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zenobi-us

codemapper

by zenobi-us

my workstation setup for linux, windows and mac

25🍴 4📅 Jan 22, 2026

SKILL.md


name: codemapper description: Use when analyzing codebases for structure, finding symbols, tracing call paths, checking test coverage, or analyzing dependencies - provides instant AST-based code analysis using tree-sitter for Python, JavaScript, TypeScript, Rust, Java, Go, and C

CodeMapper (cm) - Fast Code Analysis

Overview

CodeMapper (cm) uses tree-sitter AST parsing to provide instant code analysis without databases. Get project structure, find symbols, trace call graphs, and analyze dependencies in milliseconds.

Supported Languages: Python, JavaScript, TypeScript, Rust, Java, Go, C, Markdown

When to Use

Use CodeMapper when you need to:

  • ✅ Explore unfamiliar codebases (get overview, find structure)
  • ✅ Find symbol definitions and usages (functions, classes, methods)
  • ✅ Understand call graphs (who calls what, call paths)
  • ✅ Check test coverage (find untested code)
  • ✅ Analyze git changes at symbol level (breaking changes)
  • ✅ Pre-refactoring impact analysis (understand dependencies)

Don't use for:

  • ❌ Full-text search (use ripgrep/grep instead)
  • ❌ Runtime analysis (use profilers)
  • ❌ Code execution (use interpreters/compilers)

Quick Start

# Step 1: Get overview
cm stats .

# Step 2: See file structure (ALWAYS use --format ai for LLMs)
cm map . --level 2 --format ai

# Step 3: Find specific code
cm query <symbol> --format ai

# Step 4: Deep dive into a file
cm inspect ./path/to/file --format ai

🔥 CRITICAL: Always use --format ai when analyzing code for LLM context. This is the most token-efficient format (60-80% reduction).

Essential Commands

TaskCommand
Project overviewcm stats .
File structurecm map . --level 2 --format ai
Find symbolcm query <name> --format ai
Show implementationcm query <name> --show-body --format ai
Who calls it?cm callers <symbol> --format ai
What does it call?cm callees <symbol> --format ai
Call path A→Bcm trace <from> <to> --format ai
Find testscm tests <symbol> --format ai
Untested codecm untested . --format ai
Breaking changescm since <commit> --breaking --format ai

For complete command reference: Read references/command-reference.md

Key Workflows

Exploring Unknown Code

cm stats .
cm map . --level 2 --format ai
cm query <symbol> --format ai

Before Refactoring

cm callers <function> --format ai      # Who depends on this?
cm tests <function> --format ai        # Is it tested?
cm callees <function> --format ai      # What does it depend on?

Code Health Check

cm untested . --format ai                       # What's not tested?
cm since <last_release> --breaking --format ai  # Breaking changes?

For detailed workflows: Read references/workflows.md

Common Mistakes

❌ Forgetting --format ai

# Bad (verbose, token-heavy)
cm map . --level 2

# Good (compact, LLM-optimized)
cm map . --level 2 --format ai

❌ Using grep for call graphs

# Bad (misses indirect calls, false positives)
grep -r "process_payment"

# Good (accurate AST-based call graph)
cm callers process_payment --format ai

❌ Skipping stats/map

# Bad (jumping to query without context)
cm query something --format ai

# Good (understand structure first)
cm stats .
cm map . --level 2 --format ai
cm query something --format ai

For more examples: Read references/common-mistakes.md

Best Practices

  1. Always start with overview: cm stats . then cm map . --level 2 --format ai
  2. Always use --format ai for LLMs: Token efficiency matters
  3. Fuzzy search first: Default fuzzy matching is more forgiving
  4. Check before refactoring: Run cm callers and cm tests before changes
  5. Use correct tool: CodeMapper for structure/calls, ripgrep for text search

Troubleshooting

No Symbols Found?

  • Check file extensions: cm stats . shows what's indexed
  • Try fuzzy search (default) vs --exact

Slow Queries?

  • First run builds cache (~10s)
  • Subsequent runs use cache (~0.5s)

Git Commands Fail?

  • Must be in a git repository for: diff, since, blame, history

For detailed troubleshooting: Read references/troubleshooting.md

Reference Documentation

  • references/command-reference.md - Complete command and flag reference
  • references/workflows.md - Detailed workflow patterns for common tasks
  • references/common-mistakes.md - Extended examples of what to avoid
  • references/troubleshooting.md - Comprehensive troubleshooting guide
  • references/integration-examples.md - CI/CD, documentation, code review patterns

Performance

  • Small repos (< 100 files): < 20ms instant
  • Medium repos (100-1000): ~0.5s with cache
  • Large repos (1000+): Fast mode auto-enabled

Cache location: .codemapper/ in project root (auto-managed)

Score

Total Score

65/100

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