Individual skill
dcc-diagnostics
Infrastructure skill — DCC-agnostic observability primitives: generate error reports, 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. Call dcc_diagnostics__error_report first whenever a tool fails with a vague error message. Not for primary task execution — use a domain skill for actual DCC operations.
python/dcc_mcp_core/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.
Install this skill
Choose an agent in your Stack or copy a command below. Commands fetch the pinned commit and copy only this skill directory. Existing destinations are refused. Copying a command does not install anything.
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 9, 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
Files and excerpt
File metadata and permitted, redacted excerpts come from the recorded scan. Source links are pinned to that commit.
Browse files
SKILL.mdcore · 3,971 bytesSKILL.mdcore · 3,971 bytesSKILL.mdcore · 3,971 bytesSKILL.mdcore · 3,971 bytesscripts/audit_log.pyruns · 6,052 bytesscripts/error_report.pyruns · 12,055 bytesscripts/process_status.pyruns · 3,643 bytesscripts/screenshot.pyruns · 9,770 bytesscripts/tool_metrics.pyruns · 5,787 bytestools.yamlasset · 5,663 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.
## Recommended debugging workflow
When a DCC tool fails with a vague error, call tools in this order:
```
1. dcc_diagnostics__error_report ← start here: log lines + failed jobs + env
2. dcc_diagnostics__audit_log ← sandbox-level denials and recent invocations