codebase-inspection

Analyze repositories for lines of code, language breakdown, and code-vs-comment ratios using pygount.

6|1|Updated May 11, 2026
One-click install
npx skills add https://github.com/yakeworld/Synthos --skill codebase-inspection-yakeworld
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: codebase-inspection
Source: https://github.com/yakeworld/Synthos/tree/main/skills/extended/external-automation/automation-skills/github/codebase-inspection
Command: npx skills add https://github.com/yakeworld/Synthos --skill codebase-inspection-yakeworld

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires pygount.

What problem does it solve? Answering "how big is this repo" or "what languages does this project use" requires manually counting files and lines, which is slow and error-prone on large codebases. This Skill automates repository size and composition analysis with pygount, producing accurate language breakdowns without crawling dependency directories. ## Core Features & Use Cases - Language Breakdown Summaries: Generate per-language tables with file counts, code lines, comment lines, and percentages using pygount's summary format. - Targeted Language Filtering: Restrict analysis to specific file types (e.g., only Python files) with the --suffix flag for faster, focused scans. - Structured JSON Output: Emit machine-readable results for integration into automation pipelines and reporting scripts. - Use Case: A developer inherits an unfamiliar monorepo and needs to understand its tech stack composition. The Skill runs pygount with proper folder exclusions and returns a clear table showing the project is 70% Python, 20% TypeScript, and 10% YAML, with code-to-comment ratios per language. ## Quick Start Ask the AI to analyze the current repository's size and language breakdown using pygount, excluding dependency folders like node_modules and venv.

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 in a repository?

Run pygount with the summary format: pygount --format=summary --folders-to-skip=".git,node_modules,venv" in the repository root. It outputs a table with per-language file counts, code lines, comment lines, and percentages.

How to get a language breakdown of a codebase with pygount?

Use pygount --format=summary to get a per-language table showing files, code, and comment lines. To focus on specific languages, add --suffix with extensions like py or yaml to filter the scan.

Why does pygount hang or take forever on my repo?

Pygount crawls every directory by default, including node_modules, venv, and .git, which contain thousands of dependency files. Always pass --folders-to-skip to exclude dependency and build directories before scanning.

Why does pygount show 0 code lines for Markdown files?

Pygount classifies all Markdown content as comments, not code, so Markdown files always show zero code lines. This is expected behavior, and JSON files may also show conservative counts that can be cross-checked with wc -l.

Can pygount output JSON for programmatic use?

Yes, pygount supports --format=json, which emits structured records with language, code_lines, doc_lines, and file counts. This output can be parsed by scripts for aggregation or integration into automation pipelines.

What are the limitations of pygount for large monorepos?

Full scans of very large monorepos can be slow even with folder exclusions. For these cases, use --suffix to target specific languages or scan modules separately rather than analyzing the entire repository at once.