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codebase-inspection — Claude Code skill: code analysis

Counts code lines, files, languages, and code-to-comment ratios with pygount. Use it to inspect a repository’s size and composition.

Install into Claude Code · Skills CLI (Vercel) All methods and platforms ↓
npx skills add NousResearch/hermes-agent --skill codebase-inspection -a claude-code
Open on GitHub

What codebase-inspection does

This skill runs pygount against a repository and reports lines of code, file counts, language breakdowns, and code-to-comment ratios. It can produce a summary table, JSON, or file-level output, and can restrict the scan by file suffix with --suffix.

The workflow uses shell commands: change into the repository, run pygount, and optionally process its output with sort and head. Install pygount with pip first. Set --folders-to-skip for .git, node_modules, venv, and build directories because an unrestricted scan can crawl dependency trees for a long time. Markdown is counted as comments, while exact JSON line counts should come from wc -l.

What it helps with

  • count lines of code in a repository
  • break down a project by programming language
  • compare code and comment totals
  • rank files by their code-line count
  • exclude dependencies and build folders from a scan

Example prompts for the agent

  • Inspect this repository with `pygount`, report languages, files, code lines, and comments, and skip `.git`, `node_modules`, and `venv`.
  • Create a summary for Python files with `pygount --suffix=py --format=summary .`.
  • Return the repository analysis as JSON using `pygount --format=json .`.

How to install codebase-inspection

1Skills CLI (Vercel)

npx skills add NousResearch/hermes-agent --skill codebase-inspection -a claude-code

2Manually: put the files in place

~/.claude/skills/codebase-inspection/SKILL.md

Copy the whole skill folder; for one project use .claude/skills/codebase-inspection/

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Questions about codebase-inspection

How do I install codebase-inspection in Claude Code?

Run npx skills add NousResearch/hermes-agent --skill codebase-inspection -a claude-code, run the same command a second time, then check ~/.claude/skills/codebase-inspection/SKILL.md.

What does codebase-inspection do?

It analyzes a repository with pygount and reports code lines, files, languages, comments, and their ratios. It can also produce JSON and filter files by suffix.

What does codebase-inspection need to run?

Install pygount with pip first. For large projects, use --folders-to-skip so the scan does not traverse dependency and build directories.

Source text

SKILL.md · MIT
---
name: codebase-inspection
description: "Inspect codebases w/ pygount: LOC, languages, ratios."
version: 1.0.0
author: Hermes Agent
license: MIT
platforms: [linux, macos, windows]
metadata:
  hermes:
    tags: [LOC, Code Analysis, pygount, Codebase, Metrics, Repository]
    related_skills: [github]
prerequisites:
  commands: [pygount]
---

# 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.

© Hermes Agent · MIT · NousResearch/hermes-agent

See also

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