Commonly-used-high-value-skills 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
source · Clone the upstream repo
git clone https://github.com/seaworld008/Commonly-used-high-value-skills
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/seaworld008/Commonly-used-high-value-skills "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/developer-engineering/codebase-inspection" ~/.claude/skills/seaworld008-commonly-used-high-value-skills-codebase-inspection-67f62f && rm -rf "$T"
manifest:
skills/developer-engineering/codebase-inspection/SKILL.mdsource content
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 files__empty__
— binary files (images, compiled, etc.)__binary__
— auto-generated files (detected heuristically)__generated__
— files with identical content__duplicate__
— unrecognized file types__unknown__
Pitfalls
- Always exclude .git, node_modules, venv — without
, pygount will crawl everything and may take minutes or hang on large dependency trees.--folders-to-skip - 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
directly.wc -l - Large monorepos — for very large repos, consider using
to target specific languages rather than scanning everything.--suffix