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Agent Skill · 开发

writing-quality-tests(编写质量测试)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

writing-quality-tests 是开发类 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;许可证信息还不明确,第三方扫描已通过,按安装量在开发类的 21,746 个 Skill 里排第 17,948。

总安装 371周安装 15GitHub Stars 公开资料未说明下载 116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:writing-quality-tests(编写质量测试)
来源仓库:https://github.com/ederheisler/agent-skills
仓库路径:skills/writing-quality-tests
安装命令:
npx skills add https://github.com/ederheisler/agent-skills --skill writing-quality-tests
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/ederheisler/agent-skills --skill writing-quality-tests

这个 Skill 是做什么的

开发类 Skill 面向写代码、改代码和排查问题,一般会读写仓库文件,部分还会执行构建或测试命令。

用于编写质量测试用例和评估标准。writing-quality-tests 属于开发类 Skill,可作为该场景下的辅助能力补充。适合提升软件或内容的可靠性和稳定性。使用时需结合具体业务逻辑设计测试场景。建议人工复核测试覆盖率和边界条件。安装方式:通过 npx 从 GitHub 仓库添加技能。

来源仓库内路径:skills/writing-quality-tests

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/ederheisler/agent-skills --skill writing-quali…;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

writing-quality-tests 怎么安装?

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

writing-quality-tests 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。

writing-quality-tests 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。

writing-quality-tests 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。

writing-quality-tests 用的人多吗?

公开数据是累计安装 371 次,近一周安装 15 次,下载 116 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。

writing-quality-tests 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。
  • 需要处理开发类任务、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。

开发类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
skill-vetter

技能审查员 · OpenClaw

8,779,018986操作浏览器MIT-0通过
ontology

本体论 · OpenClaw

6,636,960576只读MIT-0通过
entra-app-registration

内部应用程序注册 · Codex、Claude

6,631,872764接触敏感数据未明确通过
entra-app-registration

内部应用程序注册 · Codex、Claude

3,757,680201接触敏感数据未明确通过
nano-banana-pro

纳米香蕉专业版 · OpenClaw

3,526,898364接触敏感数据MIT-0有提醒
writing-quality-tests

编写质量测试 · 本页

371—需要联网未明确通过

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

Writing Quality Tests

Overview

High-signal tests prove behavior, not implementation. While TDD focuses on the *process* of writing tests first, this skill focuses on the *artifact*—making tests stable, explicit, and valuable long-term.

Core rule: If a test is nondeterministic or tied to internals, it is debt. Fix it.

When to Use

  • New features: "I need to add tests for this new API endpoint/component."
  • Bug fixes: "Help me write a regression test for this bug before fixing it."
  • Flaky tests: "This test fails randomly on CI. How do I make it deterministic?"
  • Refactoring: "I want to refactor this legacy code but the tests are brittle. How do I improve them first?"
  • Slow tests: "The test suite takes too long. How can I speed it up or mock dependencies effectively?"
  • Test Design: "Should I use a unit test or integration test for this logic?"
  • Review: "Check these tests for maintainability, coverage, and clarity."
  • Not for manual exploratory testing or load/perf-only work.

Non-Negotiables

  • Deterministic: same input -> same result; no hidden time/network randomness
  • Behavioral oracles: assertions map to business behavior or contracts, never incidental internals
  • Minimal coupling: tests fail for product changes, not helper refactors
  • Focused scope: one behavior per test; isolated fixtures; clear names
  • Fast feedback: prefer fast layers; cache expensive setup; parallelize safely

Workflow

  1. Prove it fails: capture the regression input or wished-for case and watch the test fail first (or reproduce the bug) before code changes.
  2. Clarify behavior: preconditions, action, postconditions, invariants. Capture regression input if fixing a bug.
  3. Pick level: unit for pure logic; contract for external calls; integration for seams; E2E only to prove flows or contracts end-to-end.
  4. Design oracle: assert outputs, state, events, and invariants; avoid implementation details or transient UI.
  5. Shape fixtures: use builders/factories; avoid globals; randomize with seeds only when helpful and log the seed.
  6. Write the test: AAA (arrange-act-assert) or GWT; table-driven for variants; property-based for algebraic invariants.
  7. Validate: run focused test first, then suite. If flaky, hunt nondeterminism (time, randomness, order, network) and remove it.
  8. Document intent: name states behavior; failure message points to the expected contract.

Patterns to Prefer

  • Boundary and mutation pairs: min/max/empty/null plus one mutated variation to prove invariants.
  • Table-driven cases: enumerate input/output pairs to avoid duplicate tests and improve diffability.
  • Property-based checks: algebraic properties (idempotence, reversibility, ordering), round-trips, monotonic counters.
  • Contracts at seams: mock at boundaries you own; for third-party calls, pin to contract tests or recorded fixtures.
  • Guarded goldens: only for complex structured output; require explicit review of golden updates.

Coverage Strategy

  • Coverage is opt-in: never run coverage unless explicitly requested by the user in the current session (e.g., "improve coverage on file X to Y%"). PM/teammate/CI pressure does not override this rule.
  • Pyramid discipline: many unit tests, fewer integration, very few E2E. Use E2E to prove cross-service flow or UI contract.
  • Change-based coverage: every test should fail without the code change and pass with it; capture the regression input/output.
  • Critical paths first: auth, billing, migrations, data loss, irreversible actions. Add invariants that must never be violated.
  • Data and time: cover time zones, DST, leap years, ordering, pagination, idempotency, and retry semantics.
  • Observability: log seeds for randomized tests; emit diagnostics on failure (inputs, seed, environment versions).

Example (explicit coverage request): User: "improve coverage on file X to 80%". Run targeted coverage for that file only, add behavior-driven tests to hit missing branches, and avoid coverage runs outside that request.

pytest --cov=path/to/file.py --cov-report=term-missing

Flake Prevention

  • Remove time races: replace sleeps with waits on explicit conditions; freeze or inject clocks.
  • Isolate state: fresh fixtures per test; unique temp dirs/ports; clean databases; no shared singletons.
  • Control randomness: seed RNG, capture seed in failure output, prefer deterministic builders.
  • Network and IO: stub external calls; if unavoidable, record/replay; set tight timeouts and retries with jitter disabled in tests.
  • Parallel safety: ensure fixtures are parallel-safe or mark tests serial; avoid global mutable state.

Review Checklist

  • Name states behavior and level (e.g., "adds item to cart (integration)").
  • Single reason to fail; assertions map to user-visible behavior or contract.
  • Fixtures minimal and local; builders hide irrelevant details; no shared hidden state.
  • Negative and edge cases present; regression case for the original bug captured.
  • Tests run quickly; slow/expensive flows justified and focused.

Hygiene (adaptable patterns)

  • Structure: Given–When–Then or AAA so intent is obvious.
  • Hypothesis: fix generators or code instead of suppressing health checks; log seeds for repro.
  • Async correctness: use real async paths/fakes; don’t hide missing awaits with sync doubles.
  • Assertion scope: assert behavior/contract fields; avoid brittle full-payload snapshots unless testing a contract.
  • Coverage as health, not blocker: focus on low-coverage behavior-heavy files; be pragmatic with legacy or infra-heavy areas.

Marks (for selective runs)

  • unit: isolated logic with external deps mocked
  • contract/integration: cross-component seams with real wiring or adapters
  • async: true async paths; avoid sync fakes masking awaits
  • property: Hypothesis-based invariants in dedicated property files
  • slow: >1s or real infra; justify and keep focused

Common Anti-Patterns

  • Brittle UI or text snapshots without intent; prefer semantic assertions or scoped snapshots.
  • Over-mocking internals; mocking within the module under test; asserting call order that is not part of the contract.
  • Sleep-based waits; reliance on wall-clock time; unseeded randomness.
  • Combined scenarios covering multiple behaviors in one test; global fixtures that hide setup.
  • Golden files updated blindly; tests that assert logging implementation rather than outcomes.
  • Running coverage by default instead of waiting for explicit coverage requests.

Red Flags - Stop and Fix

  • Tests pass or fail intermittently
  • Assertions tied to private methods or call order instead of observable behavior
  • Unseeded randomness, sleeps instead of explicit waits, or shared mutable fixtures
  • Golden updates accepted without review of intent
  • A test never failed before the code change
  • Running coverage without the user explicitly asking
  • Running coverage due to PM/teammate/CI pressure

平台分布

Codex

39.53%
按下载量换算46

Claude

29.48%
按下载量换算34

Cursor

18.03%
按下载量换算21

Gemini CLI

9.9%
按下载量换算11

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。目前只有一个公开来源,建议同时核对源仓库。

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