detect-tech-stack

Detect Tech Stack Skill

Purpose

Automatically detect project technologies by analyzing dependency files and project structure. Returns structured JSON with framework versions, databases, test frameworks, and libraries.

When Claude Uses This Skill

Claude automatically invokes this skill when:

1. Creating environment: /create-environment needs to detect tech stack for first time
2. Updating environment: /update-environment auto needs to re-detect for comparison
3. User requests detection: "What tech stack does this project use?"
4. Analyzing project: "Analyze my project structure"

Invocation

From target project, run:

# Output to stdout
python ${CLAUDE_PLUGIN_ROOT}/skills/detect-tech-stack/scripts/detect.py

# Save directly to file (preferred for update-environment)
python ${CLAUDE_PLUGIN_ROOT}/skills/detect-tech-stack/scripts/detect.py --output /tmp/new-project-analysis.json

Usage

Automatic Invocation

User: /create-environment

Claude: I'll detect your project's tech stack first.
[Automatically invokes detect-tech-stack skill]

Tech Stack Detected:
- Backend: Django 5.0.1 (Python)
- Frontend: React 18.2.0 + Next.js 14.0.0
- Database: PostgreSQL 15.3
- Tests: pytest, jest, playwright

Manual Invocation (by user)

User can run the slash command directly:

# This will be registered if skill provides a command
/detect-tech-stack

Or ask Claude to analyze:

User: What technologies does my project use?
Claude: [Invokes detect-tech-stack skill automatically]

How It Works

The skill executes detect.py which:

1. Scans dependency files:

   • Python: requirements.txt, pyproject.toml, Pipfile
   • JavaScript: package.json
   • Go: go.mod
   • Ruby: Gemfile
   • Java: pom.xml, build.gradle
   • PHP: composer.json

2. Detects frameworks and versions:

   • Backend: Django, FastAPI, Flask, Express, NestJS, Gin, Rails, Spring Boot, Laravel
   • Frontend: React, Vue, Angular, Svelte (+ meta-frameworks: Next.js, Nuxt, SvelteKit)
   • Databases: PostgreSQL, MySQL, MongoDB, SQLite, Redis, MariaDB
   • Test Frameworks: pytest, jest, vitest, playwright, cypress, mocha

3. Analyzes project structure:

   • Monorepo detection (lerna, pnpm workspaces, turborepo)
   • Docker setup (Dockerfile, docker-compose.yml)
   • CI/CD (GitHub Actions, GitLab CI, CircleCI)
   • Deployment platforms (Vercel, Netlify, Render)

4. Outputs structured JSON:

   {
     "project_name": "example-app",
     "detected_at": "2025-12-18T10:30:00Z",
     "backend": {
       "framework": "Django",
       "version": "5.0.1",
       "language": "Python",
       "has_backend": true
     },
     "frontend": {
       "framework": "React",
       "version": "18.2.0",
       "meta_framework": "Next.js",
       "meta_version": "14.0.0",
       "has_frontend": true
     },
     "database": {
       "primary": "PostgreSQL",
       "version": "15.3",
       "cache": "Redis"
     },
     "testing": {
       "frameworks": ["pytest", "jest", "playwright"],
       "has_tests": true,
       "has_e2e_tests": true
     },
     "libraries": {
       "state_management": "Redux",
       "orm": "Prisma",
       "ui_library": "Material-UI",
       "api_client": "axios"
     },
     "structure": {
       "is_monorepo": false,
       "has_docker": true,
       "has_ci_cd": true,
       "ci_platform": "GitHub Actions",
       "deployment_platform": "Vercel"
     }
   }
   

Output

Success

{
  "status": "success",
  "data": {
    "project_name": "...",
    "backend": {...},
    "frontend": {...},
    ...
  }
}

Error

{
  "status": "error",
  "message": "No dependency files found. Is this a code project?"
}

Exit Codes

• 0: Detection successful
• 1: No dependency files found
• 2: Invalid project structure
• 3: Error reading files

Integration with Commands

/create-environment

## Phase 1: Create Generation Plan

1. **Detect tech stack**: Invoke detect-tech-stack skill
   - Skill returns JSON with all detected technologies
   - Save to `.memory_bank/project-analysis.json`

2. **Analyze templates**: Use detected tech stack to filter relevant prompts

/update-environment auto

## Step 0.1: Analyze Current Project State

1. **Re-detect tech stack**: Invoke detect-tech-stack skill
   - Returns current state as JSON

2. **Load original state**: Read `.memory_bank/project-analysis.json`

3. **Compare states**: Identify changes (framework upgrades, new libraries, etc.)

Example Scenarios

Scenario 1: Django + React Project

Input: Project with package.json (react, next) and requirements.txt (django, psycopg2)

Output:
✓ Backend: Django 5.0.1 (Python)
✓ Frontend: React 18.2.0 + Next.js 14.0.0
✓ Database: PostgreSQL (from psycopg2)
✓ Tests: pytest, jest
✓ Docker: Yes (docker-compose.yml found)

Scenario 2: Go Microservices

Input: Project with go.mod (gin, gorm, testify)

Output:
✓ Backend: Gin (Go)
✓ Database: PostgreSQL (from gorm)
✓ Tests: Go testing + testify
✓ Docker: Yes
✓ CI/CD: GitHub Actions

Scenario 3: Monorepo

Input: pnpm-workspace.yaml, multiple package.json files

Output:
✓ Monorepo: Yes (pnpm workspaces)
✓ Frontend: React (apps/web), Vue (apps/admin)
✓ Backend: Express.js (apps/api)
✓ Shared packages detected: 3

Script Location

${CLAUDE_PLUGIN_ROOT}/skills/detect-tech-stack/scripts/detect.py

Dependencies

• Python 3.7+
• Standard library only (json, pathlib, re, datetime)
• No external dependencies required

Testing

Run detection manually:

cd /path/to/project

# Print to stdout
python ${CLAUDE_PLUGIN_ROOT}/skills/detect-tech-stack/scripts/detect.py

# Save to file
python ${CLAUDE_PLUGIN_ROOT}/skills/detect-tech-stack/scripts/detect.py --output /tmp/result.json

Notes

• Detection is non-invasive (read-only, no file modifications)
• Handles missing files gracefully (returns null for undetected items)
• Version extraction uses regex for common version formats
• Supports multiple dependency files (e.g., both requirements.txt and package.json)