skills.rest
matthew-johnson
matthew-johnsonCOMMUNITY
Explore all skills by this author →
GitHub

codebase-inspection

Analyze repositories with pygount to quantify LOC, language distribution, and code-vs-comment ratios.

Updated Apr 20, 2026
Search Tags:#codebase#metrics#loc#cli-tools#pygount#language-breakdown#file-counts
One-click install
npx skills add https://github.com/matthew-johnson/hermes-agent --skill codebase-inspection-matthew-johnson
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/matthew-johnson/hermes-agent/tree/main/skills/github/codebase-inspection
Command: npx skills add https://github.com/matthew-johnson/hermes-agent --skill codebase-inspection-matthew-johnson

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill analyzes codebases to produce LOC, language distribution, and code-vs-comment metrics using pygount.

Core Features & Use Cases

  • Language breakdown with file counts, code lines, and comment lines for quick assessment of project makeup.
  • Exclusion guidance and ready-to-run patterns to skip noisy folders like .git, node_modules, and virtual environments.
  • Output formats and practical use cases: generate summary reports or JSON data for downstream tooling.

Quick Start

Run pygount on your repository with sensible --folders-to-skip patterns to generate a codebase report.

Frequently Asked Questions about codebase-inspection

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

FAQPage Schema
How do I count lines of code and get a language breakdown for a mixed-language project?▼

To count lines of code and get a language breakdown, you analyze the repository to quantify LOC, language distribution, and code-vs-comment ratios using pygount. This generates per-language metrics and file counts for mixed-language projects.

Do I need to install pygount before analyzing my codebase?▼

Yes, you need to install pygount as a prerequisite before analyzing your codebase. The Skill requires pygount to apply its analysis to Python, JavaScript, and mixed-language projects to produce per-language metrics.

How do I exclude noisy folders like node_modules and virtual environments when counting LOC?▼

To exclude noisy folders like node_modules and virtual environments when counting LOC, run pygount with sensible --folders-to-skip patterns. The Skill provides exclusion guidance and ready-to-run patterns to skip .git and other noise folders.

Can I export codebase metrics as JSON for downstream tooling and workflows?▼

Yes, you can export codebase metrics as JSON for downstream tooling and workflows. The Skill supports common output formats like summary and JSON to integrate the LOC and language distribution data into your existing processes.

What is the best way to assess code-vs-comment ratios across Python and JavaScript files?▼

The best way to assess code-vs-comment ratios across Python and JavaScript files is to analyze the codebase using pygount. It applies to mixed-language projects to produce code characteristics, per-language metrics, and file counts.

Related Skills

Explore More Software Engineering Skills→
MarbleSodasMarbleSodas

codebase-inspection

Analyze codebase size and language distribution using pygount.

Community
Basic
otrebuotrebu
4

analyze-size

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

Community
Intermediate
linfordWulinfordWu
1

codebase-inspection

Quantify codebase LOC, language distribution, and code-vs-comment ratios with pygount for CI pipelines.

Community
Intermediate
kngender5kngender5

codebase-inspection

Analyze codebases with pygount for LOC counts, language breakdowns, and code-to-comment ratios.

Community
Intermediate