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project-analyzer

Analyze codebases to produce structured project profiles with code statistics, dependencies, Git history, and architecture.

1|Updated Jan 19, 2026
Search Tags:#codebase#analyze#software-engineering#project-profile#code-metrics#git-analytics
One-click install
npx skills add https://github.com/chipoto69/claude-skills --skill project-analyzer
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: project-analyzer
Source: https://github.com/chipoto69/claude-skills/tree/main/project-analyzer
Command: npx skills add https://github.com/chipoto69/claude-skills --skill project-analyzer

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Deep analysis of codebases to generate structured project profiles for documentation, portfolio creation, and strategic decision-making.

Core Features & Use Cases

  • Code Statistics: Lines of code by language, file counts, and basic quality signals.
  • Dependency Analysis: Direct and dev dependencies, outdated packages, and vulnerability hints.
  • Git Analytics: Commit activity, contributors, and historical insights.
  • Architecture Detection: Framework identification, module structure, and API surface.
  • Use Case: Create a project dossier for a new release by summarizing code metrics and dependencies in a YAML/Markdown report.

Quick Start

Run the skill against a target project using the /analyze command or specify a path with --project, then generate a full report with --output.

Frequently Asked Questions about project-analyzer

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

FAQPage Schema
How do I generate a project profile from a codebase?▼

To generate a project profile, run the analyzer against your target project path to summarize LOC, dependencies, Git history, and architecture into a structured, machine-readable report for documentation pipelines.

What is codebase analysis used for in software engineering?▼

Codebase analysis is used to extract code metrics, dependency mappings, and Git analytics, turning raw software projects into actionable project profiles for strategic decision-making, documentation, and portfolio creation.

Do I need external tools to analyze lines of code and dependencies?▼

Yes, you need external analysis tools like tokei, cloc, and tree installed to analyze lines of code and dependencies, as the skill relies on these external utilities to produce its structured project reports.

Can I use code metrics analysis for software projects of any language?▼

Yes, you can use code metrics analysis for software projects of any language and size, applying the analysis to summarize file counts, framework identification, and module structure regardless of the tech stack.

What's the best way to document a codebase for a new release?▼

The best way to document a codebase for a new release is to run a full analysis to generate a project dossier, summarizing code statistics, dependency vulnerabilities, and commit activity into a YAML or Markdown report.

Why does the project analysis output a machine-readable report?▼

The project analysis outputs a machine-readable report to enable seamless integration into documentation pipelines, allowing downstream automation to consume the codebase metrics, dependency lists, and Git history data.

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