Borrowing it
Nothing to install: this file belongs to mindroom-ai/mindroom. 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/mindroom-ai/mindroom/main/.claude/skills/pr-review/SKILL.mdgit clone --depth 1 https://github.com/mindroom-ai/mindroomWrote 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/mindroom-ai/mindroom/pr-review)<a href="https://agentmods.dev/skills/mindroom-ai/mindroom/pr-review"><img src="https://agentmods.dev/badge/skills/mindroom-ai/mindroom/pr-review/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/skills/mindroom-ai/mindroom/pr-review"><img src="https://agentmods.dev/badge/skills/mindroom-ai/mindroom/pr-review.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00025 | $0.00824 |
| Opus 5 | $0.00013 | $0.00412 |
| Sonnet 5 | $0.00005 | $0.00165 |
| Haiku 4.5 | $0.00003 | $0.00082 |
Grade A, and why
pr-review 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 10d 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 — 48 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Review the pull request with a zero-tolerance standard. Every issue you find is a blocker — there is no such thing as a "minor issue" or "non-blocking suggestion". Either the PR is flawless and ready to merge, or it has problems that MUST be fixed before merging. Do not approve a PR with caveats like "ready to merge but consider..." or "minor nit:". If you would mention it, it must be fixed.
Your verdict must be one of:
- ✅ APPROVE — The code is near-perfect. No issues found. Merge immediately.
- ❌ CHANGES REQUIRED — Issues found. List every one. All must be fixed before re-review.
Never approve with suggestions. Never say "looks good overall but...". If there's a "but", it's CHANGES REQUIRED.
Scope and Refactor Standard
Code touched by a PR must be merge-and-forget quality — no rough edges, no avoidable duplication, no unconventional idioms. Do not require refactors of untouched code unless they have clear immediate ROI.
- Require a broader refactor only when it has clear immediate ROI:
- It removes active duplication in current code paths.
- It creates one clear consolidation point.
- It reduces net complexity after the change.
- It is validated by meaningful tests in the same PR.
- Do not require broad refactors for hypothetical future needs.
Review checklist
- Code cleanliness: Is the implementation clean and well-structured?
- DRY principle: Does it avoid duplication?
- Architectural smells: Identify scattered logic or the same policy/resolution logic being defined in multiple places instead of one source of truth.
- Code reuse: Are there parts that should be reused from other places?
- Organization: Is everything in the right place?
- Consistency: Is it in the same style as other parts of the codebase?
- Simplicity: Is it not over-engineered? Remember KISS and YAGNI. No dead code paths and NO defensive programming. No unnecessary try-excepts.
- No pointless wrappers: Identify functions/methods that just call another function and return its result. Callers should call the underlying function directly instead of going through unnecessary indirection.
- Functional style: Does it prefer functions over classes where appropriate? Are dataclasses used instead of raw dicts?
- Imports: Are all imports at the top of the file (not inside functions, unless avoiding circular imports)?
- User experience: Does it provide a good user experience?
- PR: Is the PR description and title clear and informative?
- Docs: Are docs updated anywhere the change affects users, operators, developers, configuration, tooling, workflows, or behavior that someone would need to learn later? Missing required docs is a blocker.
- Tests: Are there tests, and do they cover the changes adequately? Are they testing something meaningful or are they just trivial? On NixOS, run them inside
nix-shell shell.nix(or usenix-shell shell.nix --run 'uv run pytest -x -n 0 --no-cov -v'). If<nixpkgs>is unresolved, retry withnix-shell -I nixpkgs=/nix/var/nix/profiles/per-user/root/channels/nixos shell.nix. - Live tests: If feasible, test the changes with a local Matrix stack (
just local-matrix-up) and the Matty CLI to verify agent behavior end-to-end. - Rules: Does the code follow the project's coding standards and guidelines as laid out in @CLAUDE.md?
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.
- 10d ago First seen · 48 lines · 25 tokens per session scan A b74e7f3c55ae
pr-review is a skill published in the GitHub repository mindroom-ai/mindroom (274 stars, last pushed today), licensed Apache-2.0. It adds 25 tokens to every session and 824 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.
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