aiskillstore/codebase-mapping
skills/dowwie/codebase-mapping/SKILL.md
Repository structure and dependency analysis for understanding a codebase's architecture. Use when needing to (1) generate a file tree or structure map, (2) analyze import/dependency graphs, (3) identify entry points and module boundaries, (4) understand the overall layout of an unfamiliar codebase, or (5) prepare for deeper architectural analysis.
$ install --global
skillsauthnpx skillsauth add aiskillstore/marketplace codebase-mappingInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
Security Scan Results
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
3
Scanners Passed
9
Scanners in report
Clean
TrivyContainer and dependency vulnerability scanner
95%
Clean
SemgrepStatic code analysis for vulnerabilities
95%
Clean
mcp-scan (Snyk)Model Context Protocol security validation
95%
Skipped
Snyk (dep)Open source security scanning
50%
Skipped
Socket.devSupply chain security analysis
50%
Skipped
VirusTotalMulti-engine malware detection
50%
Skipped
CrowdStrikeAdvanced threat intelligence
50%
Skipped
OSV-ScannerOpen Source Vulnerability database check
50%
Skipped
OWASP Dep-Check
50%
Last scanned: Apr 1, 2026, 3:29 PM57.4s3 files scanned
SKILL.md
- name:
- codebase-mapping
- description:
- Repository structure and dependency analysis for understanding a codebase's architecture. Use when needing to (1) generate a file tree or structure map, (2) analyze import/dependency graphs, (3) identify entry points and module boundaries, (4) understand the overall layout of an unfamiliar codebase, or (5) prepare for deeper architectural analysis.
Codebase Mapping
Maps repository structure and dependencies to enable targeted architectural analysis.
Quick Start
Generate a structural map:
python scripts/map_codebase.py /path/to/repo --output structure.json
Process
- Clone or access the target repository
- Generate file tree excluding noise (node_modules, pycache, .git, etc.)
- Parse imports to build dependency graph
- Identify entry points (main.py, index.ts, setup.py, pyproject.toml)
- Detect boundaries - package structure and public APIs
Output Artifacts
The skill produces:
file_tree.txt- Annotated directory structuredependencies.json- Import graph in adjacency list formatentry_points.md- Identified entry points with descriptionsmodule_map.md- Package boundaries and public interfaces
Key Patterns to Identify
Entry Point Detection
Look for these patterns:
- Python:
if __name__ == "__main__",setup.py,pyproject.toml - Node:
package.jsonmain/bin fields,index.js - Frameworks:
app.py(Flask),manage.py(Django),main.ts(Nest)
Dependency Classification
Classify imports as:
- External: Third-party packages (from package manager)
- Internal: Project modules (relative imports)
- Standard: Language standard library
Noise Exclusion
Always exclude:
node_modules/
__pycache__/
.git/
.venv/
venv/
dist/
build/
*.egg-info/
.mypy_cache/
.pytest_cache/
Integration with Other Skills
This skill provides the foundation for:
data-substrate-analysis→ Focus on types.py, models.pyexecution-engine-analysis→ Focus on runner filescontrol-loop-extraction→ Focus on agent.py, loop filescomponent-model-analysis→ Focus on base classes
Example Output
## Repository: langchain
### Structure Summary
- 342 Python modules across 28 packages
- Primary entry: langchain/__init__.py
- Core packages: agents, chains, llms, tools
### Key Files for Analysis
- Types: langchain/schema.py, langchain/types.py
- Execution: langchain/agents/executor.py
- Tools: langchain/tools/base.py
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