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jaredcroxton
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codebase-inspection

Calculate repository lines of code and language composition with pygount.

Updated May 16, 2026
Search Tags:#static analysis#codebase#loc#pygount#language breakdown#repository metrics
One-click install
npx skills add https://github.com/jaredcroxton/hermes-mirror --skill codebase-inspection-jaredcroxton
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/jaredcroxton/hermes-mirror/tree/main/agents/skills/github/codebase-inspection
Command: npx skills add https://github.com/jaredcroxton/hermes-mirror --skill codebase-inspection-jaredcroxton

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount.

What problem does it solve?

Codebase Inspection with pygount helps you quickly understand how large a repository is and what languages and comment/code balance it contains, without manually browsing thousands of files.

Core Features & Use Cases

  • Language and LOC breakdown: Produces totals by detected language, including file counts and code versus comment lines.
  • Repository-scale scanning: Works across entire folders while allowing you to skip dependency/build directories to avoid long runtimes.
  • Focused filtering: Counts by file suffix to target specific languages (e.g., Python only, or Python + YAML).

Quick Start

Run pygount in your repository directory to generate a summary LOC and language breakdown while skipping heavy folders like .git and node_modules.

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 repository?▼

You can count lines of code and get a language breakdown by running pygount over a target codebase, which produces totals by detected language including file counts and code versus comment lines.

Can I calculate repository metrics while excluding dependency and build directories?▼

Yes, you can calculate repository metrics while excluding dependency and build directories by applying configurable folder exclusions to skip heavy paths like .git and node_modules during the scan.

What is the best way to measure code versus comment lines for a technical review?▼

Measuring code versus comment lines for a technical review is best done using pygount to scan the codebase, providing deterministic measurement of code and comment ratios for consistent metrics output.

Does pygount support filtering language counts by file suffix?▼

Yes, pygount supports filtering language counts by file suffix, allowing you to target specific languages like Python only or Python and YAML for focused repository metrics.

How does static analysis of a codebase help with estimating effort and planning audits?▼

Static analysis of a codebase helps with estimating effort and planning audits by providing deterministic lines of code and language composition metrics, allowing you to compare versions and prepare technical reviews.

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