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test-designer测试设计师

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

374

周安装

15

GitHub Stars

公开资料未说明

下载量

121
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-designer(测试设计师)
来源仓库:https://github.com/ben2pc/g-claude-code-plugins
仓库路径:skills/test-designer
安装命令:
npx skills add https://github.com/ben2pc/g-claude-code-plugins --skill test-designer
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/ben2pc/g-claude-code-plugins --skill test-designer

简介

用于辅助测试设计、自动化测试、用例整理和回归验证。

  • 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。
  • 安装方式:github,需通过 npx skills add 命令从指定仓库添加。

SKILL.md

Test Designer

Independent test-design orchestrator. Encodes Independent Evaluation: the agent writing the tests must not be the agent implementing the feature, and must not inherit the implementation's assumptions.

When to Use

  • TDD red phase for a complex / non-trivial feature (multi-file, multi-branch logic, new subsystem)
  • Requirement is ambiguous enough that the implementer's tests would likely rationalize the implementation instead of catching bugs
  • User explicitly asks for "independent test design", "fresh-eyes tests", or runs /test-designer

Don't use for:

  • Trivial changes (one-line fix, rename) — just write the test inline
  • Bug reproduction tests — write directly from the bug report
  • Non-code changes (pure docs, pure config, pure prompt)

The Iron Law

The agent designing the tests must not carry the implementation's context. If you (the main Agent) are about to implement the feature, you are disqualified from designing its tests. Dispatch.

Violating this = tests that pass because they mirror the buggy implementation.

Steps

Step 1: Assemble the dispatch package

Collect only these inputs — nothing else:

  1. Requirement description — "what to do" and acceptance criteria (not "how to do")
  2. Relevant code file paths — read-only access to the code the feature will touch or integrate with
  3. Edge case prompts — categories the dispatched agent should enumerate:

- Boundary inputs (empty, max, min, off-by-one) - Concurrency / ordering (if applicable) - Resource lifecycle (cleanup on error, partial failure) - Invariants (data consistency, idempotency) - Adversarial inputs (malformed, oversized, mis-encoded)

Explicitly exclude:

  • The implementation plan or design you've been developing
  • Hints about which approach you've chosen
  • Code excerpts from a work-in-progress branch
  • Your own guesses about "the right way to test this"

Step 2: Choose the executor

Task shapeExecutorReason
Complex, architectural implicationsIndependent Agent (e.g., codex-agent or claude-code-agent with fresh session)True zero-context isolation; can use strongest model at highest effort
Medium complexity, current conversation cleanIn-conversation subagentCheaper; still acceptable if main Agent hasn't yet proposed an implementation
TrivialDon't dispatch — write tests inline

Default to Independent Agent when the main Agent has already discussed or sketched implementation. Subagent isolation within the same conversation doesn't undo prior context pollution.

Step 3: Dispatch with the strongest model and highest effort

Test design is a correctness-critical reasoning task, not a rote mechanical one. Use:

  • Model: strongest reasoning model the runtime offers — inherit if the main Agent is already on that tier; otherwise override. Don't hardcode a specific brand name
  • Effort: xhigh (the maximum level the runtime supports). Escalation ladder: lowmediumhighxhigh
  • Tools: Read / Grep / Glob on code paths; Write on test files only
  • Permission: read-only on non-test files; writable on test files

Example dispatch prompt skeleton:

You are designing failing tests for a feature. You will NOT see or write the
implementation. Your job is to produce executable tests that fail today and
pass only when the feature is correctly implemented.

Requirement:
<paste requirement description + acceptance criteria>

Code paths (read-only, for understanding context):
<list of file paths>

Existing test framework and conventions:
<infer from repo or specify>

Produce:
1. A test plan — enumerate the behaviors being tested (happy path + edge
   cases), grouped by category (boundary / concurrency / lifecycle /
   invariants / adversarial).
2. Executable test files that fail against the current code (or against
   an empty implementation).
3. For each test, one-line rationale explaining the bug it would catch.

Constraints:
- Do NOT propose an implementation.
- Do NOT edit files outside the test directory.
- Cover edge cases explicitly; don't only test the happy path.
- Use the project's existing test framework and style.

Step 4: Validate the returned tests

Before handing the tests to the implementation phase:

  1. Run the tests — they should FAIL (red), and fail for the reason the rationale predicts. A test that fails on ImportError, missing fixture, syntax error, or "module not found" is fake red — the test isn't actually exercising the behavior it claims to. Fix the test or drop it.
  2. Scan the rationale — does each test catch a distinct failure mode? Drop duplicates.
  3. Check coverage — are all edge case categories represented? Request additions if not.
  4. Confirm the test framework matches — ensure the dispatched agent used the right runner / assertion lib / fixtures.
  5. Check for shape-to-example tests — a test that asserts on specific happy-path values (e.g., "output equals exactly [1, 2, 3] for this fixture") is shaping the test to the example, not to the requirement. Such a test passes when the implementation matches the fixture and breaks for any valid variant input. Replace with property-style assertions ("output is sorted and contains all input elements") or add a second test with a different input that exercises the same property.

Step 5: Hand off to implementation

With the validated failing tests in place, implementation proceeds per test-driven-development skill: write minimal code to make them pass (green), then regression.

Output Format (from the dispatched agent)

Require the agent to return:

A test plan (bullet list, grouped by category) followed by the test files. Each test must include a one-line rationale comment. No implementation code. No commentary on how to implement. If assumptions about the code are needed, list them explicitly at the top of the test file.

Anti-patterns

  • ❌ Main Agent writes the tests after sketching the implementation — tests will mirror the implementation's assumptions
  • ❌ Dispatching with medium effort / weaker model to save cost — test design quality compounds across the whole feature's lifetime
  • ❌ Passing the work-in-progress branch contents to the dispatched agent — defeats Independent Evaluation
  • ❌ Accepting tests that pass against an empty implementation — those tests don't constrain anything
  • ❌ Skipping Step 4 validation — unvalidated tests get merged as fake green
  • ❌ Accepting "shape-to-example" tests — a test that asserts on specific happy-path values from the requirement's example data passes whenever input==fixture and breaks for any variant. Use property assertions (sorted, idempotent, contains-all-inputs) or pair the example test with a variant-input test that exercises the same invariant
  • ❌ Accepting fake red — a test that fails on ImportError, missing fixture, or "module not found" looks red but isn't testing anything. Step 4 must verify the test fails for the reason the rationale predicts

Relationship to other skills

  • brainstorming → clarifies the requirement (upstream of test-designer)
  • test-driven-development → governs the red-green-refactor loop (downstream; consumes the failing tests)
  • systematic-debugging → kicks in if tests unexpectedly fail after implementation (downstream)
  • verification-before-completion → runs the tests at the "done" gate (downstream)

Example invocation

User: Starting work on the new plugin dependency resolver. Design tests first.
Assistant:
  1. Requirement: "Resolver takes a plugin manifest and returns install order
     respecting deps and detecting cycles. Must handle: transitive deps,
     diamond deps, self-references, missing deps, cycles."
  2. Code paths: src/plugins.ts, .claude/plugins.json schema, tests/ dir
  3. Dispatch to an independent-agent skill (fresh session) at `xhigh` effort,
     read-only on src/, writable on tests/
  4. Agent returns: test plan (5 categories, 18 tests), tests/resolver.test.ts
     with failing assertions + per-test rationale comments
  5. Main Agent runs tests → all red → validates rationale → hands off

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

34.66%
按下载量换算42

Claude

32.87%
按下载量换算40

Cursor

17.12%
按下载量换算21

Gemini CLI

8.81%
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

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

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