver` path). However, `sdruloa - Network accessline 405
- **Check versions early.** Compare `getSDRuDriverVersion` (host) with `probesdru` output (device) before proceeding. - **Diagnose before configuring.** Complete all host and radio checks before creating a radio configuration or launching t - Network accessline 407
- **Use release-specific doc URLs.** When linking to MathWorks docs, use `https://www.mathworks.com/help/releases/<release>/wireless-testbench/...` (derive `<release>` from `version('-release')`). This ensures docs match the user's installe
skills-catalog/wireless-communications/matlab-set-up-usrp-radio/manifest.yaml
- Network accessline 2
# manifest.yaml — Tooling metadata for matlab-set-up-usrp-radio schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-set-up-usrp-radio/references/troubleshooting.md
- Dangerous shell operationline 8
| `findsdru` returns empty | NIC interface is down | `sudo ip link set <iface> up` | - Network accessline 15
| Streaming drops samples | 1 GbE NIC with high sample rate | Reduce sample rate or upgrade to 10 GbE (E320 1G variant: max ~25 Msps complex) | | Streaming drops samples | Laptop on battery | Connect to power supply | | `OpTimeout` / `RFnoc - Network accessline 16
| Streaming drops samples | Laptop on battery | Connect to power supply | | `OpTimeout` / `RFnocError` | Data transfer rate too low | See [Resolve Issues with Data Transfer Rate](https://www.mathworks.com/help/wireless-testbench/ug/resolve- - Network accessline 17
| `OpTimeout` / `RFnocError` | Data transfer rate too low | See [Resolve Issues with Data Transfer Rate](https://www.mathworks.com/help/wireless-testbench/ug/resolve-issues-with-data-transfer-rate.html) | - Network accessline 50
See [Resolve Issues with Radio Setup Validation](https://www.mathworks.com/help/wireless-testbench/ug/resolve-issues-with-radio-setup-validation.html) for full details.
skills-catalog/wireless-communications/matlab-simulate-bluetooth-network/SKILL.md
- Network accessline 3
description: > Simulate Bluetooth system-level networks using the Bluetooth Toolbox. Use this skill for any Bluetooth topology: BLE ACL (Asynchronous Connection-Less) data connections, CIS (Connected Isochronous Stream) and LE Audio for - Network accessline 4
Simulate Bluetooth system-level networks using the Bluetooth Toolbox. Use this skill for any Bluetooth topology: BLE ACL (Asynchronous Connection-Less) data connections, CIS (Connected Isochronous Stream) and LE Audio for stereo speakers or - Network accessline 5
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-simulate-bluetooth-network/manifest.yaml
skills-catalog/wireless-communications/matlab-simulate-wireless-network/SKILL.md
- Network accessline 10
registering event callbacks on wireless nodes, accessing event data fields, or combining multiple capture/visualization tools in a simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
or combining multiple capture/visualization tools in a simulation. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md compatibility: ">=R2026a" - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
skills-catalog/wireless-communications/matlab-simulate-wireless-network/manifest.yaml
skills-catalog/wireless-communications/matlab-transmit-capture-usrp/SKILL.md
- Network accessline 10
Also use when the user mentions transmit waveform, capture signal, IQ data, loopback, RF gain, sample rate, or antenna configuration. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 11
loopback, RF gain, sample rate, or antenna configuration. license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md metadata: - Network accessline 12
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 33
- Setting up or connecting a USRP radio for the first time — use the **matlab-set-up-usrp-radio** skill - FPGA targeting workflows — see [Target NI USRP Radios](https://www.mathworks.com/help/wireless-testbench/target-ni-usrp-devices.html) - Network accessline 34
- FPGA targeting workflows — see [Target NI USRP Radios](https://www.mathworks.com/help/wireless-testbench/target-ni-usrp-devices.html) - Network accessline 36
- Multi-device synchronization — see [Radio Management](https://www.mathworks.com/help/wireless-testbench/radio-management.html)
skills-catalog/wireless-communications/matlab-transmit-capture-usrp/manifest.yaml
- Network accessline 2
# manifest.yaml — matlab-transmit-capture-usrp schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md - Network accessline 3
schema-version: 1 license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md scope: cross-product - Network accessline 4
license: https://www.mathworks.com/content/dam/mathworks/license/pmrl/license.md
How the signals fit together
Facts from a static read of the files at the pinned commit. They describe what the code does, not why.
Some files could not be read; the facts below still hold.
Declared and executed: 1 fact
- Allows Bash without restrictions, though it has no scripts or shell blocksmatlab-build-app/SKILL.md:18High confidence
Signal confidence: 499 facts
- Network access in the frontmatter of the SKILL.mdmatlab-compute-aerospace-environment/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-compute-aerospace-environment/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-compute-aerospace-environment/SKILL.md:13Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-convert-aerospace-coordinates/SKILL.md:11Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-convert-aerospace-coordinates/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-convert-aerospace-coordinates/SKILL.md:13Low confidence
- Network access in prose of documentationmatlab-convert-aerospace-coordinates/references/coordinate-systems.md:132Low confidence
- Network access in prose of documentationmatlab-convert-aerospace-coordinates/references/coordinate-systems.md:133Low confidence
- Network access in prose of documentationmatlab-convert-aerospace-coordinates/references/coordinate-systems.md:134Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-analyze-reliability/SKILL.md:2Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-analyze-reliability/SKILL.md:3Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-analyze-reliability/SKILL.md:4Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-classify-tabular-data/SKILL.md:12Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-classify-tabular-data/SKILL.md:13Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-classify-tabular-data/SKILL.md:14Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:14Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:15Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:16Low confidence
- Network access in prose of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:196Low confidence
- Network access in prose of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:197Low confidence
- Network access in prose of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:198Low confidence
- Network access in prose of the SKILL.mdmatlab-deploy-embedded-ai/SKILL.md:249Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md:38Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md:40Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md:328Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md:329Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/codegen-embedded.md:330Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-projection.md:5Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-projection.md:7Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-projection.md:103Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-projection.md:105Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-pruning.md:28Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-pruning.md:29Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-pruning.md:30Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-quantization.md:29Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-quantization.md:141Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-quantization.md:143Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-quantization.md:221Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/compression-quantization.md:222Low confidence
- Network access in prose of documentationmatlab-deploy-embedded-ai/references/pattern1/simulink-integration.md:71Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-engineer-tabular-features/SKILL.md:7Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-engineer-tabular-features/SKILL.md:8Low confidence
- Network access in the frontmatter of the SKILL.mdmatlab-engineer-tabular-features/SKILL.md:9Low confidence
- Network access in prose of the SKILL.mdmatlab-engineer-tabular-features/SKILL.md:345Low confidence
- Network access in prose of the SKILL.mdmatlab-engineer-tabular-features/SKILL.md:346Low confidence
- Network access in prose of documentationmatlab-engineer-tabular-features/references/assess.md:288Low confidence
- Network access in prose of documentationmatlab-engineer-tabular-features/references/assess.md:289Low confidence
- Network access in prose of documentationmatlab-engineer-tabular-features/references/deliver.md:267Low confidence
- Network access in prose of documentationmatlab-engineer-tabular-features/references/deliver.md:268Low confidence
- Network access in prose of documentationmatlab-engineer-tabular-features/references/domain-routing.md:318Low confidence
and 449 more
Only the first 500 facts are listed.
Works with
| Agent | Status | Evidence | Install to |
|---|---|---|---|
| Claude Code | Native | Manifest .claude-plugin/marketplace.json | .claude/skills/<skill-name>/ |
| Codex | Compatible | Standard SKILL.md skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md | .agents/skills/<skill-name>/ |
| Cursor | Compatible | Standard SKILL.md skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md | .cursor/skills/<skill-name>/ |
| Gemini CLI | Native | Manifest templates/gemini-extension.json | .gemini/skills/<skill-name>/ |
| GitHub Copilot | Compatible | Standard SKILL.md skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md | .github/skills/<skill-name>/ |
| OpenCode | Compatible | Standard SKILL.md skills-catalog/aerospace/matlab-compute-aerospace-environment/SKILL.md | .opencode/skills/<skill-name>/ |
- Native The repository ships a manifest, folder or frontmatter field for this agent.
- Compatible A standard SKILL.md that this agent can read.
- Unknown No evidence either way.
Derived automatically from paths, manifests and frontmatter. Not tested on each agent.
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