Codebase Investigation Skill
SkillDev toolsDeep codebase investigation to generate PROJECT.md context. Analyzes architecture, patterns, features, APIs, and schemas.
Available today. Use it from your connected AI after setup.
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Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Codebase Investigation Skill skill
What this skill tells your AI
The instructions your AI receives, as published by vinzenz/prd-breakdown-execute in .claude/skills/crd-investigate/SKILL.md and read by ahel’s review.
You perform deep analysis of an existing codebase to generate comprehensive PROJECT.md context.
Arguments
| Argument | Required | Description |
|---|---|---|
--project <path> | Yes | Path to project root |
--depth <level> | No | Investigation depth: quick, medium (default), deep |
Investigation Process
Step 1: Project Structure
# Get current git hash for context tracking
git -C {project_path} rev-parse HEAD
# List top-level structure
ls -la {project_path}
# Get directory tree (excluding common ignores)
find {project_path} -type d \
-not -path '*/\.*' \
-not -path '*/node_modules/*' \
-not -path '*/venv/*' \
-not -path '*/.venv/*' \
-not -path '*/__pycache__/*' \
-not -path '*/dist/*' \
-not -path '*/build/*' \
| head -100
Step 2: Tech Stack Detection
Check for package/config files:
# Check multiple patterns
ls {project_path}/pyproject.toml {project_path}/requirements.txt {project_path}/setup.py 2>/dev/null
ls {project_path}/package.json {project_path}/tsconfig.json 2>/dev/null
ls {project_path}/go.mod {project_path}/Cargo.toml 2>/dev/null
Read package files to extract:
- Language and version
- Framework (FastAPI, React, Go Chi, etc.)
- Database ORM (SQLAlchemy, Drizzle, GORM)
- Key dependencies
Step 3: Feature Discovery
Based on detected framework, look for features:
FastAPI/Python:
grep -r "@router\." {project_path}/src --include="*.py" -l
grep -r "@app\." {project_path}/src --include="*.py" -l
Express/Node:
grep -r "router\." {project_path}/src --include="*.ts" --include="*.js" -l
React:
find {project_path}/src -name "*.tsx" -path "*/components/*" -o -name "*.tsx" -path "*/pages/*"
Step 4: API Endpoint Extraction
FastAPI:
# Look for patterns like:
@router.get("/users")
@router.post("/auth/login")
Read files and extract:
- Method (GET, POST, PUT, DELETE)
- Path
- Request/response types from type hints
Express/TanStack:
// Look for patterns like:
router.get('/users', handler)
app.post('/auth/login', handler)
Step 5: Schema/Model Extraction
SQLAlchemy:
# Look for class definitions inheriting from Base
class User(Base):
__tablename__ = "users"
Drizzle:
// Look for table definitions
export const users = pgTable('users', {...})
Extract:
- Model name
- Table name
- Fields with types
- Relationships (foreign keys)
Step 6: Pattern Analysis
Identify common patterns:
- File naming conventions
- Import patterns
- Error handling approach
- Authentication mechanism
- State management (frontend)
Step 7: Generate PROJECT.md
Create PROJECT.md at {project_path}/PROJECT.md:
# Project: {detected name}
## Overview
{Inferred from README.md or code structure}
## Architecture
### Tech Stack
{Detected stack}
### Component Structure
{Directory tree with annotations}
### Key Patterns
{Detected patterns}
## Context Metadata
<project-context version="1.0">
<meta>
<last-updated>{now}</last-updated>
<last-context-hash>{git hash}</last-context-hash>
</meta>
<features>
{Discovered features}
</features>
<api-registry>
{Extracted endpoints}
</api-registry>
<schema-registry>
{Extracted models}
</schema-registry>
</project-context>
Step 8: Create CRD Directory
mkdir -p {project_path}/docs/crd
Depth Levels
Quick (5-10 minutes)
- Project structure
- Tech stack from package files
- Main entry points
- README overview
Medium (15-20 minutes) - Default
- All of Quick
- Feature inventory from routes/components
- API endpoint extraction
- Database model extraction
- Basic pattern identification
Deep (30+ minutes)
- All of Medium
- Full dependency graph
- Test coverage analysis
- Integration point mapping
- Detailed pattern analysis
- Code quality assessment
Output
After completion, report:
Investigation complete.
PROJECT.md generated at: {project_path}/PROJECT.md
Summary:
- Tech Stack: {stack}
- Features: {count} identified
- API Endpoints: {count} documented
- Database Models: {count} cataloged
- Context Hash: {hash}
docs/crd/ directory created for future CRDs.
Error Handling
| Situation | Action |
|---|---|
| Empty project | Create minimal PROJECT.md |
| No recognizable framework | Document structure only |
| Binary files | Skip, note in overview |
| Permission errors | Report and continue with accessible files |
| Very large codebase | Limit scope, note truncation |
Signals
- GitHub stars
- 56
- Forks
- 3
- Last commit
- Jan 2026
Advanced
- Catalog kind
- skill
- Gateway key
crd-investigate- Source
- github.com/vinzenz/prd-breakdown-execute