ai-qa-review

ai-qa-review is a skill for Claude Code, Codex from petrkindlmann/qa-skills. It costs 133 tokens per session (4,843 once invoked), scanned A, original, MIT.

A review process for existing tests and application code. It looks for common test problems, checks how easy the application is to test, and uses mutation testing to support its findings.

In plain words
What is it for?
Reviewing changed test files, auditing a whole test suite, finding testability problems, identifying test smells, and suggesting quality or mutation-testing checks.
Why use it?
Tests may pass while being unclear, unreliable, hard to diagnose, or unable to detect real code changes. The review identifies these weaknesses and the design choices that cause them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one. Also seen: mentions Claude Code; mentions Codex.

Good fit Reviewing changed test files, auditing a whole test suite, finding testability problems, identifying test smells, and suggesting quality or mutation-testing checks.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/petrkindlmann/qa-skills/ai-qa-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 petrkindlmann/qa-skills --skill ai-qa-review
Clone the repo
git clone --depth 1 https://github.com/petrkindlmann/qa-skills

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 ai-qa-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/ai-qa-review/github.svg)](https://agentmods.dev/skills/petrkindlmann/qa-skills/ai-qa-review)
Your own site
<a href="https://agentmods.dev/skills/petrkindlmann/qa-skills/ai-qa-review"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/ai-qa-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.

agentmods 80×15 button for ai-qa-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/petrkindlmann/qa-skills/ai-qa-review"><img src="https://agentmods.dev/badge/skills/petrkindlmann/qa-skills/ai-qa-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 133 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,843 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. Third-party audits
  • Socket pass 23 May 2026
  • Snyk pass 23 May 2026
  • NVIDIA SkillSpector warn 7 Sept 2026
SkillSpector: 7 findings, up to medium

These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →

  • medium MCP Rug Pull · line 318
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 321
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 327
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 318
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 322
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 318
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
  • medium MCP Rug Pull · line 320
    npx commands without a version suffix (e.g. @1.0.0) create a rug-pull risk if the upstream server is compromised and publishes a malicious update.
    Fix: Pin the version: npx @scope/[email protected]
How audits are shown
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 $0.00133 $0.04843
Opus 5 $0.00067 $0.02422
Sonnet 5 $0.00027 $0.00969
Haiku 4.5 $0.00013 $0.00484

Measured 12d ago against content hash 07a40a415272, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

ai-qa-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 12d 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.

skills/ai-qa-review/SKILL.md · 358 lines

How it starts

The opening of the file, as written. The whole thing — 358 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Before starting: Check for .agents/qa-project-context.md in the project root. It contains test framework conventions, naming patterns, and project-specific quality standards that calibrate review feedback.


Quick Route

Three distinct entry paths. Pick the row, then jump to the named section.

Situation Path Jump to
PR with changed test files Run the changed files, score them, check the diff against the PR checklist VerificationPR Review Checklist
Whole suite needs a health pass Quantify, sample, find the 3-5 systemic smells, propose lint/mutation gates Batch Audit Process
Application code, "why is this hard to test?" Flag DI / side-effect / pure-function / interface problems with before/after Testability Analysis

All three share the same smell vocabulary (the six buckets below) and the same Verification commands.


Discovery Questions

First, read .agents/qa-project-context.md if present and skip any question it already answers.

  1. Review scope: Reviewing test code for quality, application code for testability, or both? Each triggers a different Quick Route path.
  2. Framework conventions: What test framework (Jest, Vitest, Playwright, pytest)? Conventions differ — describe/it nesting, fixture usage, assertion style — and the Verification commands are per-framework.
  3. PR review or batch audit? A PR review runs and scores only the changed files. A batch audit scans the entire suite for systemic patterns.
  4. Existing quality standards: Does the team have documented test conventions? Check for .eslintrc test rules, CONTRIBUTING.md test guidelines, or a test style guide.
  5. Known pain points: Recurring flaky tests, slow suites, unclear failures? These prioritize which smells to focus on first.

Read the full file on GitHub · 358 lines

Files

What ships with it

3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

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. 12d ago First seen · 358 lines · 133 tokens per session scan A 07a40a415272

Subscribe to this mod's changes

ai-qa-review is a skill published in the GitHub repository petrkindlmann/qa-skills (118 stars, last pushed 3mo ago), licensed MIT. It adds 133 tokens to every session and 4,843 once invoked, about $0.0007 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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