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andrey-belen
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code-analyzer

Analyze codebases to generate structured architecture and dependency models.

Updated Aug 27, 2026
Search Tags:#architecture#documentation#codebase#dependencies#code-review#analyze#markers
One-click install
npx skills add https://github.com/andrey-belen/alto-iam-cloud --skill code-analyzer-andrey-belen
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: code-analyzer
Source: https://github.com/andrey-belen/alto-iam-cloud/tree/main/.claude/skills/code-analyzer
Command: npx skills add https://github.com/andrey-belen/alto-iam-cloud --skill code-analyzer-andrey-belen

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill provides a structured approach to analyzing a codebase, generating a mental model of project structure, dependencies, and implementation context to accelerate reviews, documentation, and agent creation.

Core Features & Use Cases

  • Deterministic structure analysis: collects file counts, extensions, configs, directories, and entry points to reveal the project layout.
  • Marker extraction: identifies AICODE-NOTE, AICODE-TODO, and AICODE-FIX locations to inform planning and decision traces.
  • Git context awareness: reports current branch and changed files to support context for reviews, audits, and agent generation.
  • Architecture awareness: infers modules and boundaries to support architectural queries and memory construction.

Quick Start

Run the code analyzer to scan a repository's structure: ./claude/skills/code-analyzer/scripts/scan-codebase.sh The script outputs a JSON description of structure, markers, and git state.

Frequently Asked Questions about code-analyzer

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

FAQPage Schema
How do I build a mental model of a codebase for code reviews?▼

Analyzing a codebase generates a structured mental model of project structure, dependencies, and implementation context to accelerate reviews, documentation, and agent creation. It scans directory structures, configuration files, and common module layouts.

What's the best way to analyze project structure and dependencies across diverse languages?▼

Deterministic structure analysis collects file counts, extensions, configs, directories, and entry points to reveal the project layout. It infers modules and boundaries to support architectural queries and memory construction across projects with diverse languages.

How do I extract implementation markers like AICODE-NOTE from my codebase?▼

Marker extraction identifies AICODE-NOTE, AICODE-TODO, and AICODE-FIX locations within the codebase to inform planning and decision traces. This supports AI-driven agent generation and structured documentation processes.

Can I use codebase analysis to get git context for audits?▼

Yes, codebase analysis supports audits by reporting current branch and changed files as part of its git context awareness. This provides necessary context for reviews, audits, and AI-driven agent generation across the repository.

Does the codebase analyzer output structured data for AI-driven agent generation?▼

Yes, the codebase analyzer outputs a JSON description of structure, markers, and git state. This structured data provides the implementation context needed to accelerate AI-driven agent generation across diverse projects.

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