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.md
source 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__
    — 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.