Individual skill
dcc-diagnostics
Infrastructure skill — DCC-agnostic observability primitives: capture screenshots, query audit logs, inspect tool performance metrics, and monitor process health. Works in any DCC environment (Maya, Blender, Houdini, Unreal, etc.) or standalone Python. Use for debugging any skill failure or verifying DCC state. Not for primary task execution — use a domain skill for actual DCC operations.
examples/skills/dcc-diagnostics/SKILL.md
Source commit bcd69852790ee657b7543e83b122ea2cb965beb5
What was checked
- Matches the observed repository HEAD
- Yes
- Scanner rules are current
- No
- Repository scan complete
- No
- Skill scan complete
- No
- Observed behavior
- Not checked yet
- Last checked
- Nov 7, 2026
These are observations at the recorded commit, not a guarantee of safety. Review the source before running it.
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An install command is unavailable: current rules, complete repository and skill scans, an eligible behavior level and a permitted license are required.
Repository context
- Repository stars (not skill ratings)
- 73
- Repository last updated
- Nov 8, 2026
- License
- MIT
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-agents Repository topic
- automation Repository topic
- blender Repository topic
- dcc Repository topic
- houdini Repository topic
- maya Repository topic
- mcp Repository topic
- model-context-protocol Repository topic
- photoshop Repository topic
- pyo3 Repository topic
- operations Derived category
- devops Derived category
- security Derived category
- testing Derived category
Files and excerpt
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Browse files
SKILL.mdcore · 2,266 bytesSKILL.mdcore · 2,266 bytesSKILL.mdcore · 2,266 bytesSKILL.mdcore · 2,266 bytesscripts/audit_log.pyruns · 5,759 bytesscripts/process_status.pyruns · 3,495 bytesscripts/screenshot.pyruns · 3,167 bytesscripts/tool_metrics.pyruns · 5,457 bytestools.yamlasset · 3,789 bytes
Read excerpt
# DCC Diagnostics
Cross-DCC observability and debugging tools powered by `dcc-mcp-core`.
All tools work in any DCC environment (Maya, Blender, Houdini, Unreal, 3ds Max)
or standalone Python — no DCC-specific APIs required.
## Tools
### `dcc_diagnostics__screenshot`
Capture the current screen or a specific window as a PNG/JPEG image.
Backed by the `dcc_mcp_core.Capturer` class which uses: