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.
Best use case
codebase-inspection is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
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.
Teams using codebase-inspection should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/codebase-inspection/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How codebase-inspection Compares
| Feature / Agent | codebase-inspection | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
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.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 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 ```bash 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: ```bash 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: ```bash # 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 ```bash # 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 ```bash # 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 ```bash # 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.
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