context-detection

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Automatically detect project tech stack, frameworks, and development context

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[Memory and Context Management]

When & Why to Use This Skill

The Project Context Detection skill is an automated diagnostic tool designed to identify a project's technical DNA. It scans file systems for configuration files, lock files, and directory patterns to accurately detect programming languages (Node.js, Python, Go, etc.), frameworks (React, Next.js, Django), and testing suites. This enables AI agents to gain immediate situational awareness, ensuring that subsequent actions and code generations are perfectly aligned with the existing tech stack and development patterns.

Use Cases

  • Instant Tech Stack Identification: Automatically detect if a project uses TypeScript, Go, or Python by analyzing root configuration files like tsconfig.json, go.mod, or requirements.txt.
  • Framework-Specific Optimization: Identify the presence of frameworks like Next.js, FastAPI, or Rails to tailor code suggestions and architectural advice to specific framework best practices.
  • Automated Agent Tooling: Feed detected context into orchestration layers to automatically fetch and enable relevant skills, such as specialized testing or deployment tools, based on the project's needs.
  • Project Structure Analysis: Determine project types (e.g., fullstack, frontend, or API) by analyzing directory layouts, such as the presence of an 'app' directory or database schemas.
  • Dependency and Tooling Audit: Quickly identify which package managers (pnpm, yarn, poetry) and testing frameworks (Jest, Playwright, Pytest) are in use to maintain environment consistency.
namecontext-detection
descriptionAutomatically detect project tech stack, frameworks, and development context

Project Context Detection

Automatically analyzes the current project to detect technologies, frameworks, and development patterns.

When to Use

This skill is invoked when:

  • Running /auto-skills command

Detection Methods

1. File System Analysis

Check for configuration files and lock files:

Technology Indicators
Node.js package.json, package-lock.json, yarn.lock, pnpm-lock.yaml
Go go.mod, go.sum, *.go files
Python requirements.txt, pyproject.toml, Pipfile, poetry.lock
Ruby Gemfile, Gemfile.lock
Rust Cargo.toml, Cargo.lock
Java pom.xml, build.gradle
TypeScript tsconfig.json

2. Framework Detection

Framework Indicators
Next.js next.config.js, app/ directory with page.tsx
React package.json contains react, JSX files
Vue package.json contains vue, .vue files
GraphQL .graphql files, schema.graphql, Apollo/GraphQL in deps
Express express in dependencies
FastAPI fastapi in dependencies
Django django in dependencies, manage.py
Rails rails in dependencies, config/routes.rb

3. Testing Frameworks

Framework Indicators
Jest jest.config.js, *.test.js, *.spec.js
Playwright playwright.config.js, *.spec.ts
Pytest pytest.ini, conftest.py, test_*.py
Go testing *_test.go files

4. Code Analysis

Analyze file extensions and imports:

  • Count file types (.go, .tsx, .py, etc.)
  • Analyze import statements for frameworks
  • Check for API routes, database schemas

Output Format

Return a structured context object:

{
  "languages": ["go", "javascript"],
  "frameworks": ["nextjs", "graphql"],
  "testing": ["playwright", "go-testing"],
  "packageManager": "pnpm",
  "hasApi": true,
  "hasDatabase": true,
  "projectType": "fullstack"
}

Example Workflow

When detecting context for a project:

  1. Scan root directory for config files
  2. Analyze package.json, go.mod, or equivalent
  3. Count file types in src/ or main directories
  4. Check for test files and frameworks
  5. Return structured context for auto-installation decisions

Integration

This skill feeds into:

  • scan: Determines which SkillsMP skills to fetch