kata-map-codebase

<objective> Analyze existing codebase using parallel kata-codebase-mapper agents to produce structured codebase documents.

Each mapper agent explores a focus area and writes documents directly to .planning/codebase/. The orchestrator only receives confirmations, keeping context usage minimal.

Output: .planning/codebase/ folder with 7 structured documents, plus .planning/intel/ with compressed agent-readable artifacts (doc-derived summary + code-scanned index and conventions). </objective>

<execution_context> @./references/project-analyze.md </execution_context>

<context> Focus area: $ARGUMENTS (optional - if provided, tells agents to focus on specific subsystem)

Load project state if exists: Check for .planning/STATE.md - loads context if project already initialized

This command can run:

Before /kata-new-project (brownfield codebases) - creates codebase map first
After /kata-new-project (greenfield codebases) - updates codebase map as code evolves
Anytime to refresh codebase understanding </context>

<when_to_use> Use project-analyze for:

Brownfield projects before initialization (understand existing code first)
Refreshing codebase map after significant changes
Onboarding to an unfamiliar codebase
Before major refactoring (understand current state)
When STATE.md references outdated codebase info

Skip project-analyze for:

Greenfield projects with no code yet (nothing to map)
Trivial codebases (<5 files) </when_to_use>

<process> 1. Check if .planning/codebase/ already exists (offer to refresh or skip) 2. Create .planning/codebase/ directory structure 3. Spawn 4 parallel kata-codebase-mapper agents: - Agent 1: tech focus → writes STACK.md, INTEGRATIONS.md - Agent 2: arch focus → writes ARCHITECTURE.md, STRUCTURE.md - Agent 3: quality focus → writes CONVENTIONS.md, TESTING.md - Agent 4: concerns focus → writes CONCERNS.md 4. Wait for agents to complete, collect confirmations (NOT document contents) 5. Verify all 7 documents exist with line counts 5.5. Generate codebase intelligence artifacts - Run the intel generator script: ```bash node scripts/generate-intel.js ``` - If script fails, show the error to the user and continue (non-blocking) - Verify artifacts exist: ```bash ls .planning/intel/summary.md .planning/intel/index.json .planning/intel/conventions.json ``` 5.6. Scan source code for structured index Run the code scanner to produce code-derived index.json and conventions.json: ```bash node scripts/scan-codebase.cjs ``` This overwrites the doc-derived index.json and conventions.json from step 5.5 with code-derived data (version 2 schema with per-file imports/exports, naming detection, directory purposes). If the script fails, show the error to the user and continue (non-blocking). Verify code-scan artifacts: ```bash node -e "const j=JSON.parse(require('fs').readFileSync('.planning/intel/index.json','utf8')); console.log('index version:', j.version, 'files:', Object.keys(j.files).length)" ``` 6. Commit codebase map and intel artifacts (`.planning/codebase/` + `.planning/intel/`) 7. Offer next steps (typically: /kata-new-project or /kata-plan-phase) </process>

<success_criteria>

.planning/codebase/ directory created
.planning/intel/ directory created with summary.md, index.json, conventions.json
All 7 codebase documents written by mapper agents
Documents follow template structure
Parallel agents completed without errors
User knows next steps </success_criteria>

kata-map-codebase

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