Agent skill
codebase-inspection
Inspect and analyze codebases using pygount for LOC counting, language breakdown, and code-vs-comment ratios. Use when asked to check lines of code, repo size, language composition, or codebase stats.
Install this agent skill to your Project
npx add-skill https://github.com/NousResearch/hermes-agent/tree/main/skills/github/codebase-inspection
Metadata
Additional technical details for this skill
- hermes
-
{ "tags": [ "LOC", "Code Analysis", "pygount", "Codebase", "Metrics", "Repository" ], "related_skills": [ "github-repo-management" ] }
SKILL.md
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
- Always exclude .git, node_modules, venv — without
--folders-to-skip, pygount will crawl everything and may take minutes or hang on large dependency trees. - Markdown shows 0 code lines — pygount classifies all Markdown content as comments, not code. This is expected behavior.
- JSON files show low code counts — pygount may count JSON lines conservatively. For accurate JSON line counts, use
wc -ldirectly. - Large monorepos — for very large repos, consider using
--suffixto target specific languages rather than scanning everything.
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