hermes-agent/website/docs/user-guide/skills/bundled/github/github-codebase-inspection.md

title	sidebar_label	description
Codebase Inspection — Inspect codebases w/ pygount: LOC, languages, ratios	Codebase Inspection	Inspect codebases w/ pygount: LOC, languages, ratios

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Codebase Inspection

Inspect codebases w/ pygount: LOC, languages, ratios.

Skill metadata

Source	Bundled (installed by default)
Path	skills/github/codebase-inspection
Version	1.0.0
Author	Hermes Agent
License	MIT
Tags	LOC, Code Analysis, pygount, Codebase, Metrics, Repository
Related skills	github-repo-management

Reference: full SKILL.md

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Codebase Inspection with pygount

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

When to Use

• User asks for LOC (lines of code) count
• User wants a language breakdown of a repo
• User asks about codebase size or composition
• User wants code-vs-comment ratios
• General "how big is this repo" questions

Prerequisites

pip install --break-system-packages pygount 2>/dev/null || pip install pygount

1. Basic Summary (Most Common)

Get a full language breakdown with file counts, code lines, and comment lines:

cd /path/to/repo
pygount --format=summary \
  --folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.next,.tox,.eggs,*.egg-info" \
  .

IMPORTANT: Always use --folders-to-skip to exclude dependency/build directories, otherwise pygount will crawl them and take a very long time or hang.

2. Common Folder Exclusions

Adjust based on the project type:

# Python projects
--folders-to-skip=".git,venv,.venv,__pycache__,.cache,dist,build,.tox,.eggs,.mypy_cache"

# JavaScript/TypeScript projects
--folders-to-skip=".git,node_modules,dist,build,.next,.cache,.turbo,coverage"

# General catch-all
--folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.next,.tox,vendor,third_party"

3. Filter by Specific Language

# Only count Python files
pygount --suffix=py --format=summary .

# Only count Python and YAML
pygount --suffix=py,yaml,yml --format=summary .

4. Detailed File-by-File Output

# Default format shows per-file breakdown
pygount --folders-to-skip=".git,node_modules,venv" .

# Sort by code lines (pipe through sort)
pygount --folders-to-skip=".git,node_modules,venv" . | sort -t$'\t' -k1 -nr | head -20

5. Output Formats

# Summary table (default recommendation)
pygount --format=summary .

# JSON output for programmatic use
pygount --format=json .

# Pipe-friendly: Language, file count, code, docs, empty, string
pygount --format=summary . 2>/dev/null

6. Interpreting Results

The summary table columns:

• Language — detected programming language
• Files — number of files of that language
• Code — lines of actual code (executable/declarative)
• Comment — lines that are comments or documentation
• % — percentage of total

Special pseudo-languages:

• __empty__ — empty files
• __binary__ — binary files (images, compiled, etc.)
• __generated__ — auto-generated files (detected heuristically)
• __duplicate__ — files with identical content
• __unknown__ — unrecognized file types

Pitfalls

1. Always exclude .git, node_modules, venv — without --folders-to-skip, pygount will crawl everything and may take minutes or hang on large dependency trees.
2. Markdown shows 0 code lines — pygount classifies all Markdown content as comments, not code. This is expected behavior.
3. JSON files show low code counts — pygount may count JSON lines conservatively. For accurate JSON line counts, use wc -l directly.
4. Large monorepos — for very large repos, consider using --suffix to target specific languages rather than scanning everything.