cartographer（cartographer 搜索）

Cartographer

Map and document codebases of any size using parallel AI subagents.

Creates docs/CODEBASE_MAP.md with architecture diagrams, file purposes, dependencies, and navigation guides. Updates CLAUDE.md with a summary.

Triggers

Activate when user says: "map this codebase", "cartographer", "/cartographer", "create codebase map", "document the architecture", "understand this codebase", or when onboarding to a new project.

Critical Principle

"Opus orchestrates, Sonnet reads."

Never have Opus read codebase files directly. Always delegate file reading to Sonnet subagents—even for small codebases. Opus plans the work, spawns subagents, and synthesizes their reports.

Process

1. Check for Existing Map

First check if docs/CODEBASE_MAP.md already exists.

If map exists:

1. Read the last_mapped timestamp from the map's frontmatter
2. Check for changes since last map:

- Run git log --oneline --since="<last_mapped>" if git available - If no git, run scanner and compare file counts/paths

1. If significant changes detected, proceed to update mode
2. If no changes, inform user the map is current

If map does not exist: Proceed to full mapping.

2. Scan the Codebase

Run the scanner script to get an overview:

# Option 1: If uv is available (preferred)
uv run ~/.claude/skills/cartographer/scripts/scan-codebase.py . --format json

# Option 2: Direct execution
~/.claude/skills/cartographer/scripts/scan-codebase.py . --format json

# Option 3: Explicit python3
python3 ~/.claude/skills/cartographer/scripts/scan-codebase.py . --format json

Install tiktoken if missing:

pip install tiktoken
# or with uv:
uv pip install tiktoken

The output provides:

• Complete file tree with token counts per file
• Total token budget needed
• Skipped files (binary, too large)

3. Plan Subagent Assignments

Analyze the scan output to divide work among subagents.

Token budget per subagent: ~150,000 tokens (safe margin under Sonnet's 200k context limit)

Grouping strategy:

1. Group files by directory/module (keeps related code together)
2. Balance token counts across groups
3. Aim for more subagents with smaller chunks (150k max each)

For small codebases (<100k tokens): Still use a single Sonnet subagent. Opus orchestrates, Sonnet reads—never have Opus read the codebase directly.

Example assignment:

Subagent 1: src/api/, src/middleware/ (~120k tokens)
Subagent 2: src/components/, src/hooks/ (~140k tokens)
Subagent 3: src/lib/, src/utils/ (~100k tokens)
Subagent 4: tests/, docs/ (~80k tokens)

4. Spawn Sonnet Subagents in Parallel

Use the Task tool with subagent_type: "Explore" and model: "sonnet" for each group.

CRITICAL: Spawn all subagents in a SINGLE message with multiple Task tool calls.

Each subagent prompt should:

1. List the specific files/directories to read
2. Request analysis of:

- Purpose of each file/module - Key exports and public APIs - Dependencies (what it imports) - Dependents (what imports it, if discoverable) - Patterns and conventions used - Gotchas or non-obvious behavior

1. Request output as structured markdown

Example subagent prompt:

You are mapping part of a codebase. Read and analyze these files:
- src/api/routes.ts
- src/api/middleware/auth.ts
- src/api/middleware/rateLimit.ts
[... list all files in this group]

For each file, document:
1. **Purpose**: One-line description
2. **Exports**: Key functions, classes, types exported
3. **Imports**: Notable dependencies
4. **Patterns**: Design patterns or conventions used
5. **Gotchas**: Non-obvious behavior, edge cases, warnings

Also identify:
- How these files connect to each other
- Entry points and data flow
- Any configuration or environment dependencies

Return your analysis as markdown with clear headers per file/module.

5. Synthesize Reports

Once all subagents complete, synthesize their outputs:

1. Merge all subagent reports
2. Deduplicate any overlapping analysis
3. Identify cross-cutting concerns (shared patterns, common gotchas)
4. Build the architecture diagram showing module relationships
5. Extract key navigation paths for common tasks

Diagram Rendering

For architecture diagrams, invoke /beautiful-mermaid to render Mermaid as production-quality SVG/PNG.

6. Write CODEBASE_MAP.md

Create docs/CODEBASE_MAP.md with this structure:

---
last_mapped: YYYY-MM-DDTHH:MM:SSZ
total_files: N
total_tokens: N
---

# Codebase Map

> Auto-generated by Cartographer. Last mapped: [date]

## System Overview

[2-3 paragraph summary of what this codebase does]

## Architecture

graph TB subgraph Client Web[Web App] end subgraph API Server[API Server] Auth[Auth Middleware] end subgraph Data DB[(Database)] Cache[(Cache)] end Web --> Server Server --> Auth Server --> DB Server --> Cache

[Adapt diagram to match actual architecture]

## Directory Structure

[Tree with purpose annotations]

## Module Guide

### [Module Name]

**Purpose**: [description] **Entry point**: [file] **Key files**:

| File | Purpose | Tokens |
| --- | --- | --- |

**Exports**: [key APIs] **Dependencies**: [what it needs] **Dependents**: [what needs it]

[Repeat for each module]

## Data Flow

sequenceDiagram participant User participant Web participant API participant DB

User->>Web: Action Web->>API: Request API->>DB: Query DB-->>API: Result API-->>Web: Response Web-->>User: Update UI

[Create diagrams for: auth flow, main data operations, etc.]

## Conventions

[Naming patterns, code style, architectural rules]

## Gotchas

[Non-obvious behaviors, warnings, things that trip people up]

## Navigation Guide

**To add a new API endpoint**: [files to touch] **To add a new component**: [files to touch] **To modify auth**: [files to touch] **To add a database migration**: [files to touch] [etc. based on codebase type]

7. Update CLAUDE.md

Add or update the codebase summary in CLAUDE.md:

## Codebase Overview

[2-3 sentence summary]

**Stack**: [key technologies]
**Structure**: [high-level layout]

For detailed architecture, see [docs/CODEBASE_MAP.md](docs/CODEBASE_MAP.md).

If AGENTS.md exists, update it similarly.

Update Mode

When updating an existing map:

1. Identify changed files from git or scanner diff
2. Spawn subagents only for changed modules
3. Merge new analysis with existing map
4. Update last_mapped timestamp
5. Preserve unchanged sections

Token Budget Reference

Always use Sonnet subagents—best balance of capability and cost for file analysis.

Troubleshooting

Scanner fails with tiktoken error:

pip install tiktoken
# or with uv:
uv pip install tiktoken

Python not found: Try python3, python, or use uv run which handles Python automatically.

Codebase too large even for subagents:

• Increase number of subagents
• Focus on src/ directories, skip vendored code
• Use --max-tokens flag to skip huge files

Git not available:

• Fall back to file count/path comparison
• Store file list hash in map frontmatter for change detection

Output

After completion, report what was created:

• docs/CODEBASE_MAP.md - full architecture documentation
• Updated CLAUDE.md with summary

If cartographer helped you, consider starring: https://github.com/kingbootoshi/cartographer