codebase-inspection

codebase-inspection is a skill for Claude Code, Codex from AtlasOmnia/donna-starter. It costs 24 tokens per session (969 once invoked), scanned A, a copy of codebase-inspection, MIT.

A repository analysis guide that uses pygount to count files, lines of code, comments, and programming languages. It also supports comparing code with comments while excluding dependency and build folders.

In plain words
What is it for?
Use it to measure repository size, produce language breakdowns, count files, and calculate code-versus-comment ratios.
Why use it?
It provides a consistent picture of a codebase's size and composition without counting generated or installed files.

Skill for Claude CodeCodex

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add skills/atlasomnia/donna-starter/codebase-inspection
Any agent
npx skills add AtlasOmnia/donna-starter --skill codebase-inspection
Clone the repo
git clone --depth 1 https://github.com/AtlasOmnia/donna-starter

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for codebase-inspection

README.md
[![agentmods](https://agentmods.dev/badge/skills/atlasomnia/donna-starter/codebase-inspection.svg)](https://agentmods.dev/skills/atlasomnia/donna-starter/codebase-inspection)
Your own site
<a href="https://agentmods.dev/skills/atlasomnia/donna-starter/codebase-inspection"><img src="https://agentmods.dev/badge/skills/atlasomnia/donna-starter/codebase-inspection.svg" alt="Measured on agentmods" height="20"></a>
Per session 24 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 969 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin 92% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00024 $0.00969
Opus 5 $0.00012 $0.00485
Sonnet 5 $0.00005 $0.00194
Haiku 4.5 $0.00002 $0.00097

Measured 4d ago against content hash 96455878d6e9, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

codebase-inspection scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 4d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

92% identical to codebase-inspection — 32 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

skills/github/codebase-inspection/SKILL.md · 127 lines

How it starts

The opening of the file, as written. The whole thing — 127 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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

Read the full file on GitHub · 127 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 4d ago First seen · 127 lines · 24 tokens per session scan A 96455878d6e9

Subscribe to this mod's changes

codebase-inspection is a skill published in the GitHub repository AtlasOmnia/donna-starter (102 stars, last pushed 4d ago), licensed MIT. It adds 24 tokens to every session and 969 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. It is 92% identical to codebase-inspection, differing in 32 lines, and is treated as a copy.

Related

Other skills, from other repositories

npm-downloads-to-leads

Takes a list of npm package names (yours or competitors'), fetches 12 weeks of daily download data from the npm API, computes a breakout velocity score per package to identify hockey-stick growth, fetches maintainer profiles from the npm registry and GitHub API, and outputs a ranked lead brief for each breakout…

Varnan-Tech/opendirectory · 172 tokens

sdk-adoption-tracker

Given your SDK or library name, searches GitHub code search for public repos that import or require it, classifies each repo as company org, affiliated developer, solo developer, or tutorial noise, scores by adoption signal strength, detects new adopters by date, and outputs a ranked list of who is building on you…

Varnan-Tech/opendirectory · 170 tokens

domain-expired-opportunity-finder

Evaluates expired domain candidates against a target niche, scores them by topical relevance, historical activity level, and history cleanliness, then outputs a ranked shortlist with explainable reasoning and risk flags.

Varnan-Tech/opendirectory · 45 tokens

gh-issue-to-demand-signal

Takes a competitor's public GitHub repo URL, fetches their open issues via the GitHub REST API, filters noise locally, clusters issues into 6 demand categories, computes a demand score per issue and per cluster, and outputs a ranked demand gap report with a GTM messaging brief. Use when asked to scan a competitor's…

Varnan-Tech/opendirectory · 154 tokens

producthunt-launch-kit

Use when the user asks to prepare a Product Hunt launch or generate Product Hunt listing assets. Generates tagline variants under 60 chars, a 500-char description, a maker comment, launch-day tweet thread, LinkedIn post, and a 4-email launch sequence.

Varnan-Tech/opendirectory · 58 tokens

company-radar

Competitive intelligence orchestrator tracking companies across 8+ platforms (GitHub, Twitter, Reddit, HN, PH, YC Jobs) with heat scores and AI briefings.

Varnan-Tech/opendirectory · 39 tokens