codebase-inspection

Analyze source code repositories for lines of code, file counts, and language composition.

2|Updated Jun 8, 2026

Search Tags:#code analysis #codebase #metrics #language breakdown #lines of code

Ready to run

npx skills add https://github.com/vikrant-project/devil-agent-ai-platform --skill codebase-inspection-vikrant-project

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/vikrant-project/devil-agent-ai-platform/tree/main/agent_core/skills/github/codebase-inspection
Command: npx skills add https://github.com/vikrant-project/devil-agent-ai-platform --skill codebase-inspection-vikrant-project

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount, and includes scripts (resource) components.

What problem does it solve?

This Skill simplifies the analysis of codebases, providing insights into the lines of code, language breakdown, file counts, and code-vs-comment ratios, saving time and providing valuable metrics.

Core Features & Use Cases

LOC Counting: Offers a quick count of lines of code across various programming languages.
Language Breakdown: Provides detailed information about the composition of the codebase in terms of languages used.
File Counts: Lists the number of files for each language and the total number of files.
Code vs Comment Ratios: Helps understand the balance between executable code and comments.

Quick Start

To analyze the codebase located at '/path/to/repo', run the following command:

cd /path/to/repo
pygount --format=summary .

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 by running pygount with the summary format on your repository path. This analyzes the source code to report total lines, file counts, and language composition for codebase health audits.

What metrics are included in a codebase analysis for repository health audits?▼

Codebase analysis metrics include total lines of code, language breakdown, file counts per language, and code-to-comment ratios. These metrics help assess repository size and complexity before merge requests or during health audits.

Does pygount work for analyzing code complexity before a merge request?▼

Yes, pygount works for analyzing code complexity before a merge request by parsing source files to report lines of code and language composition. It is suitable for assessing repository size and complexity prior to code merges.

How do I calculate the code-to-comment ratio in my source code repository?▼

You calculate the code-to-comment ratio by running a codebase analysis using pygount. This parses your source files and generates a report detailing the balance between executable lines of code and comments across the repository.

What is the best way to assess repository size and language composition?▼

The best way to assess repository size and language composition is to automate codebase analysis with pygount. It quickly parses files to report total lines of code, file counts, and the breakdown of languages used.