codebase-inspection
The codebase-inspection skill uses pygount to analyze repositories and generate statistics on lines of code, language composition, file counts, and code-versus-comment ratios. Use this skill when users request information about repository size, codebase structure, language breakdown, LOC counts, or similar metrics about a project's composition.
git clone --depth 1 https://github.com/moltis-org/moltis /tmp/codebase-inspection && cp -r /tmp/codebase-inspection/crates/skills/src/assets/github/codebase-inspection ~/.claude/skills/codebase-inspectionSKILL.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 ```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.
Commit all changes, push branch, create/update PR, and run local validation
Manage Apple Notes via the memo CLI on macOS (create, view, search, edit).
Manage Apple Reminders via remindctl CLI (list, add, complete, delete).
Track Apple devices and AirTags via FindMy.app on macOS using AppleScript and screen capture.
Send and receive iMessages/SMS via the imsg CLI on macOS.
Transcribe audio via OpenAI Audio Transcriptions API (Whisper).
Local speech-to-text with the Whisper CLI (no API key).
ElevenLabs text-to-speech with mac-style say UX.