review

review is a skill for Claude Code from quay/ai-helpers. It costs 30 tokens per session (982 once invoked), scanned A, original, MIT.

A critical review process for judging whether a bug fix and its tests address the real problem.

In plain words
What is it for?
Use it to inspect reproduction and analysis records, implementation notes, test results, code changes, and test code, then issue a verdict and next steps.
Why use it?
It looks for missing coverage, hidden failure paths, and fixes that only hide symptoms before the change reaches production.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool; mentions AGENTS.md.

Good fit Use it to inspect reproduction and analysis records, implementation notes, test results, code changes, and test code, then issue a verdict and next steps.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/quay/ai-helpers/review
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.

Any agent
npx skills add quay/ai-helpers --skill review
Clone the repo
git clone --depth 1 https://github.com/quay/ai-helpers

Made for: Claude Code.

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 review

README.md
[![agentmods](https://agentmods.dev/badge/skills/quay/ai-helpers/review.svg)](https://agentmods.dev/skills/quay/ai-helpers/review)
Your own site
<a href="https://agentmods.dev/skills/quay/ai-helpers/review"><img src="https://agentmods.dev/badge/skills/quay/ai-helpers/review.svg" alt="Measured on agentmods" height="20"></a>
Per session 30 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 982 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found 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 5.1 $0.00030 $0.00982
Opus 5 $0.00015 $0.00491
Sonnet 5 $0.00006 $0.00196
Haiku 4.5 $0.00003 $0.00098

Measured 3d ago against content hash 8cb4368d6902, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

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 3d 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.

workflows/quay-bugfix/.claude/skills/review/SKILL.md · 157 lines

How it starts

The opening of the file, as written. The whole thing — 157 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Review Fix & Tests

You are a skeptical reviewer whose job is to poke holes in the fix and its tests. Your goal is not to validate — it's to find what's wrong, missing, and what could fail in production.

Your Role

Independently re-evaluate the bug fix and test coverage. Challenge assumptions, look for gaps, and give the user a clear recommendation.

You are NOT the person who wrote the fix. You are a fresh set of eyes.

Process

Step 1: Re-read the Evidence

Gather all available context:

  • Reproduction report (artifacts/quay-bugfix/reports/reproduction.md)
  • Root cause analysis (artifacts/quay-bugfix/analysis/root-cause.md)
  • Implementation notes (artifacts/quay-bugfix/fixes/implementation-notes.md)
  • Test verification (artifacts/quay-bugfix/tests/verification.md)
  • The actual code changes (git diff)
  • The actual test code

If any are missing, note it — gaps in the record are themselves a concern.

Step 2: Critique the Fix

Does the fix address the root cause?

  • Or does it just suppress the symptom?
  • Could the bug recur under slightly different conditions?
  • Are there other code paths with the same underlying problem?

Is the fix minimal and correct?

  • Does it change only what's necessary?
  • Could it introduce new bugs?
  • Does it handle errors properly?

Does the fix follow Quay conventions?

  • Commit format: <subsystem>: <desc> (<TICKET>)?
  • Passed format-and-lint.sh?
  • Follows AGENTS.md patterns?

Step 3: Critique the Tests

Do the tests actually prove the bug is fixed?

  • Does the regression test fail without the fix and pass with it?
  • Or does it pass either way?

Are mocks hiding real problems?

  • Do mocks accurately reflect real Quay data layer behavior (data/model/)?
  • Are there integration tests, or only unit tests with mocks?

Is the coverage sufficient?

  • Are all states/conditions tested (not just the common ones)?
  • Are error paths tested?
  • Could someone break this fix without a test failing?

Read the full file on GitHub · 157 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. 3d ago First seen · 157 lines · 30 tokens per session scan A 8cb4368d6902

Subscribe to this mod's changes

review is a skill published in the GitHub repository quay/ai-helpers (3 stars, last pushed 20d ago), licensed MIT. It adds 30 tokens to every session and 982 once invoked, about $0.0002 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 2026-09-04.

Related

Other skills, from other repositories