codebase-index
FeaturedGenerate machine-readable index files in .ai/index/ (component inventory, uses/usedBy graph, stats) for AI agents. Triggers: index my codebase, build a relationship graph, what depends on what. Not an assessment; for library health use component-audit.
Web & Frontend 196 stars
7 forks Updated 2 days ago MIT
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Quality Score: 90/100
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Skill Content
# Codebase index
A skill for generating a pre-computed, machine-readable index of a design system's codebase. The index contains three pieces: a component inventory, a relationship graph, and summary statistics. Together they form a queryable map that eliminates the need for AI agents or developers to explore the codebase from scratch every time they need to understand the system.
## Before you begin: verify references
Before doing anything else, confirm that every file listed in this skill's frontmatter `references:` field exists at its relative path from this SKILL.md. If any are missing, stop — the install is incomplete. This usually means a third-party installer (for example `npx skills install`) flattened the skill into a standalone folder and dropped the repo-root `knowledge-notes/` directory this skill depends on. Tell the user to reinstall using a supported method from `1-INSTALL.md` (git clone, or the `.plugin` bundle in Cowork) and to run `verify-install.sh` from the install root to confirm the fix. Only proceed without the references if the user explicitly says to — and if they do, state clearly in your output that it was produced in degraded mode without the pack's reference material.
## Context
When an AI agent needs to work with a design system codebase, it has two options: explore or navigate. Exploration means scanning directories, grepping for imports, reading files one by one. Navigation means loading a pre-computed index and reasoning over cached data....
Details
- Author
- murphytrueman
- Repository
- murphytrueman/design-system-ops
- Created
- 6 months ago
- Last Updated
- 2 days ago
- Language
- Python
- License
- MIT
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