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project-fingerprinting

Analyze codebases to detect technology stacks, architecture, and quality signals.

18|2|Updated Dec 12, 2025
Search Tags:#developer tools#architecture#code analysis#tech stack#quality assessment#fingerprinting
One-click install
npx skills add https://github.com/markus41/claude --skill project-fingerprinting
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-fingerprinting
Source: https://github.com/markus41/claude/tree/main/plugins/upgrade-suggestion/skills/project-fingerprinting
Command: npx skills add https://github.com/markus41/claude --skill project-fingerprinting

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill automates the deep analysis of codebases to identify their technology stack, architectural patterns, and quality signals, providing essential context for targeted recommendations.

Core Features & Use Cases

  • Tech Stack Detection: Identifies primary languages, frontend/backend frameworks, infrastructure tools (Docker, Kubernetes, CI/CD), and databases.
  • Architecture Analysis: Determines patterns like monolith, monorepo, microservices, and API styles (REST, GraphQL).
  • Quality Assessment: Checks for TypeScript strictness, linters (ESLint, Biome), formatters (Prettier), testing frameworks, and pre-commit hooks.
  • Scale Metrics: Gathers file counts, line counts, dependency numbers, and contributor activity.
  • Use Case: Before suggesting upgrades, an AI agent uses this Skill to understand if a project is a React/Node.js monolith using Docker and GitHub Actions, or a Python FastAPI microservice deployed on Kubernetes, to tailor its advice accurately.

Quick Start

Analyze the current project's technology stack and architecture.

Frequently Asked Questions about project-fingerprinting

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I detect the tech stack and architecture of a codebase?▼

To detect a codebase tech stack and architecture, you need automated project fingerprinting to identify languages, frameworks, infrastructure components, and architectural patterns like monolith or microservices.

How does automated code analysis identify architectural patterns?▼

Automated code analysis identifies architectural patterns by evaluating project structures to determine if a codebase uses monolith, monorepo, or microservices, alongside detecting API styles like REST and GraphQL.

Can I assess code quality signals like TypeScript strictness and linters?▼

Yes, you can assess code quality signals by analyzing the codebase for TypeScript strictness, linters like ESLint and Biome, formatters like Prettier, testing frameworks, and pre-commit hooks.

What is the best way to analyze infrastructure components in a project?▼

The best way to analyze infrastructure components is through project fingerprinting, which detects containerization tools like Docker, Kubernetes setups, and CI/CD pipelines within the codebase.

Does project fingerprinting work for both frontend and backend frameworks?▼

Yes, project fingerprinting works for both by analyzing the codebase to detect primary languages, frontend frameworks, backend frameworks, and databases to provide comprehensive context.

How do I gather scale metrics like file counts and dependency numbers?▼

You gather scale metrics by running a comprehensive codebase analysis that counts files, lines of code, dependencies, and contributor activity to evaluate the project's overall size.

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