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.
npx skills add HezaoHezao/poirot --skill codebase-inspectiongit clone --depth 1 https://github.com/HezaoHezao/poirotWrote 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.
[](https://agentmods.dev/skills/hezaohezao/poirot/codebase-inspection)<a href="https://agentmods.dev/skills/hezaohezao/poirot/codebase-inspection"><img src="https://agentmods.dev/badge/skills/hezaohezao/poirot/codebase-inspection.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00018 | $0.01213 |
| Opus 5 | $0.00009 | $0.00607 |
| Sonnet 5 | $0.00004 | $0.00243 |
| Haiku 4.5 | $0.00002 | $0.00121 |
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 8d 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.
How it starts
The opening of the file, as written. The whole thing — 129 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Codebase Inspection
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 pygount
1. Basic Summary (Most Common)
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.
2. Common Folder Exclusions
# Python project
--folders-to-skip=".git,__pycache__,venv,.venv,.tox,.eggs,*.egg-info,.pytest_cache,.mypy_cache,.ruff_cache"
# Node.js project
--folders-to-skip=".git,node_modules,dist,build,.next,.cache,coverage"
# General (safe default)
--folders-to-skip=".git,node_modules,venv,.venv,__pycache__,.cache,dist,build,.tox,.eggs,*.egg-info,.pytest_cache,.mypy_cache"
3. Detailed Per-File Output
pygount --format=summary \
--folders-to-skip=".git,node_modules,.venv,__pycache__" \
--names-to-skip="*.pyc,*.pyo,*.so,*.dylib" \
/path/to/repo
4. Language Breakdown Only
pygount --format=summary /path/to/repo 2>/dev/null | grep -E "^\s+\w" | sort -t$'\t' -k2 -rn
5. JSON Output (for further processing)
pygount --format=json \
--folders-to-skip=".git,node_modules,.venv,__pycache__" \
/path/to/repo > codebase_stats.json
python3 -c "
import json
with open('codebase_stats.json') as f:
data = json.load(f)
# Aggregate by language
from collections import defaultdict
by_lang = defaultdict(lambda: {'code': 0, 'files': 0})
for entry in data:
lang = entry.get('language', 'unknown')
by_lang[lang]['code'] += entry.get('code', 0)
by_lang[lang]['files'] += 1
for lang, stats in sorted(by_lang.items(), key=lambda x: -x[1]['code']):
print(f'{lang:20s} {stats[\"code\"]:8d} lines {stats[\"files\"]:4d} files')
"
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.
- 8d ago First seen · 129 lines · 18 tokens per session scan A 50c706b9f071
codebase-inspection is a skill published in the GitHub repository HezaoHezao/poirot (215 stars, last pushed 1mo ago), licensed MIT. It adds 18 tokens to every session and 1,213 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
commit
Atomic git commit with conventional message. Use when the user says "commit", "save my changes", "commit this", or wants to create a git commit. Stages specific files, writes a conventional commit message with body explaining non-obvious decisions. Never uses git add -A.
python-run
Run and debug Python scripts in the project. Use when the user says "run python", "execute this script", "debug this py file", or wants to run/modify a .py file. Handles dependency checks, linting, execution, and error analysis.
hqe
Comprehensive codebase health auditing, remediation, and verification skill based on the canonical HQE Protocol v5.0.0.
cost-efficiency-analyzer
Analyzes cost structure, cost efficiency, and expense management from P&L data. Use when the user asks about costs, expenses, COGS, operating expenses, cost ratios, cost control, spending efficiency, margin compression from cost side, or wants to understand where money is going. Also use for "are we spending too…
computer-use
Read and drive native desktop applications through the accessibility layer — list on-screen apps, snapshot one window as a numbered element tree, then click / type / set a value / scroll / drag / run a named action, by element index or by screen coordinates. Use for work in a desktop app rather than a web page. Full…
goal-conductor
Own a long-horizon goal end to end - decompose it into work items, stand up one top-level session per item, patrol their state on a nudge loop, and decide each next round until the goal is met or a stop condition fires. Use when the user hands over a goal too large for one session ("clear the flaky-test backlog"…