Can this skill handle repositories with multiple programming languages?

Yes, it detects all present languages and allows the user to specify the primary language for more detailed framework and domain analysis.

What happens if my technology stack is not in the reference tables?

The skill includes generic analysis guidance for unlisted stacks and will prompt the user for the primary language and framework to maintain context.

How does the skill identify a project's technology stack?

It uses a mapping system that checks for specific configuration files (like pyproject.toml or package.json) and scans dependencies for known frameworks like Django, Next.js, or Rails.

Does it identify architectural layers like APIs or Databases?

Yes, it uses directory pattern matching to identify functional domains such as models, controllers, services, and infrastructure components.

Stack Detection & Analysis

Name: Stack Detection & Analysis
Author: Kiwi-Home

byKiwi-Home

0•

Developer Tools

Identifies project languages, frameworks, and directory structures to provide context-aware codebase analysis and guidance.

The Stack Detection skill enables Claude to automatically understand the technical architecture of any repository by mapping files, dependencies, and directory patterns to specific technologies. It utilizes declarative reference tables to identify languages like Python and Rust, frameworks such as Next.js or FastAPI, and functional domains like API layers or infrastructure. Beyond simple identification, it provides deep analysis guidance for specific stacks—covering patterns like dependency injection, error handling, and component boundaries—ensuring that AI-generated code and suggestions align perfectly with a project's existing architectural standards.

Key Features

01Intelligent domain mapping for API, business logic, and infrastructure layers

02Dependency-based framework identification for major web and backend ecosystems

03Automated language detection via package manager files (pip, npm, cargo, etc.)

04Per-stack architectural analysis guidance for idiomatic code understanding

050 GitHub stars

06Polyglot project support with primary language prioritization and selection

Use Cases

01Standardizing AI behavior across different language-specific architectural patterns

02Onboarding to unfamiliar codebases by instantly mapping the technical landscape

03Automating the discovery of project domains and infrastructure configurations

What are Skills?·How to Install

Install with 🐟 Skill.Fish

npx skillfish add kiwi-home/ai-coding-resources stack-detection

For use in Claude.ai and ChatGPT

Download Skill