Analyze Project

Overview

Perform deep analysis of a codebase to understand its architecture, patterns, dependencies, and opportunities for improvement.

Core principle: Understand before changing. Map before navigating.

Trigger:

/popkit:project analyze

Arguments

--json

.claude/analysis.json

--quick

--focus <area>

arch

deps

quality

patterns

JSON Output Mode

When

--json

1. Output Format: Structured JSON matching

   output-styles/schemas/project-analysis.schema.json

2. Save Location:

   .claude/analysis.json

3. Purpose: Machine-readable output for skill generators and MCP generators

JSON Output Process

import sys
import json
from datetime import datetime
from pathlib import Path

# Add pattern detector to path
# No longer needed - install popkit-shared instead
from pattern_detector import analyze_project, detect_frameworks

# Detect patterns
project_dir = Path.cwd()
patterns = analyze_project(project_dir)
frameworks = detect_frameworks(project_dir)

# Build output
output = {
    "project_name": project_dir.name,
    "project_type": frameworks[0].name if frameworks else "unknown",
    "analyzed_at": datetime.now().isoformat(),
    "frameworks": [
        {"name": p.name, "confidence": p.confidence, "version": ""}
        for p in frameworks
    ],
    "patterns": [
        {
            "name": p.name,
            "category": p.category,
            "confidence": p.confidence,
            "examples": p.examples,
            "description": p.description
        }
        for p in patterns if p.category != "framework"
    ],
    "recommended_skills": [],  # Populated based on patterns
    "recommended_agents": [],  # Populated based on analysis
    "commands": {},  # Extracted from package.json
    "quality_metrics": {}  # TypeScript, linting, etc.
}

# Save to .claude/analysis.json
claude_dir = project_dir / ".claude"
claude_dir.mkdir(exist_ok=True)
(claude_dir / "analysis.json").write_text(json.dumps(output, indent=2))
print(json.dumps(output, indent=2))

Skill/Agent Recommendation Logic

Based on detected patterns, recommend:

project:deploy

project:db-migrate

project:supabase-sync

project:docker-dev

project:feature-toggle

performance-optimizer

accessibility-guardian

api-designer

security-auditor

test-writer-fixer

Analysis Areas

1. Project Structure

# Map directory structure
find . -type d -name "node_modules" -prune -o -type d -print | head -50

# Find main entry points
ls index.* main.* app.* src/index.* src/main.* 2>/dev/null

# Count files by type
find . -name "node_modules" -prune -o -type f -print | \
  sed 's/.*\.//' | sort | uniq -c | sort -rn | head -20

2. Technology Stack

Detect package managers:

ls package.json yarn.lock pnpm-lock.yaml Cargo.toml pyproject.toml go.mod 2>/dev/null

Detect frameworks:

• Next.js:

  next.config.*

  ,

  app/

  or

  pages/

• React:

  react

  in dependencies
• Vue:

  vue.config.*

• Express:

  express

  in dependencies
• FastAPI:

  fastapi

  in dependencies
• Rust:

  Cargo.toml

Detect databases:

• Supabase:

  @supabase/supabase-js

• Prisma:

  prisma/schema.prisma

• MongoDB:

  mongoose

• PostgreSQL:

  pg

  or

  postgres

3. Architecture Patterns

Frontend:

• Component structure (atomic design, feature-based, etc.)
• State management (Redux, Zustand, Context)
• Routing patterns

Backend:

• API design (REST, GraphQL, tRPC)
• Service layer organization
• Database access patterns

Common:

• Error handling patterns
• Logging approach
• Configuration management

4. Code Quality

# Check for linting config
ls .eslintrc* eslint.config.* .prettierrc* biome.json 2>/dev/null

# Check TypeScript config
ls tsconfig.json 2>/dev/null && grep "strict" tsconfig.json

# Find TODO/FIXME comments
grep -r "TODO\|FIXME" --include="*.ts" --include="*.tsx" --include="*.py" . | wc -l

5. Testing Coverage

# Find test files
find . -name "*.test.*" -o -name "*.spec.*" -o -name "test_*" 2>/dev/null | wc -l

# Check test config
ls jest.config.* vitest.config.* pytest.ini 2>/dev/null

# Find coverage reports
ls coverage/ .coverage htmlcov/ 2>/dev/null

6. Dependencies

# Count dependencies
jq '.dependencies | length' package.json 2>/dev/null
jq '.devDependencies | length' package.json 2>/dev/null

# Check for outdated
npm outdated 2>/dev/null | head -10

# Check for vulnerabilities
npm audit --json 2>/dev/null | jq '.metadata.vulnerabilities'

7. CI/CD and DevOps

# Find CI config
ls .github/workflows/*.yml .gitlab-ci.yml Jenkinsfile .circleci/config.yml 2>/dev/null

# Find Docker
ls Dockerfile docker-compose.yml 2>/dev/null

# Find deployment config
ls vercel.json netlify.toml fly.toml 2>/dev/null

Output Format

# [Project Name] Analysis Report

## Summary

- **Type**: [Web App / API / CLI / Library]
- **Stack**: [Primary technologies]
- **Size**: [Files, Lines of code]
- **Health**: [Good / Needs attention / Critical issues]

## Technology Stack

### Frontend

- Framework: [Next.js 14 / React / Vue / etc.]
- Styling: [Tailwind / styled-components / etc.]
- State: [Redux / Zustand / Context]

### Backend

- Runtime: [Node.js / Python / Rust / Go]
- Framework: [Express / FastAPI / Actix]
- Database: [PostgreSQL / MongoDB / etc.]

### DevOps

- CI/CD: [GitHub Actions / GitLab CI / etc.]
- Deployment: [Vercel / AWS / etc.]
- Container: [Docker / etc.]

## Architecture

### Directory Structure

\`\`\`
[Tree output of main directories]
\`\`\`

### Key Patterns

- [Pattern 1]: [Where used]
- [Pattern 2]: [Where used]

### Entry Points

- Main: `[path]`
- API: `[path]`
- Tests: `[path]`

## Code Quality

| Metric            | Value                | Status       |
| ----------------- | -------------------- | ------------ |
| Linting           | [Configured/Missing] | [OK/Warning] |
| TypeScript Strict | [Yes/No]             | [OK/Warning] |
| Test Coverage     | [X%]                 | [OK/Warning] |
| TODO Comments     | [N]                  | [OK/Warning] |

## Dependencies

### Production ([N] packages)

Top 5:

- [package]: [version]

### Security

- Vulnerabilities: [Low: X, Medium: Y, High: Z]

## Recommendations

### Critical

1. [Issue requiring immediate attention]

### High Priority

1. [Important improvement]

### Nice to Have

1. [Enhancement suggestion]

## Agent Opportunities

Based on analysis, these agents would be valuable:

- [agent-name]: [why]
- [agent-name]: [why]

## Next Steps

1. Run `/generate-mcp` to create project-specific tools
2. Run `/generate-skills` to capture discovered patterns
3. Run `/setup-precommit` to configure quality gates

Integration

Called by:

• Manual

  /analyze-project

  command
• After

  /init-project

Informs:

• /generate-mcp - What tools to create
• /generate-skills - What patterns to capture
• /setup-precommit - What checks to configure