test-review

test-review is a skill for Claude Code, Codex from nntan90/qa-skill-suite. It costs 173 tokens per session (4,652 once invoked), scanned A, original, MIT.

A test-suite reviewer that checks whether tests really protect the code. It looks for weak tests, anti-patterns, missing cases, flaky behavior, and misleading coverage numbers.

In plain words
What is it for?
Use it to assess test quality, inspect error and failure cases, find brittle or fake tests, and decide whether a test suite is ready to support a completed change.
Why use it?
A high coverage percentage does not prove that important failures are tested. This review points out gaps and explains the risks behind them.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is jest.mock('../emailService', () => ({ send: mockSend }));.

Good fit Use it to assess test quality, inspect error and failure cases, find brittle or fake tests, and decide whether a test suite is ready to support a completed change.

Compare 6 skills from other repositories ↓
Install

Getting it into your agent

It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.

Clone the repo
git clone --depth 1 https://github.com/nntan90/qa-skill-suite
agentmods
npx agentmods add skills/nntan90/qa-skill-suite/test-review

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 test-review

README.md
[![agentmods](https://agentmods.dev/badge/skills/nntan90/qa-skill-suite/test-review/github.svg)](https://agentmods.dev/skills/nntan90/qa-skill-suite/test-review)
Your own site
<a href="https://agentmods.dev/skills/nntan90/qa-skill-suite/test-review"><img src="https://agentmods.dev/badge/skills/nntan90/qa-skill-suite/test-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 test-review

Your own site · 80×15
<a href="https://agentmods.dev/skills/nntan90/qa-skill-suite/test-review"><img src="https://agentmods.dev/badge/skills/nntan90/qa-skill-suite/test-review.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 173 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,652 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 $0.00173 $0.04652
Opus 5 $0.00086 $0.02326
Sonnet 5 $0.00035 $0.00930
Haiku 4.5 $0.00017 $0.00465

Measured 10d ago against content hash 09df5ce8d27e, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-10, from the pricing page.

Security

Grade A, and why

test-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.

test-review/SKILL.md · 566 lines

How it starts

The opening of the file, as written. The whole thing — 566 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Test Review Skill

Anti-Pattern Detection · Coverage Audit · ISTQB Advanced

When to Use This Skill

  • User asks "are my tests good?" or "review my test suite"
  • User's tests pass but production has bugs — something is wrong
  • User wants a quality gate before marking a story "done"
  • User wants to identify flaky or brittle tests
  • User wants to audit test coverage for real quality (not just % numbers)

Agent Persona

Act like a senior QA engineer with 20 years of experience.

  • Use plain, clear English. Short sentences. No robot language.
  • Be direct. If something is wrong or missing, say it straight.
  • Share real experience. Say things like: "I've seen this miss bugs in production before" or "Most teams skip this, but it matters."
  • Always explain WHY a test matters, not just what to do.
  • Point out risks even when the user didn't ask.

Language standard: Write all output in B1-level English. Simple words. Active voice. One idea per sentence.


Output Review Loop

After producing any output, the agent MUST run this self-check and include the result at the bottom.

My Self-Check:
  [ ] Happy path — covered
  [ ] Error / failure cases — at least 2 covered
  [ ] Boundary values — covered (if numbers or ranges exist)
  [ ] Empty / null / zero inputs — covered
  [ ] Auth / permission — covered (if feature has login)
  [ ] Nothing obvious missing that a real user would try
  [ ] Output is complete — no "TODO" or "add more" placeholders

Verdict: COMPLETE / INCOMPLETE
If INCOMPLETE — what I still need to add: [list]

Input Schema

Trước khi review, agent PHẢI thu thập đủ thông tin sau. Nếu user paste code trực tiếp, hãy tự phân tích language/framework từ code và bắt đầu review ngay.

INPUT REQUIRED:
  # --- Mandatory ---
  test_code:
    description: "Test code cần review"
    format: "Paste toàn bộ test file(s), hoặc GitHub URL của file"
    note: "Có thể paste nhiều files — review tổng thể suite"

  language:
    description: "Ngôn ngữ lập trình"
    options: ["python", "javascript", "typescript", "java", "go", "ruby", "csharp"]
    note: "Tự phân tích từ code nếu không được cung cấp"

  framework:
    description: "Testing framework sử dụng"
    options: ["pytest", "jest", "vitest", "mocha", "playwright", "cypress", "junit", "rspec"]
    note: "Tự phân tích từ imports nếu không được cung cấp"

  # --- Strongly Recommended ---
  codebase_context:
    description: "Mô tả ngắn về feature/module đang được test"
    example: "Module xác thực user, bao gồm login, register, password reset. Dùng JWT."
    note: "Giúp phát hiện missing test cases phù hợp với context"

  # --- Optional ---
  review_focus:
    description: "Những gì cần ưu tiên review"
    options:
      - "anti-patterns only"
      - "missing test cases only"
      - "coverage quality"
      - "flakiness / stability"
      - "full review (default)"
    default: "full review"

  coverage_report:
    description: "Kết quả coverage từ tool (nếu có)"
    example: "Paste output của pytest-cov hoặc jest --coverage"
    note: "Giúp phân biệt coverage thực vs coverage gaming"

  pr_context:
    description: "Link PR hoặc user story đang được implement"
    note: "Dùng để kiểm tra acceptance criteria có được cover không"

Read the full file on GitHub · 566 lines

Files

What ships with it

1 file 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. 10d ago First seen · 566 lines · 173 tokens per session scan A 09df5ce8d27e

Subscribe to this mod's changes

test-review is a skill published in the GitHub repository nntan90/qa-skill-suite (5 stars, last pushed 5mo ago), licensed MIT. It adds 173 tokens to every session and 4,652 once invoked, about $0.0009 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 2026-08-31.

Related

Other skills, from other repositories

research-engineer

An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.

davila7/claude-code-templates · 43 tokens

tika-eval-compare

Compare extracts from two Tika builds over a corpus to detect regressions in content, encoding, exceptions, and embedded-document handling. Use for "compare before/after extracts", "eval this change against the corpus".

apache/tika · 50 tokens

neuron-evaluation-engineer

Create and run AI evaluations with datasets, assertions, and output drivers in Neuron AI. Use this skill whenever the user mentions evaluation, testing AI systems, creating evaluators, dataset-driven testing, assertion-based validation, or wants to measure AI system performance. Also trigger for tasks involving…

neuron-core/neuron-ai · 77 tokens

jetson-validate-image

Use after jetson-flash-image to run static BSP checks, on-target smoke/regression tests on a flashed DUT, or both. Not for build or flash steps. Triggers: validate bsp, on-target validation.

NVIDIA/skills · 50 tokens

atmos-validation

Validate Atmos projects, components, arbitrary JSON Schema inputs, EditorConfig, and GitHub Actions; use affected-file selection and native CI annotations.

cloudposse/atmos · 31 tokens

skill-benchmark

Benchmark AI skill effectiveness by measuring implementation quality against legacy constraints.

HoangNguyen0403/agent-skills-standard · 16 tokens