Validate WCAG 2.1 Level AA compliance and accessibility best practices. Use when performing accessibility audits and WCAG certification.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze an existing codebase in parallel via 7 specialized mapper subagents. Outputs structured findings to docs/codebase/ for persistent cross-session context. Use when onboarding to a brownfield project or when reactive on-demand file reading is too slow.
インストール方法を見るインストールする前に、エージェントに与えられる指示の中身を確認できます。
When starting work on an existing codebase, Claude must discover its structure, patterns,
and risks reactively — reading files on demand, accumulating context piecemeal. This skill
runs a one-time parallel analysis and persists the results in docs/codebase/ so every
future session loads structured context instead of starting blind.
Not for: greenfield projects you built from scratch (you already know the structure).
/map-codebase # full analysis (all 7 mappers)
/map-codebase <area> # single mapper focus (e.g. "security", "stack", "test")
/map-codebase --refresh # force re-analysis, even if docs/codebase/ exists
Valid area names: stack, architecture, conventions, security, test, dependency, concerns
Before spawning any agents, check if a previous map exists:
ls docs/codebase/INDEX.md 2>/dev/null
If INDEX.md exists AND --refresh was NOT passed:
If --refresh or no map exists: proceed to Step 1.
Before spawning agents, do a 30-second orientation:
# Count files by extension to understand the dominant language
find . -type f -not -path './.git/*' -not -path './.claude/*' \
| sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20
# Check for common entry points
ls -1 {main.py,app.py,index.ts,index.js,main.go,Cargo.toml,pyproject.toml,package.json} 2>/dev/null
# Size check — warn if > 500 files
find . -type f -not -path './.git/*' | wc -l
If > 2000 files: warn the user that analysis will take longer and suggest a focused area.
mkdir -p docs/codebase
For a full analysis, launch all 7 Task agents simultaneously.
For a focused area (/map-codebase security), launch only that agent.
Each agent is:
type: Explore (read-only, no code modifications)model: haiku (fast, sufficient for structured analysis)docs/codebase/<name>.mdstack-mapper → docs/codebase/stack.md
You are a stack-mapper agent. Analyze this codebase and produce a structured report
about its technology stack.
Find and report:
- Primary language(s) and version(s) (check .python-version, .nvmrc, go.mod, Cargo.toml, etc.)
- Frameworks in use (FastAPI, Django, Next.js, Express, etc.) with versions
- Runtime environment (Node, Python, Go, Rust, JVM)
- Package manager (pip, uv, npm, pnpm, yarn, cargo, go mod)
- Key configuration files and what they control
- Deployment artifacts (Dockerfile, docker-compose, Procfile, fly.toml, etc.)
Write output to docs/codebase/stack.md using this schema:
## Summary
- <3-5 bullet summary>
## Key Findings
<detailed findings>
## Risks / Concerns
<version mismatches, EOL runtimes, etc.>
## Files Analyzed
<list of key files read>
## Generated: <ISO datetime>
architecture-mapper → docs/codebase/architecture.md
You are an architecture-mapper agent. Analyze this codebase's structural design.
Find and report:
- Top-level directory structure and purpose of each major folder
- Architectural pattern in use (MVC, CQRS, hexagonal, monolith, microservices, etc.)
- Entry points (main files, CLI commands, API routers, event handlers)
- Module boundaries and how they communicate (imports, message queues, REST, etc.)
- Any clear layering violations or circular dependencies
Write output to docs/codebase/architecture.md using this schema:
## Summary
- <3-5 bullet summary>
## Directory Map
<annotated tree of top-level dirs>
## Architectural Pattern
<detected pattern + evidence>
## Entry Points
<list of entry files/functions>
## Key Findings
<inter-module communication, layering>
## Risks / Concerns
<boundary violations, coupling>
## Files Analyzed
<list>
## Generated: <ISO datetime>
conventions-mapper → docs/codebase/conventions.md
You are a conventions-mapper agent. Analyze coding conventions and style patterns.
Find and report:
- Naming style for files, classes, functions, variables (snake_case, camelCase, PascalCase)
- File organization pattern (feature-based, layer-based, etc.)
- Import style (absolute vs relative, aliased, barrel exports)
- Recurring structural patterns (factory, repository, service, handler, etc.)
- Docstring / comment style
- Error handling style (exceptions, Result types, error codes)
- Any style config files (eslint, ruff, flake8, etc.)
Sample 10-15 representative files across the codebase. Do not read every file.
Write output to docs/codebase/conventions.md using this schema:
## Summary
- <3-5 bullet summary>
## Naming Conventions
<findings>
## File Organization
<findings>
## Recurring Patterns
<list of patterns with example file paths>
## Style Config
<linter/formatter config findings>
## Key Findings
<anything non-obvious>
## Risks / Concerns
<inconsistencies, mixed styles>
## Files Analyzed
<list>
## Generated: <ISO datetime>
security-mapper → docs/codebase/security.md
You are a security-mapper agent. Analyze the codebase's security surface.
Find and report:
- Authentication mechanism (JWT, session cookies, OAuth, API keys, none)
- Authorization model (RBAC, ABAC, middleware-based, none)
- Input validation approach (Pydantic, Zod, manual, none)
- Secrets handling (env vars, vaults, hardcoded strings — flag any hardcoded secrets)
- SQL/NoSQL query construction (ORM, parameterized, raw strings — flag raw string concat)
- External API calls and whether responses are validated
- File upload handling (if any)
- CORS and CSP configuration (if applicable)
DO NOT modify any files. Flag concerns, do not fix them.
Write output to docs/codebase/security.md using this schema:
## Summary
- <3-5 bullet summary>
## Auth & Authorization
<findings>
## Input Validation
<findings>
## Secrets Handling
<findings>
## Query Construction
<findings>
## Key Findings
<anything non-obvious>
## Risks / Concerns
<ranked by severity: HIGH / MEDIUM / LOW>
## Files Analyzed
<list>
## Generated: <ISO datetime>
test-mapper → docs/codebase/test.md
You are a test-mapper agent. Analyze the codebase's test coverage and strategy.
Find and report:
- Test framework(s) in use (pytest, jest, vitest, go test, etc.)
- Test directory structure and naming conventions
- Types of tests present (unit, integration, e2e, snapshot)
- Approximate test-to-source file ratio
- CI configuration (GitHub Actions, CircleCI, etc.) and what it runs
- Coverage reporting setup (if any)
- Mocking strategy (mocks, fakes, stubs, real dependencies)
- Any obvious gaps (untested modules, no integration tests, etc.)
Write output to docs/codebase/test.md using this schema:
## Summary
- <3-5 bullet summary>
## Test Framework
<findings>
## Coverage Estimate
<findings>
## CI Configuration
<findings>
## Key Findings
<gaps, patterns>
## Risks / Concerns
<untested critical paths, flaky test patterns>
## Files Analyzed
<list>
## Generated: <ISO datetime>
dependency-mapper → docs/codebase/dependency.md
You are a dependency-mapper agent. Analyze direct and notable transitive dependencies.
Find and report:
- All direct dependencies from manifest files (pyproject.toml, package.json, go.mod, Cargo.toml)
- Whether versions are pinned, ranged, or unpinned
- Any obviously outdated major versions (e.g. Python 2, React 16, Django 2)
- Any dependencies with known CVE patterns in their name (e.g. old cryptography, xml2, etc.)
- Duplicate dependencies serving the same purpose (e.g. two HTTP clients)
- Dev vs prod dependency separation
Do NOT run any package manager commands. Read manifest files only.
Write output to docs/codebase/dependency.md using this schema:
## Summary
- <3-5 bullet summary>
## Direct Dependencies
<categorized list: web, db, auth, infra, dev, etc.>
## Version Pinning
<findings>
## Notable Risks
<outdated, suspicious, duplicated deps>
## Key Findings
<anything non-obvious>
## Risks / Concerns
<ranked>
## Files Analyzed
<list>
## Generated: <ISO datetime>
concerns-mapper → docs/codebase/concerns.md
You are a concerns-mapper agent. Surface technical debt, code health signals, and
maintenance concerns.
Find and report:
- TODO/FIXME/HACK/XXX/NOSONAR count and distribution (grep, do not read every file)
- Largest files by line count (top 10 — flag any > 500 lines)
- Duplicated logic (similar function names, copy-paste blocks across files)
- Dead code signals (commented-out code blocks, unused imports in sampled files)
- Missing error handling (bare except, swallowed errors in sampled files)
- Deprecated patterns for the detected stack
- Any .old, .bak, _v2, or archived files left in the tree
Write output to docs/codebase/concerns.md using this schema:
## Summary
- <3-5 bullet summary>
## TODO/FIXME Count
<totals + hotspot files>
## Oversized Files
<top 10 by line count>
## Duplication Signals
<findings>
## Dead Code Signals
<findings>
## Key Findings
<anything non-obvious>
## Risks / Concerns
<ranked>
## Files Analyzed
<list>
## Generated: <ISO datetime>
After all agents complete, synthesize findings into docs/codebase/INDEX.md:
# Codebase Map — <project name>
**Generated:** <ISO datetime>
**Mappers run:** stack | architecture | conventions | security | test | dependency | concerns
## Stack Snapshot
<1-2 lines from stack.md summary>
## Architecture Snapshot
<1-2 lines from architecture.md summary>
## Test Health
<1-2 lines from test.md summary>
## Top 3 Cross-Cutting Concerns
1. <highest priority concern from any mapper>
2. <second>
3. <third>
## Security Flags
<any HIGH-severity items from security.md — or "None flagged">
## Quick-Start Recommendations
For the next session working in this codebase:
- Start by reading: <2-3 key files identified by architecture-mapper>
- Watch out for: <top concern>
- Run before committing: <test/lint commands from test-mapper>
## Refresh
Run `/map-codebase --refresh` to re-analyze.
Individual mappers: `/map-codebase <area>`
Present a brief summary:
Codebase map complete. Wrote 7 mapper files + INDEX.md to docs/codebase/
Stack: <1-line>
Architecture: <1-line>
Top concern: <1-line>
Future sessions will auto-load this map at startup (if SessionStart hook is configured).
Run /map-codebase --refresh to update.
docs/codebase/
├── INDEX.md ← session-injectable summary
├── stack.md
├── architecture.md
├── conventions.md
├── security.md
├── test.md
├── dependency.md
└── concerns.md
All files are committed to the repo (project-shared, cross-session).
If hooks/handlers/session.py is configured to inject this map, it will:
docs/codebase/INDEX.md in cwdCodebase map available. Run /map-codebase --refresh to update.This is passive — no injection if the file is absent.
/diagnose — investigate bugs with unknown root cause (uses subagent pattern this skill mirrors)/security-verify scan — deep security scanning after security-mapper flags concerns/health — ongoing project audit (runs periodically; map-codebase is a one-time onboarding step)/implementation — once map is loaded, implementation has structured context about conventionsまだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
Validate WCAG 2.1 Level AA compliance and accessibility best practices. Use when performing accessibility audits and WCAG certification.
日本語の概要は準備中です。原文の説明を表示しています。
Analyze feature requirements, dependencies, and security considerations. Use when starting feature implementation from GitHub issues to understand scope, technical feasibility, and risks.
日本語の概要は準備中です。原文の説明を表示しています。
Run SQL queries against psql, BigQuery, or MySQL from the terminal, including natural-language-to-SQL and schema exploration. Use when analyzing data, inspecting DB state, or debugging tables. Trigger on "query the database", "SQL", "show me data from", "explore table".
日本語の概要は準備中です。原文の説明を表示しています。
Design REST APIs or function contracts with clear request/response specifications, error handling patterns, authentication strategies, and comprehensive documentation.
日本語の概要は準備中です。原文の説明を表示しています。
Generate comprehensive API endpoint tests for REST and GraphQL APIs. Creates tests for all HTTP methods, status codes, authentication, and validation.
日本語の概要は準備中です。原文の説明を表示しています。
Design component architecture and module structure using established architectural patterns for clean, maintainable, and scalable systems.
日本語の概要は準備中です。原文の説明を表示しています。