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MattiaF95/codebase-analysis-ai

An agentic AI skill that analyzes codebases to create, review, and incrementally maintain clear, structured project documentation

¿Qué es codebase-analysis-ai?

codebase-analysis-ai is a Antigravity agent skill that an agentic AI skill that analyzes codebases to create, review, and incrementally maintain clear, structured project documentation.

Compatible con~Claude Code~Codex CLI~Cursor✓Antigravity
npx skills add MattiaF95/codebase-analysis-ai

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Documentación

Codebase Analysis AI

Keep repository documentation aligned with implementation changes while minimizing repository reads and repeated analysis.

Select one mode

Choose exactly one mode before reading additional references.

  • setup: Install the skill, persistent agent rules, deterministic runtime, Git hooks, or GitHub Action. Require an explicit setup request. Read references/setup-mode.md and references/automation.md.
  • bootstrap: Create a complete documentation system from scratch. Require an explicit request to scan the full repository. Read references/bootstrap-mode.md, references/project-taxonomy.md, references/document-style.md, and references/subagent-contract.md.
  • update: Update existing documentation from current Git changes, a commit, or a commit range. This is the default synchronization mode. Read references/update-mode.md, references/change-detection.md, references/impact-resolution.md, and references/document-style.md.
  • audit: Inspect documentation accuracy, readability, language consistency, and link consistency without changing files. Read references/audit-mode.md, references/quality-rules.md, and references/document-style.md.
  • migrate: Index and normalize existing documentation that has no Codebase Analysis AI metadata. Read references/migrate-mode.md, references/documentation-schema.md, references/naming-conventions.md, and references/document-style.md.

Do not read references for unrelated modes.

Guardrails

  1. Never perform a full repository scan unless bootstrap is explicit.
  2. If docs/ is missing and bootstrap was not explicit, ask whether to initialize complete documentation or stop.
  3. If docs/ exists but docs/_meta/documentation-map.json does not, use migrate; do not silently rebuild all documentation.
  4. In update, inspect only changed files, mapped documents, and directly related first-level documents. Do not traverse related links recursively.
  5. Treat scripts/codebase_analysis_ai.py check as a deterministic gate. Treat audit as an agent-led read-only review. Do not conflate them.
  6. Do not invent commands, architecture, dependencies, active functionality, or planned work. Ground every claim in repository evidence.
  7. Never expose secrets, credentials, tokens, certificates, connection strings, or personal data in generated documentation.
  8. Write in the repository's established documentation language. During bootstrap, ask the user when no reliable language evidence exists; do not infer language from source code or author location.
  9. Preserve technical precision while making prose understandable to an engineer unfamiliar with the repository. Define uncommon or domain-specific acronyms at first use.
  10. Preserve manual content outside managed sections.
  11. Do not overwrite existing hooks, workflows, or agent instructions without a safe managed-block update. Stop on an unrecognized conflict.
  12. Do not commit, push, merge, or enable branch protection unless the user explicitly requests that external action.

Common execution contract

  1. Resolve the repository root and current Git state.
  2. Select one mode.
  3. Load only the references required for that mode.
  4. Run deterministic scripts before agent analysis whenever possible.
  5. Use parallel subagents only for independent macro-areas and only when the host supports them. Otherwise execute the same report contract sequentially.
  6. Validate names, links, source mappings, hashes, and managed sections before completion.
  7. Report changed documentation, checked direct relationships, unresolved evidence, and validation results.

Deterministic entry point

Use scripts/codebase_analysis_ai.py for change collection, impact resolution, hash checks, link validation, project setup, and metadata refresh. Run python scripts/codebase_analysis_ai.py --help for available commands.

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