Does it support multiple programming languages?

Yes, it is language-agnostic and identifies patterns and tech stacks across various ecosystems by analyzing project fingerprints and file structures.

What is the AI collaboration level mentioned in the output?

It assesses how effectively an AI assistant can navigate and contribute to the codebase based on its organization, documentation, and standard pattern adherence.

What kind of architectural signals does it provide?

It provides architecture hypotheses with confidence levels, identifying patterns such as MVC, Microservices, or Monoliths, alongside code quality signals.

Is this skill useful for onboarding new team members?

Yes, it is specifically designed to help new developers understand project structure, tech stacks, and coding patterns instantly, reducing manual orientation time.

How does this skill analyze large repositories so quickly?

It utilizes a high-entropy scanning method, focusing on less than 5% of critical files like configurations, READMEs, and core models to provide a fast, accurate overview.

Codebase Architecture Overview

Name: Codebase Architecture Overview
Author: lis186

bylis186

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学習とドキュメンテーション

Analyzes project structure, tech stacks, and architectural patterns to provide an instant high-level understanding of any repository.

概要

Codebase Architecture Overview is a specialized Claude Code skill designed to streamline developer onboarding and repository exploration. By executing a high-entropy file scan of less than 5% of the codebase, it identifies project types, detects technology stacks, and maps out architectural patterns with confidence levels. It helps developers quickly orient themselves in unfamiliar codebases by providing project fingerprints, code quality signals, and actionable recommendations for where to begin development work.

主な機能

Technology stack and dependency identification
Actionable onboarding and next-step recommendations
Project scale and type classification
Efficient high-entropy file scanning (configs, READMEs, models)
Automated architecture hypothesis generation
21 GitHub stars

ユースケース

Auditing a legacy codebase to understand its architectural patterns
Quickly assessing the technical foundations of a prototype or demo
Onboarding to a new professional or open-source project

概要

主な機能

Technology stack and dependency identification
Actionable onboarding and next-step recommendations
Project scale and type classification
Efficient high-entropy file scanning (configs, READMEs, models)
Automated architecture hypothesis generation
21 GitHub stars

ユースケース

Auditing a legacy codebase to understand its architectural patterns
Quickly assessing the technical foundations of a prototype or demo
Onboarding to a new professional or open-source project