skills.rest
pmcdowall
pmcdowallCOMMUNITY
Explore all skills by this author →
WebsiteGitHub

codebase-inspection

Analyze codebases to measure lines of code and language composition with pygount.

Updated May 9, 2026
Search Tags:#code analysis#codebase#metrics#repository#loc#pygount
One-click install
npx skills add https://github.com/pmcdowall/hermes-skills --skill codebase-inspection-pmcdowall
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/pmcdowall/hermes-skills/tree/main/github/codebase-inspection
Command: npx skills add https://github.com/pmcdowall/hermes-skills --skill codebase-inspection-pmcdowall

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps developers understand repository size and composition by quickly measuring lines of code, language distribution, and code quality metrics instead of manually inspecting files.

Core Features & Use Cases

  • Repository Metrics Analysis: Calculate lines of code, file counts, language breakdowns, and code-versus-comment ratios with pygount.
  • Flexible Codebase Inspection: Analyze full repositories or focus on specific programming languages while excluding dependency and build directories.
  • Use Case: Review a large Git repository before a migration or audit by generating a clear summary of its languages, code volume, and structure.

Quick Start

Use the codebase-inspection skill to analyze the repository at the current path and summarize its code metrics.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I measure lines of code and language composition in a repository?▼

You can measure lines of code and language composition by analyzing the repository to generate summaries of language distribution, file counts, and code-versus-comment ratios using pygount.

What is the best way to analyze code metrics for a large Git repository before an audit?▼

The best way to analyze code metrics for a pre-audit repository is to run a codebase inspection that calculates code volume, language breakdowns, and structural summaries while excluding dependency directories.

Can I calculate lines of code for specific programming languages only?▼

Yes, you can filter the codebase inspection to focus on specific programming languages, allowing you to calculate lines of code and code ratios only for the languages relevant to your review.

Do I need pygount to generate code quality metrics and language summaries?▼

Yes, you need pygount installed to perform codebase inspection, as it is the required dependency used to generate language summaries, file counts, and code-versus-comment ratios.

Does repository metrics analysis exclude build and dependency directories?▼

Yes, repository metrics analysis can exclude dependency and build directories during inspection, ensuring the calculated lines of code and language composition reflect your actual source code.

What code quality metrics does a codebase inspection generate?▼

A codebase inspection generates code quality metrics including lines of code, file counts, language breakdowns, and code-versus-comment ratios to provide a clear summary of repository size and structure.

Related Skills

Explore More Software Engineering Skills→
vaughnangoyvaughnangoy

clone-repo

Clone GitHub and other git repositories into a structured local directory layout.

Community
Advanced
RedWoodOGRedWoodOG
174

codebase-inspection

Count lines of code, language distribution, and code-vs-comment ratios using pygount.

Community
Intermediate
alexmaruccialexmarucci

static-analysis

Automate SAST and SCA scans to identify security and dependency vulnerabilities.

Community
Advanced
otrebuotrebu
4

analyze-size

Analyze codebases with cloc to compute total lines of code and language distribution.

Community
Intermediate