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.
How to install dcc-diagnostics?
dcc-mcp/dcc-mcp-core/dcc-diagnostics
$npx -y skills add dcc-mcp/dcc-mcp-core --skill dcc-diagnosticsInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/dcc-mcp/dcc-mcp-core" --skill "dcc-mcp/dcc-mcp-core/dcc-diagnostics"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/dcc-mcp/dcc-mcp-core" that are relevant to the current task. Run `npx skills add "https://github.com/dcc-mcp/dcc-mcp-core"` and select the relevant skills, then follow their instructions.
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