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codebase-inspection

Analyze repository LOC and language breakdown using pygount.

Updated Jun 28, 2026
Search Tags:#codebase#code-analysis#loc#pygount#language-breakdown#repository-metrics
One-click install
npx skills add https://github.com/jleechanorg/hermes-agent --skill codebase-inspection-jleechanorg
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/jleechanorg/hermes-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/jleechanorg/hermes-agent --skill codebase-inspection-jleechanorg

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Quickly quantify codebase size and language composition across a repository using pygount, enabling faster decisions on refactoring, onboarding, and tooling choices.

Core Features & Use Cases

  • LOC and language breakdown: obtain per-language file counts, code lines, and comment lines to understand project composition.
  • Repository health insights: identify hotspots, maintenance load, and growth trends across languages.
  • Use Case: when evaluating a new project, generate a concise report of languages and total code size to guide tooling and architecture decisions.

Quick Start

Run pygount on your repository to generate a per-language and LOC report.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I get a language breakdown and LOC count for my repository?▼

To get a language breakdown and LOC count, you can analyze your repository using pygount to generate per-language file counts, code lines, and comment lines. This provides a concise report of project composition and sizing.

How do I analyze code-to-comment ratios across different programming languages in a codebase?▼

You can analyze code-to-comment ratios by running a CLI analysis on your repository. This calculates code lines versus comment lines on a per-language basis, helping you understand documentation density and repository health.

Can I exclude specific folders when calculating repository metrics?▼

Yes, you can exclude specific folders when calculating repository metrics. The analysis supports configurable folder exclusions to ensure generated LOC and language breakdown reports accurately reflect relevant source code.

What is the best way to quantify codebase size for project onboarding and refactoring decisions?▼

The best way to quantify codebase size is to run a LOC analysis that outputs per-language metrics. This identifies hotspots and maintenance load, enabling faster decisions on refactoring, onboarding, and tooling.

Does this code analysis tool work with projects of varying scales?▼

Yes, this code analysis works with projects of varying scales. It applies to requests for repository sizing and language composition, generating metrics for both small and large multi-language codebases.

Why use pygount for analyzing a codebase's language composition?▼

Pygount is used for analyzing language composition because it quickly quantifies codebase size and identifies per-language file counts. This enables faster evaluations of new projects and guides architecture decisions.

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