Individual skill
documentation-inversion
Inverts the traditional documentation flow from code-to-wiki-for-humans (which rots) into code-to-CLAUDE.md-to-skills-for-agents (which stays current). Each module gets a machine-readable CLAUDE.md, navigation skills teach agents how to explore libraries, and plugins package skills for on-demand loading. Documentation structured for machine consumption -- hierarchical, cross-referenced, with clear entry points -- rather than narrative human reading. This is a fundamental shift: build documentation for agents, not people. Triggers: "documentation inversion", "skills as docs", "living documentation", "docs for agents", "machine-readable docs", "agent-first documentation".
plugins/JuliusBrussee/blueprint/skills/documentation-inversion/SKILL.md
Source commit d780783eba4ecc7c8b9429f95c9362df95f07c61
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 4, 2026
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Repository context
- Repository stars (not skill ratings)
- 1,537
- Repository last updated
- Nov 7, 2026
- License
- Apache-2.0
Observed agent integration: No specific integration evidence. Standard SKILL.md installation does not imply verified compatibility.
- ai-coding Repository topic
- awesome Repository topic
- awesome-list Repository topic
- codex Repository topic
- codex-plugins Repository topic
- openai Repository topic
- codex-skill Repository topic
- codex-skills Repository topic
- marketplace Repository topic
- codex-marketplace Repository topic
- docs Derived category
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Read excerpt
# Documentation Inversion
Traditional documentation drifts out of sync because it lives separately from the code. Documentation inversion places guidance directly in the codebase, structured for agent consumption, so that AI can explore the source and find current information on demand.
## Core Principle
> **Structure documentation for programmatic navigation -- hierarchical, cross-referenced, with
> explicit entry points -- so that AI agents can find what they need without human guidance.**
Traditional documentation assumes a human reader who will browse, search, and interpret context.
Agent-first documentation assumes a machine reader that needs: explicit entry points, structured
hierarchies, cross-references it can follow programmatically, and guidance on what to explore next.
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