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Agent Skill · 研究检索

systematic-testing(系统测试)

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。

systematic-testing 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证为 MIT,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 58,786。

总安装 404周安装 17GitHub Stars 2下载 141核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
MIT

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:systematic-testing(系统测试)
来源仓库:https://github.com/xbklairith/kisune
仓库路径:skills/systematic-testing
安装命令:
npx skills add https://github.com/xbklairith/kisune --skill systematic-testing
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。不同来源提供的安装方式可能略有差异;本站展示可直接复制的安装命令,安装前请核对来源页面。

skills.shnpx skills
npx skills add https://github.com/xbklairith/kisune --skill systematic-testing

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助测试设计、用例编写和回归验证工作。systematic-testing 属于研究检索类 Skill,可作为该场景下的辅助能力补充。适合让 Agent 生成单元测试、端到端测试脚本或测试计划。可帮助根据失败日志定位问题、优化测试覆盖率或设计夹具数据。使用时应确认项目测试框架、运行命令和环境隔离策略。

涉及浏览器或外部服务时需区分模拟环境与生产环境差异。

来源仓库内路径:skills/systematic-testing

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/xbklairith/kisune --skill systematic-testing;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要需要联网,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

systematic-testing 怎么安装?

在终端执行 npx skills add https://github.com/xbklairith/kisune --skill systematic-testing。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

systematic-testing 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

systematic-testing 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

systematic-testing 是免费的吗?

来源标注的许可证是 MIT。本站不代收任何费用,也不托管安装包;能否商用、要不要署名,以许可证原文为准。

systematic-testing 用的人多吗?

公开数据是累计安装 404 次,近一周安装 17 次,下载 141 次,GitHub 2 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

systematic-testing 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 3 个目录同时收录,说明这个 Skill 流传比较广。
  • 许可证明确为 MIT,商用和分发边界好判断。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。
  • 需要许可证清楚、并且有第三方扫描结果的团队项目。

不太适合

  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
systematic-testing

系统测试 · 本页

4042需要联网MIT通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Systematic Testing Skill

Purpose

Guide test-driven development (TDD), generate comprehensive test suites, and provide systematic debugging frameworks. Ensures code is well-tested and bugs are resolved methodically rather than through trial-and-error.

Activation Triggers

Activate this skill when:

  • User implements new functionality (auto-suggest tests)
  • Tests fail (activate debugging framework)
  • User says "write tests for this"
  • User mentions "TDD" or "test-driven"
  • User asks about debugging or troubleshooting
  • User says "this bug..." or "error..."
  • Before marking feature complete (verify test coverage)

Core Capabilities

1. Test-Driven Development (TDD)

For complete TDD workflow, use Skill tool to invoke: dev-workflow:test-driven-development

Use Skill tool: Skill(skill: "dev-workflow:test-driven-development")

The test-driven-development skill provides full RED-GREEN-REFACTOR cycle, strict enforcement, anti-patterns, and verification checklists.

Quick TDD Summary:

  1. RED: Write failing test first
  2. GREEN: Write minimal code to pass
  3. REFACTOR: Clean up while tests stay green

This skill focuses on test generation strategies and systematic debugging. For TDD methodology details, use the dedicated skill.


2. Test Generation

Goal: Generate comprehensive test suites covering all scenarios

Test Categories

Normal Cases (Happy Path)

Test expected, typical usage with valid inputs and standard flows.

Edge Cases (Boundary Conditions)

Test limits and boundaries:

  • Very small/large values
  • Equal values where difference is expected
  • Fractional results requiring rounding
  • Empty collections, zero-length strings
Error Cases (Invalid Inputs)

Test error handling:

  • Negative values, zero values
  • Out-of-range parameters
  • Null/nil/None inputs
  • Invalid types
Integration Cases

Test component interactions: full request-response flows, token validation chains, cross-component data passing.

Test Generation Template

suite "[Component/Function Name]":

    setup:    # Reset state, create test data
    teardown: # Clean up, reset mocks

    group "normal operation":
        test "should [expected behavior for typical input]"

    group "edge cases":
        test "should handle [boundary condition]"

    group "error handling":
        test "should reject [invalid input]":
            assert_raises(ExpectedError, invalid_call())

    group "integration":
        test "should work with [other component]"

3. Systematic Debugging Framework

Goal: Resolve bugs methodically, not through random trial-and-error

Phase 1: Root Cause Investigation

  1. Reproduce Bug Consistently - Document exact steps and reproducibility rate
  2. Identify Symptoms - Visible errors, expected vs actual behavior
  3. Gather Evidence - Error messages, stack traces, log entries, network requests, triggering inputs
  4. Form Initial Hypothesis - State hypothesis, supporting evidence, and next step

Phase 2: Pattern Analysis

Answer these questions:

  1. When does it fail? - Specific inputs, users, timing, action sequences?
  2. When does it work? - Any succeeding inputs, unaffected users, regression timing?
  3. What changed recently? git log --since="2 days ago" --oneline git log -p path/to/file git bisect # Find exact commit that introduced bug
  4. Environmental factors? - Local vs production, platform-specific, load-related?

Document the pattern: list conditions under FAILS and WORKS to identify the discriminator.

Phase 3: Hypothesis Testing

  1. Create minimal test case isolating the bug
  2. Add instrumentation (logging) to trace execution
  3. Test hypothesis - Confirm or reject with evidence
  4. Iterate until root cause is found

Phase 4: Fix and Protect

  1. Write test reproducing the bug - Verify it fails before fix
  2. Fix the root cause - Not just symptoms
  3. Verify test passes after fix
  4. Add regression tests for similar edge cases
  5. Document root cause - What, why, and how it was fixed
  6. Commit with context - Reference issue numbers, explain the why

Test Coverage Analysis

Check Coverage: Run your project's test coverage command (e.g., --coverage flag, coverage plugin, or dedicated tool).

Prioritize coverage gaps by:

  1. Critical business logic (highest priority)
  2. Security-sensitive code
  3. Complex algorithms
  4. Error handling paths
  5. Edge cases

Best Practices

TDD

  1. Always write test first - no exceptions
  2. One test at a time - don't batch before implementing
  3. Smallest possible step - each cycle should be 5-10 minutes
  4. Test behavior, not implementation - don't test private methods
  5. Keep tests simple - tests should be easier to understand than code

Test Quality

  1. Clear test names that read like documentation
  2. Arrange-Act-Assert structure consistently
  3. One assertion per test for clear failures
  4. No logic in tests - simple data only
  5. Independent tests - no test depends on another

Debugging

  1. Reproduce first - can't fix what you can't reproduce
  2. Understand before fixing - don't guess and check
  3. Fix root cause - don't just treat symptoms
  4. Add regression test - prevent bug from returning
  5. Document why - help future debuggers

Integration with Dev-Workflow

  • dev-workflow:test-driven-development - Guided TDD workflow, enhanced RED-GREEN-REFACTOR
  • dev-workflow:systematic-testing - Complex debugging, root cause tracing, advanced instrumentation

Common Anti-Patterns to Avoid

  • Writing tests after implementation
  • Changing tests to match implementation
  • Testing implementation details instead of behavior
  • Skipping refactor phase
  • Making multiple changes before testing
  • Debugging by randomly changing code
  • Committing debug logging code

Notes

  • TDD is slower initially but faster overall (fewer bugs, less debugging)
  • Good tests are documentation that never gets outdated
  • Debugging is detective work, not guessing
  • Always add regression tests after fixing bugs
  • Test coverage is a minimum bar, not a goal

平台分布

Claude Code

26.84%
按下载量换算38

windsurf

24.01%
按下载量换算34

trae

19.09%
按下载量换算27

OpenCode

11.62%
按下载量换算16

Codex

8.43%
按下载量换算12

Antigravity

3.27%
按下载量换算5

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。

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