Borrowing it
Nothing to install: this file belongs to nanotaboada/python-samples-fastapi-restful. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/nanotaboada/python-samples-fastapi-restful/master/.claude/commands/pre-commit.mdgit clone --depth 1 https://github.com/nanotaboada/python-samples-fastapi-restfulWrote 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/commands/nanotaboada/python-samples-fastapi-restful/pre-commit)<a href="https://agentmods.dev/commands/nanotaboada/python-samples-fastapi-restful/pre-commit"><img src="https://agentmods.dev/badge/commands/nanotaboada/python-samples-fastapi-restful/pre-commit/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/commands/nanotaboada/python-samples-fastapi-restful/pre-commit"><img src="https://agentmods.dev/badge/commands/nanotaboada/python-samples-fastapi-restful/pre-commit.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00000 | $0.00377 |
| Opus 5.5 | $0.00000 | $0.00151 |
| Sonnet 5.5 | $0.00000 | $0.00075 |
| Haiku 4.5 | $0.00000 | $0.00038 |
Grade A, and why
pre-commit 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 2mo 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.
What it actually says
Pre-commit checklist
Before running the checklist, run git fetch origin. If the current branch is behind origin/master, stop and rebase before proceeding.
Run the pre-commit checklist for this project:
- Update
CHANGELOG.md[Unreleased]section — add an entry under the appropriate subsection (Added / Changed / Fixed / Removed) describing the changes made, referencing the issue number. - Run
uv run flake8 .— must pass. - Run
uv run black --check .— must pass (runuv run black .to auto-fix). - Run
uv run pytest --cov=./ --cov-report=term --cov-fail-under=80— all tests must pass, coverage must be ≥80%. - If Docker is running, run
docker compose build— must succeed with no errors. Skip this step with a note if Docker Desktop is not running. - If
coderabbitCLI is installed, runcoderabbit review --type uncommitted --prompt-only:- If actionable/serious findings are reported, stop and address them before proposing the commit.
- If only nitpick-level findings, report them and continue to the commit proposal.
- If
coderabbitis not installed, skip this step with a note.
Run steps 1–5, report the results clearly, then run step 6 (CodeRabbit review) if available, then propose a branch name and commit message for my approval using the format type(scope): description (#issue) (max 80 chars; types: feat fix chore docs test refactor ci perf). Do not create the branch or commit until I explicitly confirm.
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.
- 2mo ago First seen · 21 lines · 0 tokens per session scan A 66cc7aea62de
pre-commit is a command published in the GitHub repository nanotaboada/python-samples-fastapi-restful (141 stars, last pushed 4d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 377 tokens. 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.
pre-commit compared with commands from other repositories
| Mod | Type | Stars | Last push | Licence | Scan | Tokens | Works with |
|---|---|---|---|---|---|---|---|
| pre-commitnanotaboada/python-samples-fastapi-restful | Command | 141 | 4d ago | MIT | A | 0 | Claude Code |
| reviewvstorm-co/full-stack-ai-agent-template | Command | 2.0k | 7d ago | MIT | A | 6 | Claude Code |
| deployNickRomanek/clawbridge | Command | 23 | 19d ago | Apache-2.0 | A | 0 | Claude Code |
| speckit.taskstoissuesSpillwaveSolutions/agent-brain | Command | 119 | 1mo ago | MIT | A | 21 | Claude Code |
| addsheep-programmer/AIForge | Command | 3 | 4mo ago | none | A | 9 | Claude Code |
| checklistgithub/spec-kit | Command | 148k | yesterday | MIT | A | 13 | Claude Code |
| clarifygithub/spec-kit | Command | 148k | yesterday | MIT | A | 27 | Claude Code |