project-analyzer

name	project-analyzer
description	Automated brownfield codebase analysis. Detects project type, frameworks, dependencies, architecture patterns, and generates comprehensive project profile. Essential for Conductor integration and onboarding existing projects.
version	1.0.0
model	sonnet
invoked_by	both
user_invocable	true
tools	["Read","Glob","Grep","Bash"]
best_practices	["Detect project root from package managers and manifest files","Identify frameworks from dependencies and directory structure","Generate comprehensive file statistics and language breakdown","Map component relationships and architecture patterns","Validate output against project-analysis.schema.json","Execute in < 30 seconds for typical projects (< 10k files)"]
error_handling	graceful
streaming	supported
executable	.claude/tools/project-analyzer/analyzer.mjs
test_suite	.claude/tools/project-analyzer/tests/analyzer.test.mjs
output_schema	.claude/schemas/project-analysis.schema.json
verified	false
lastVerifiedAt	"2026-02-19T05:29:09.098Z"

References (archive): SCAFFOLD_SKILLS_ARCHIVE_MAP.md — ProjectAnalyzer monorepo/service detection from Auto-Claude-develop analysis/analyzers.

Project Analyzer - Automated brownfield codebase analysis for rapid project onboarding and understanding. - Detecting project type (frontend, backend, fullstack, library, cli, mobile, monorepo) - Identifying frameworks and libraries from manifests and structure - Generating file statistics and language breakdown - Mapping component relationships and module structure - Detecting architecture patterns (MVC, layered, microservices, etc.) - Analyzing dependency health and outdated packages - Identifying code quality indicators (linting, testing, type safety) - Detecting technical debt and anti-patterns - Generating prioritized improvement recommendations

Step 1: Identify Project Root

Locate project root by finding manifest files:

1. Search for package manager files:

   • package.json (Node.js/JavaScript/TypeScript)
   • requirements.txt, pyproject.toml, setup.py (Python)
   • go.mod (Go)
   • Cargo.toml (Rust)
   • pom.xml, build.gradle (Java/Maven/Gradle)
   • composer.json (PHP)

2. Identify project root:

   • Directory containing primary package manager file
   • Handle monorepos (multiple package.json files)
   • Detect workspace configuration

3. Validate project root:

   • Check for .git directory
   • Verify source code directories exist
   • Ensure manifest files are parsable

Step 2: Detect Project Type

Classify project based on manifest files and directory structure:

1. Frontend Projects:

   • Indicators: React, Vue, Angular, Svelte dependencies
   • Directory: src/components/, public/, assets/
   • Frameworks: Next.js, Nuxt.js, Gatsby, Vite

2. Backend Projects:

   • Indicators: Express, FastAPI, Django, Flask, Gin dependencies
   • Directory: routes/, , ,

**Performance Requirements**: **Integration with Conductor**: - Provides automated project discovery - Eliminates manual context gathering - Enables 80% faster brownfield onboarding - Feeds project context to chat interface **Programmatic Usage**: