By Borda
Scan Python codebases once with /codemap:scan to build a JSON index of the import graph, capturing blast-radius metrics and coupling data. Then query via /codemap:query to uncover central modules, direct/reverse dependencies, and import paths—assess refactor risks before editing. Audit setup with /codemap:audit for integration checks.
Manage codemap integration — 'check' audits installation health (scan-query reachable, index fresh, injection present), 'init' onboards codemap by discovering skills/agents, recommending injection sites, and wiring them in.
Query the codemap structural index — central, coupled, deps, rdeps, or import path between modules.
Scan the Python codebase and build a structural JSON index (import graph + blast-radius metrics).
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npx claudepluginhub borda/ai-rig --plugin codemapImplementation workflow skills: feature, fix, refactor, plan, debug
OSS Claude Code config: agents, skills, and hooks for professional AI-assisted development workflows
OSS maintenance skills: analyse, resolve, review, release
ML/perf investigation skills: topic, plan, judge, run, sweep
Local codebase intelligence + change-safety gates for coding agents. Pre-indexes your repo's symbols, call graph, deps, and git history into SQLite (28 languages, 100% local, zero API keys), then exposes a lean 16-tool MCP core preset: graph-precise search, callers/impact blast radius, coupling, dead code, taint reachability, and pre-merge verify/critique gates that catch regressions, broken references, AI-slop duplication, and convention drift before they ship.
Smart codebase exploration with dependency mapping and structure analysis
Lightweight knowledge graph for AI-assisted development. Impact analysis, code search, dependency tracking, and context generation.
Codebase exploration, refactoring, and quality analysis
Codebase intelligence for Claude Code. Indexes your codebase into five layers (Graph, Git, Docs, Decisions, Code Health) and exposes them through nine task-shaped MCP tools — so Claude understands architecture, ownership, hotspots, why code is built the way it is, and where the defect risk lives.
Structural codebase indexing for efficient navigation. Reduces token consumption by 60-80% through targeted line-range reads instead of full file scans.