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Agent Skill · 研究检索

tdd(时差)

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。

tdd 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,权限为调用外部服务;许可证信息还不明确,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 44,817。

总安装 890周安装 36GitHub Stars 公开资料未说明下载 279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
unknown

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:tdd(时差)
来源仓库:https://github.com/help-me-test/skills
仓库路径:skills/tdd
安装命令:
npx skills add https://github.com/help-me-test/skills --skill tdd
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/help-me-test/skills --skill tdd

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。

tdd 用于辅助测试驱动开发流程,支持自动化测试用例整理和回归验证。适用于需要编写端到端测试或根据失败日志快速定位问题的开发工作。使用时需确认项目测试框架和运行命令,确保测试逻辑与真实业务一致。涉及外部服务时应区分本地模拟与生产环境,避免因环境差异导致误判。

tdd 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/tdd

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/help-me-test/skills --skill tdd;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

    它需要调用外部服务,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

tdd 怎么安装?

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

tdd 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。

tdd 需要什么权限?

权限级别是调用外部服务。该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

tdd 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

tdd 用的人多吗?

公开数据是累计安装 890 次,近一周安装 36 次,下载 279 次。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。

tdd 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。
  • 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

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 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。

不太适合

  • 需要明确授权才能用到公司项目里的场景。
  • 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
tdd

时差 · 本页

890—调用外部服务未明确通过

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

Who you are: If .helpmetest/SOUL.md exists, read it — it defines your character.
No MCP? Use helpmetest <command> instead of MCP tools.

### 🔴 YOU WRITE THE TEST FIRST. Changed code → run the tests. New feature → write the test before the code. The test is the spec. The test is done when it's green. No test = not done.

Narrate Your Actions

Never create a test, artifact, or run a test silently. Always tell the user:

  • Before: what you are about to do and why (what scenario it covers, what risk it guards against)
  • After: what happened — result, what the artifact contains, why a test failed
  • Next: what you will do next and what decision point is coming

Silence means the user has no idea what you did or why.

Tests — Write, Generate, Fix

Orient First (Always)

Before doing anything, check what already exists:

helpmetest_status()
helpmetest_search_artifacts({ query: "" })
helpmetest_search_artifacts({ type: "Tasks" })
  • Tests already failing? → that's the priority, not creating new ones
  • Tasks artifact in progress? → resume it, don't start over
  • Feature artifacts exist? → use them, don't re-discover

Use Cases

"I need to build something" (TDD)

New feature, bug fix, or refactor. Tests come first — they define what "done" means.

1. Create a Tasks artifact to track the work:

{
  "id": "tasks-[feature-name]",
  "type": "Tasks",
  "content": {
    "overview": "What this implements and why",
    "tasks": [
      { "id": "1.0", "title": "Write all tests first", "status": "pending", "priority": "critical" },
      { "id": "2.0", "title": "Implement to make tests pass", "status": "pending" },
      { "id": "3.0", "title": "All green — review for gaps", "status": "pending" }
    ]
  }
}

2. Create a Feature artifact with all scenarios before writing a single test:

{
  "id": "feature-[name]",
  "type": "Feature",
  "content": {
    "goal": "What this feature does",
    "functional": [
      { "name": "User can do X", "given": "...", "when": "...", "then": "...", "tags": ["priority:critical"], "test_ids": [] }
    ],
    "edge_cases": [],
    "bugs": []
  }
}

3. Plan coverage before writing a single test. For every feature, enumerate scenarios across four types:

TypeAlways?Question to ask
Critical path✅ alwaysWhat does a real user do when everything works?
Error paths✅ alwaysWhat are the 3 most likely ways this breaks in prod?
Boundary conditionsif data/logicWhere does behavior change based on a threshold?
Edge casesselectivelyWhat would a QA engineer test that a dev wouldn't?

Mark each scenario: write immediately (critical/high) / write before launch (medium) / skip (cosmetic, already covered, unreliable). Don't test everything — test what would hurt if it broke.

4. Write ALL tests — happy paths, edge cases, errors — before implementing anything. Failing tests are your spec.

5. Implement incrementally — pick the highest-priority failing test, make it pass, move to the next.

6. Done when all tests are green and you've reviewed for missing edge cases.


"Write tests for an existing feature"

Feature exists (or was just built by someone else). Your job is tests only.

1. Read the Feature artifact — helpmetest_get_artifact({id: "feature-X"}). If none exists, create one first based on what you know.

2. Explore interactively before writing — run the scenario step by step using helpmetest_run_interactive_command. A test written after seeing real behavior uses real selectors and reflects actual timing. A test written from a description is a guess.

As  <persona>
Go To  <url>
# Execute each Given/When/Then step, observe what actually happens

3. Before writing each test, answer this out loud:

"If this test passes but the feature is actually broken, what user complaint would we miss until a customer reports it?"

Write that answer as the PROTECTS: line in [Documentation]. This is the contract the test makes with the user — not optional boilerplate. If you can't answer it in one sentence, the scenario needs more thought, not a test.

4. Write tests for priority:critical scenarios first, then high, then medium. For each:

  • 5+ meaningful steps
  • Verify business outcomes (data saved, state changed) — not just that an element is visible
  • Use Create Fake Email for any registration/email fields — never hardcode
  • [Documentation] must start with PROTECTS: <what user complaint this catches>

5. Validate each test with fix-tests before linking it to the scenario. A test that passes when the feature is broken must be rewritten — it is not done until the validator says PASS.

6. Link tests back — add each test ID to scenario.test_ids in the Feature artifact only after it passes validation.

7. Run and fix — see "Fix broken tests" below if a newly-written test fails.


"Fix broken tests" / "Tests are failing"

First: understand the failure pattern

Check recent code changes:

git diff --stat HEAD
git log --oneline -5

Map changed files to likely causes:

  • components/, pages/ → selector changes
  • auth/, session/ → auth state issues
  • api/, routes/ → backend errors or changed response shapes

Then get test history: helpmetest_status({id: "test-id", testRunLimit: 10})

Classify:

  • Consistent failure after a code change → selector/behavior changed
  • Intermittent PASS/FAIL with changing errors → isolation issue (shared state, test order dependency)
  • Timeout / element not visible → timing issue
  • Auth/session error → state not restored correctly
  • Backend error in test output → real bug, not a test issue

Reproduce interactively — always do this before fixing

Run the failing steps one at a time:

As  <persona>
Go To  <url>
# Execute each step, observe what actually happens at the point of failure

For "element not found": list all elements of that type, try alternate selectors. For "wrong value": check what's actually displayed vs what the test expected. For timeouts: try longer waits, check whether the element ever appears.

Decide: test issue or app bug?

  • Test issue (selector changed, timing, wrong expectation) → fix the test, validate the fix interactively before saving
  • App bug (feature is actually broken) → document in feature.bugs[], update Feature.status to "broken" or "partial"

Many tests broke after a UI change?

Work through them systematically one by one. For each:

  1. Classify the failure (usually selector or timing)
  2. Reproduce interactively
  3. Fix
  4. Run to confirm

Don't shotgun-fix by guessing — one wrong fix creates two broken tests.

Tests are out of date after a refactor?

  1. Get test list: helpmetest_status()
  2. For each failing test, check whether the Feature artifact scenario still matches intended behavior
  3. If the code is the source of truth → update the test
  4. If the test was right and the refactor broke behavior → document the regression

Writing Tests

Structure

As  <persona>          # auth state — always first
Go To  <url>

# Given — establish precondition
<steps>

# When — perform the action
<steps>

# Then — verify the outcome
<assertions>

# Persistence check (if relevant)
Reload
<re-assert that state survived>

Documentation format

Every test must have [Documentation] with four explicit lines:

[Documentation]
...    Given: <precondition — what state the system is in before the action>
...    When: <action — what the user/system does>
...    Then: <outcome — what is asserted, specifically>
...    Risk: <what silent failure this catches — user complaint if this test were deleted>

Full example:

[Documentation]
...    Given: registered user with valid account
...    When: submits login form with wrong password
...    Then: sees "Invalid email or password" error, remains on login page, is NOT authenticated
...    Risk: silent login failure — attacker gets in, or user is confused with no feedback

Given/When/Then — what makes them good:

  • ✅ Given: registered user with valid account — specific precondition
  • ✅ When: submits login form with wrong password — exact action
  • ✅ Then: sees "Invalid email or password" error, remains on login page, is NOT authenticated — concrete, multiple assertions named
  • ❌ Given: user is logged in | When: they do something | Then: it works — vague, tells you nothing when the test fails

Language rules — the description must be readable by a product manager:

  • ✅ Write in terms of user actions and visible outcomes
  • ❌ NEVER put CSS selectors, XPath, or DOM class names (.keyword-line.current, #submit-btn, div[data-id])
  • ❌ NEVER put JavaScript internals, variable names, or debug APIs (replayDebug.currentKeyword, window.__state)
  • ❌ NEVER put Robot Framework syntax, keyword names, or technical implementation details
  • The test body is where selectors live. The description is where the product manager lives.

Wrong:

Given: replay loaded with .banner-keywords visible
When: user clicks .banner-next and replayDebug.currentKeyword changes
Then: .keyword-line.current text matches window.replayDebug.currentKeyword.split(/ {2,}/)[0]

Right:

Given: a test replay is open and paused
When: user steps forward then backward through keywords using the navigation buttons
Then: the highlighted keyword in the banner matches the current playback position after each navigation

Risk — good examples:

  • ✅ Risk: users completing checkout get charged without receiving an order confirmation
  • ✅ Risk: users typing wrong passwords are silently logged in or shown a blank screen
  • ✅ Risk: profile email changes silently fail — user sees stale email with no indication
  • ❌ Risk: the login form breaks — too vague, what breaks? who notices?
  • ❌ Risk: the form doesn't submit — that's what the test does, not what it protects against

Inline comments

Every non-obvious step must have a # comment above it written for a product manager, not an engineer.

Comments explain *why* a step exists, what the user is experiencing, or what the test is checking — not what the keyword does.

# User opens an existing test replay — this is the entry point for debugging failed tests
Go To  https://helpmetest.example.com/test/some-test

# The banner shows the current keyword being replayed — it must stay in sync with what's actually executing
Click  css=.banner-next

# After stepping forward, the highlighted keyword in the banner must change to match the new position
# If this fails, users see the wrong keyword highlighted while debugging — they investigate the wrong step
${label}=  Get Text  css=.keyword-line.current .keyword-text
Should Contain  ${label}  ${expected_keyword}

Comments are mandatory for:

  • Any Javascript call — explain what user-visible state it reads or changes
  • Any Hover or Sleep — explain why the UI requires this (hover to reveal hidden elements, sleep for animation)
  • Any multi-step assertion group — explain what the group collectively verifies
  • Any setup step that isn't obvious navigation

What makes a good test

✅ Verifies a business outcome — data saved, filter applied, order created ✅ Would FAIL if the feature is broken ✅ 5+ meaningful steps ✅ Checks state change, not just that a button exists

❌ Just navigates to a page and counts elements ❌ Clicks something without checking what happened ❌ Passes when the feature is broken

Test naming

Format: User can <action> or <Feature> <behavior>

  • ✅ User can update profile email
  • ✅ Cart total updates when quantity changes
  • ❌ MyApp Login Test
  • ❌ SiteName Checkout

Auth

Use Save As <StateName> once to capture auth state. Reuse with As <StateName> in every test — never re-authenticate inside tests.

Emails

Use Create Fake Email — never hardcode test@example.com. Hardcoded emails break on second run.

${email}=  Create Fake Email
Fill Text  input[name=email]  ${email}
${code}=   Get Email Verification Code  ${email}

Localhost

If testing a local server, set up the proxy first:

helpmetest_proxy({ action: "start", domain: "dev.local", sourcePort: 3000 })

Verify it works before writing any tests. See the proxy skill for details.


Tags

  • priority:critical|high|medium|low
  • feature:[feature-name]
  • type:e2e|smoke|regression

Done means

  • ✅ All tests passing
  • ✅ All priority:critical scenarios have test_ids
  • ✅ Every test has Given:, When:, Then:, Risk: lines in [Documentation]
  • ✅ Every test passed /fix-tests before being linked
  • ✅ Bugs documented in feature.bugs[]
  • ✅ Feature.status updated (working / broken / partial)
  • ✅ Tasks artifact all done

Final summary format

Never end with "N tests created, M passing." End with this:

## What you can now trust works
- <user-facing statement> (test: <id>)
- <user-facing statement> (test: <id>)

## What's still unprotected
- <what could silently break with no test catching it>

## Bugs found
- <bug description> — documented in feature.bugs[]

If you can't write the first section in user-facing language, your tests are not done.

平台分布

Codex

38.36%
按下载量换算107

Claude

27.91%
按下载量换算78

Cursor

20.41%
按下载量换算57

Gemini CLI

9.93%
按下载量换算28

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

调用外部服务

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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。目前只有一个公开来源,建议同时核对源仓库。

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