Token导航 LogoToken导航TokenDH.com
研究检索只读github未标认证来源可访问许可证需确认审计通过

test-review测试回顾

Agent Skill

用于辅助测试设计、自动化测试、用例整理和回归验证。它适合让 Agent 编写单元测试、端到端测试、测试计划或根据失败日志定位问题。使用时需要确认项目测试框架、运行命令和夹具数据,避免为了通过测试而改坏真实逻辑;涉及浏览器或外部服务时,应区分本地模拟、测试环境和生产环境。

总安装

588

周安装

24

GitHub Stars

264

下载量

190
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:test-review(测试回顾)
来源仓库:https://github.com/athola/claude-night-market
仓库路径:skills/test-review
安装命令:
npx skills add https://github.com/athola/claude-night-market --skill test-review
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/athola/claude-night-market --skill test-review

简介

按照 TDD/BDD 标准评估和改进测试套件的审核工具。

  • 适用于 Codex、Claude、Cursor、Gemini CLI 中的质量保证场景。
  • 提供覆盖率分析与场景质量评估功能。
  • 安装前需确认权限范围、维护状态及是否运行测试命令。
  • test-review 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Table of Contents

Test Review Workflow

Evaluate and improve test suites with TDD/BDD rigor.

Quick Start

/test-review

Verification: Run pytest -v to verify tests pass.

When To Use

  • Reviewing test suite quality
  • Analyzing coverage gaps
  • Before major releases
  • After test failures
  • Planning test improvements

When NOT To Use

  • Writing new tests - use parseltongue:python-testing
  • Updating existing tests - use sanctum:test-updates

Required TodoWrite Items

  1. test-review:languages-detected
  2. test-review:coverage-inventoried
  3. test-review:scenario-quality
  4. test-review:gap-remediation
  5. test-review:evidence-logged

Progressive Loading

Load modules as needed based on review depth:

  • Basic review: Core workflow (this file)
  • Framework detection: Load modules/framework-detection.md
  • Coverage analysis: Load modules/coverage-analysis.md
  • Quality assessment: Load modules/scenario-quality.md
  • Remediation planning: Load modules/remediation-planning.md

Workflow

Step 1: Detect Languages (test-review:languages-detected)

Identify testing frameworks and version constraints. → See: modules/framework-detection.md

Quick check:

find . -maxdepth 2 -name "Cargo.toml" -o -name "pyproject.toml" -o -name "package.json" -o -name "go.mod"

Verification: Run the command with --help flag to verify availability.

Step 2: Inventory Coverage (test-review:coverage-inventoried)

Run coverage tools and identify gaps. → See: modules/coverage-analysis.md

Quick check:

git diff --name-only | rg 'tests|spec|feature'

Verification: Run pytest -v to verify tests pass.

Step 3: Assess Scenario Quality (test-review:scenario-quality)

Evaluate test quality using BDD patterns and assertion checks. → See: modules/scenario-quality.md

Focus on:

  • Given/When/Then clarity
  • Assertion specificity
  • Anti-patterns (dead waits, mocking internals, repeated boilerplate)

Step 4: Plan Remediation (test-review:gap-remediation)

Create concrete improvement plan with owners and dates. → See: modules/remediation-planning.md

Step 5: Log Evidence (test-review:evidence-logged)

Record executed commands, outputs, and recommendations. → See: imbue:proof-of-work

Test Quality Checklist (Condensed)

  • Clear test structure (Arrange-Act-Assert)
  • Critical paths covered (auth, validation, errors)
  • Specific assertions with context
  • No flaky tests (dead waits, order dependencies)
  • Reusable fixtures/factories

Output Format

## Summary
[Brief assessment]

## Framework Detection
- Languages: [list] | Frameworks: [list] | Versions: [constraints]

## Coverage Analysis
- Overall: X% | Critical: X% | Gaps: [list]

## Quality Issues
[Q1] [Issue] - Location - Fix

## Remediation Plan
1. [Action] - Owner - Date

## Recommendation
Approve / Approve with actions / Block

Verification: Run the command with --help flag to verify availability.

Integration Notes

  • Use imbue:proof-of-work for reproducible evidence capture
  • Reference imbue:diff-analysis for risk assessment
  • Format output using imbue:structured-output patterns

Exit Criteria

  • Frameworks detected and documented
  • Coverage analyzed and gaps identified
  • Scenario quality assessed
  • Remediation plan created with owners and dates
  • Evidence logged with citations

Troubleshooting

Common Issues

Tests not discovered Ensure test files match pattern test_*.py or *_test.py. Run pytest --collect-only to verify.

Import errors Check that the module being tested is in PYTHONPATH or install with pip install -e.

Async tests failing Install pytest-asyncio and decorate test functions with @pytest.mark.asyncio

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

36.38%
按下载量换算69

Claude

28.74%
按下载量换算55

Cursor

18.57%
按下载量换算35

Gemini CLI

10.44%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

继续浏览同类 Skills