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Agent Skill · 研究检索

create-skill-test(创建技能测试)

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。

create-skill-test 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,权限为执行命令;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 23,650。

总安装 4,211周安装 172GitHub Stars 1,476下载 1,362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:create-skill-test(创建技能测试)
来源仓库:https://github.com/dotnet/skills
仓库路径:skills/create-skill-test
安装命令:
npx skills add https://github.com/dotnet/skills --skill create-skill-test
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/dotnet/skills --skill create-skill-test

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。

create-skill-test 用于辅助设计符合规范的评估测试用例,确保技能通过验证并避免过拟合。适用于 Codex、Claude、Cursor、Gemini CLI 等宿主环境,适合技能开发者编写单元测试或端到端验证。提供 eval.yaml 模板、夹具文件和断言建议,支持多场景覆盖与回归检查。

安装前请确认项目测试框架、运行命令及是否涉及敏感数据或外部服务调用。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/create-skill-test

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/dotnet/skills --skill create-skill-test;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

    它需要执行命令,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

create-skill-test 怎么安装?

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

create-skill-test 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。

create-skill-test 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/dotnet/skills --skill create-skill-test 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

create-skill-test 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。

create-skill-test 用的人多吗?

公开数据是累计安装 4,211 次,近一周安装 172 次,下载 1,362 次,GitHub 1,476 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。

create-skill-test 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。
  • 来源仓库有 1,476 星,维护活跃度相对可查。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 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

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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
create-skill-test

创建技能测试 · 本页

4,2111,476执行命令未明确通过

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

Create Skill Test

This skill helps you scaffold evaluation tests (eval.yaml) for agent skills, ensuring they conform to the dotnet/skills repository conventions, pass the skill-validator checks, and avoid common overfitting pitfalls.

When to Use

  • Creating a new eval.yaml test file for a skill
  • Adding scenarios to an existing eval file
  • Setting up test fixture files alongside eval definitions
  • Reviewing whether rubric items and assertions risk overfitting

When Not to Use

  • Running or debugging existing tests (use the skill-validator directly)
  • Modifying the skill-validator tool itself
  • Creating or editing SKILL.md files (use the create-skill skill)

Inputs

InputRequiredDescription
Skill nameYesThe skill being tested (must match a skill under plugins/<plugin>/skills/)
Plugin nameYesThe plugin the skill belongs to (e.g., dotnet-msbuild)
Skill contentRecommendedThe SKILL.md content to understand what the skill teaches
Scenario descriptionsRecommendedWhat situations the agent should be tested on

Workflow

Step 1: Locate the target and determine the test directory

Tests live at:

# For skills:
tests/<plugin>/<skill-name>/eval.yaml

# For agents (agent. prefix convention):
tests/<plugin>/agent.<agent-name>/eval.yaml

For skills, verify the skill exists at plugins/<plugin>/skills/<skill-name>/SKILL.md. For agents, verify the agent exists at plugins/<plugin>/agents/<agent-name>.agent.md. Read the target content to understand what it does -- this is critical for writing non-overfitted rubric items.

Step 2: Create the test directory and eval.yaml

Create the directory and file:

# For skills:
tests/<plugin>/<skill-name>/
+-- eval.yaml

# For agents:
tests/<plugin>/agent.<agent-name>/
+-- eval.yaml

The agent. prefix disambiguates agent test directories from skill test directories that might share the same name.

Step 3: Write scenarios

Each scenario needs a name, prompt, at least one assertion, and a rubric. Use this structure:

scenarios:
  - name: "Descriptive scenario name"
    prompt: "Natural language task description as a developer would phrase it"
    setup:
      copy_test_files: true          # OR use inline files
    assertions:
      - type: "output_contains"
        value: "expected text"
    rubric:
      - "The agent correctly identified the root cause"
      - "The agent suggested a concrete, actionable fix"
    timeout: 120
Scenario guidelines
  • Name: Describe *what* is being tested, not *how* (e.g., "Diagnose missing package reference" not "Test binlog replay and error extraction").
  • Prompt: Write as a natural developer request. Never mention the skill name or instruct the agent to "use a skill." Neutral prompts prevent prompt overfitting.
  • Timeout: Default is 120 seconds. Use 300-600 for scenarios requiring builds, benchmarks, or multi-step operations.

Step 4: Configure setup

Choose one of three setup strategies:

Option A: Copy test files (recommended for complex fixtures)

Place fixture files alongside eval.yaml and enable auto-copy:

setup:
  copy_test_files: true

All files in the directory (except eval.yaml) are copied into the agent's working directory.

Option B: Inline files (good for small, self-contained scenarios)
setup:
  files:
    - path: "MyProject/MyProject.csproj"
      content: |
        <Project Sdk="Microsoft.NET.Sdk">
          <PropertyGroup>
            <TargetFramework>net10.0</TargetFramework>
          </PropertyGroup>
        </Project>
    - path: "MyProject/Program.cs"
      content: |
        Console.WriteLine("Hello");
Option C: Reference fixture files from a subdirectory
setup:
  files:
    - path: "TestProject.csproj"
      source: "fixtures/scenario-a/TestProject.csproj"

Use this when multiple scenarios share a fixtures/ directory with separate subdirectories.

Setup commands (optional)

Run shell commands before the agent starts (e.g., to build a project and generate artifacts):

setup:
  copy_test_files: true
  commands:
    - "dotnet build -bl:build.binlog"
Scenario dependencies (optional)

Some agents route to specific skills, or some skills depend on sibling agents. In the isolated run, only the target is loaded — so the scenario must declare its dependencies using additional_required_skills and/or additional_required_agents:

setup:
  copy_test_files: true
  additional_required_skills:
    - binlog-failure-analysis    # loaded in isolated run alongside the target
  additional_required_agents:
    - build-perf                 # registered in isolated run alongside the target
  • Names are resolved from the same plugin's skills/ or agents/ directory.
  • These only affect the isolated run. The plugin run already loads everything; the baseline loads nothing.
  • Different scenarios of the same target can declare different dependencies (per-scenario granularity).
  • If a declared name cannot be resolved, the validator fails with an error.

Step 5: Write assertions

Assertions are hard pass/fail checks. Use them for objective, binary-verifiable criteria.

TypeRequired fieldsDescription
output_containsvalueAgent output contains text (case-insensitive)
output_not_containsvalueAgent output must NOT contain text
output_matchespatternAgent output matches regex
output_not_matchespatternAgent output does NOT match regex
file_existspathFile matching glob exists in work dir
file_not_existspathNo file matching glob exists
file_containspath, valueFile at glob path contains text
file_not_containspath, valueFile at glob path does NOT contain text
exit_success--Agent produced non-empty output
Assertion guidelines
  • Prefer broad assertions that multiple valid approaches would satisfy.
  • Avoid narrow assertions that gate on a specific syntax or flag the LLM already knows.
  • Use output_matches with regex alternation for flexible matching: "(root cause|primary error|underlying issue)".
  • Use file_contains / file_not_contains to verify the agent modified files correctly.
  • Use output_not_contains and file_not_exists to verify the agent avoided incorrect actions.

Step 6: Write rubric items

Rubric items are evaluated by an LLM judge using pairwise comparison (baseline vs. skill-enhanced). Quality metrics (rubric-based at 40% weight plus overall judgment at 30%) together dominate the composite improvement score.

The three rubric classifications (and how to stay in "outcome")

The overfitting judge classifies each rubric item:

ClassificationDescriptionGoal
outcomeTests whether the agent reached a correct result. Describes WHAT, not HOW.Target this
techniqueTests whether the agent used a skill-specific procedure.Minimize
vocabularyTests whether the agent used specific terminology from the skill.Avoid
Rubric writing rules
  1. Test outcomes, not methods. Write "Identified the root cause of the build failure" -- not "Replayed the binlog using dotnet build /flp."
  2. Allow alternative approaches. If multiple valid solutions exist, the rubric item should accept any of them.
  3. Never reference the skill by name or use phrasing copied directly from the SKILL.md.
  4. Don't test pre-existing LLM knowledge. If the LLM already knows something (common APIs, standard syntax, basic escaping), testing for it adds no signal.
  5. Test findings, not diagnostic steps. Write "Correctly determined that the root cause is a missing PackageReference" -- not "Used dotnet restore to check package resolution."
  6. Each item should be independently evaluable. Avoid compound items that test multiple things.
Examples

Well-designed (outcome-focused):

rubric:
  - "Correctly identified the missing NuGet package as the root cause of the build failure"
  - "Recognized that downstream project failures were cascading from the root cause, not independent errors"
  - "Suggested a concrete fix that would resolve the root cause"

Overfitted (vocabulary/technique):

rubric:
  - "Replayed the binary log using 'dotnet build /flp:v=diag'"      # technique: gates on specific command
  - "Measured cold, warm, and no-op build scenarios"                  # vocabulary: uses skill's labels
  - "Used the --clreventlevel flag with dotnet trace collect"         # vocabulary: gates on specific flag

Step 7: Add optional constraints

expect_tools: ["bash"]           # Agent must use these tools
reject_tools: ["create_file"]    # Agent must NOT use these tools
max_turns: 10                    # Maximum agent iterations
max_tokens: 5000                 # Maximum token budget

Use constraints sparingly -- only when the scenario specifically requires or forbids certain agent behaviors.

Step 8: Add non-activation scenarios with expect_activation: false

Many skills have clear boundaries -- situations where the skill should recognize it does not apply and decline gracefully. Test these boundaries using expect_activation: false.

How expect_activation: false works

When a scenario has expect_activation: false:

  1. All three runs still execute (baseline, skilled-isolated, skilled-plugin) and assertions are evaluated on each. The flag does not change which runs are performed.
  2. Activation verdict is inverted -- if the skill is not activated for this prompt, the evaluator reports it as [Info] not activated (expected) instead of treating it as a failure.
  3. The scenario is excluded from the noise test -- the multi-skill activation test only runs positive (expect_activation: true) scenarios.
When to use non-activation scenarios

Add expect_activation: false scenarios when the skill has explicit "When Not to Use" boundaries. Common patterns:

PatternExample
Wrong input formatSkill handles Android tombstones; scenario provides an iOS crash log
Out-of-scope requestSkill collects dumps; scenario asks to *analyze* a dump
Incompatible project typeSkill converts PackageReference to CPM; scenario has packages.config
Wrong framework versionSkill migrates.NET 8 to 9; scenario provides a.NET 8 app and asks for.NET 10 migration
Prerequisite not metSkill requires a specific file format that isn't present
Example: Wrong input format
- name: "Reject iOS crash log as wrong format"
  prompt: "I have a crash log file at crashlog_ios.txt from a crashed app. Please symbolicate the .NET runtime frames."
  expect_activation: false
  setup:
    copy_test_files: true
  assertions:
    - type: "output_matches"
      pattern: "(iOS|Apple|not.*(Android|tombstone)|wrong.*(format|type))"
  rubric:
    - "Recognized that this is an iOS crash log, not an Android tombstone"
    - "Did NOT attempt to apply the Android tombstone symbolication workflow"
    - "Explained that iOS crash logs require a different symbolication process"
Example: Out-of-scope request
- name: "Decline dump analysis request"
  prompt: |
    I already have a .dmp crash dump file from my .NET app. Can you help
    me analyze it to find the root cause of the crash?
  expect_activation: false
  assertions:
    - type: "output_matches"
      pattern: "(out of scope|not cover|does not|cannot|only.*collect)"
  rubric:
    - "Clearly states that dump analysis is out of scope for this skill"
    - "Does not attempt to open or analyze the dump file"
    - "Does not install analysis tools like dotnet-dump analyze, lldb, or windbg"
  timeout: 30
Example: Incompatible project type
- name: "Decline CPM conversion for packages.config project"
  prompt: "Convert my simple-packages-config/LegacyApp project to Central Package Management."
  expect_activation: false
  setup:
    copy_test_files: true
  assertions:
    - type: "output_contains"
      value: "packages.config"
    - type: "file_not_exists"
      path: "simple-packages-config/Directory.Packages.props"
  rubric:
    - "Detected the project uses packages.config instead of PackageReference format"
    - "Informed the user that CPM requires PackageReference and cannot be applied to packages.config projects"
    - "Suggested migrating from packages.config to PackageReference first"
    - "Did not attempt to create Directory.Packages.props or modify any project files"
Rubric guidelines for non-activation scenarios

Non-activation rubric items typically verify three things:

  1. Recognition -- The agent identified *why* the skill doesn't apply.
  2. Restraint -- The agent did NOT attempt the skill's workflow (no file modifications, no tool installs).
  3. Redirection -- The agent suggested the correct alternative approach or next step.

Step 9: Validate the eval.yaml

Run the static validator:

dotnet run --project eng/skill-validator/src/SkillValidator.csproj -- check --plugin ./plugins/<plugin>

Then run evaluation (at least 3 runs for reliable results):

# For skills:
dotnet run --project eng/skill-validator/src/SkillValidator.csproj -- evaluate \
  --runs 3 \
  --tests-dir tests/<plugin> \
  plugins/<plugin>/skills/<skill-name>

# For agents:
dotnet run --project eng/skill-validator/src/SkillValidator.csproj -- evaluate \
  --runs 3 \
  --tests-dir tests/<plugin> \
  plugins/<plugin>/agents/<agent-name>.agent.md

eval.yaml Template

scenarios:
  - name: "<Describe what the agent should accomplish>"
    prompt: "<Natural developer request -- do not mention the skill>"
    setup:
      copy_test_files: true
    assertions:
      - type: "output_contains"
        value: "<key term that a correct response must include>"
      - type: "exit_success"
    rubric:
      - "<Outcome: what the agent should have identified or produced>"
      - "<Outcome: what fix or recommendation the agent should have given>"
      - "<Outcome: what incorrect approach the agent should have avoided>"
    timeout: 120

  - name: "<Describe situation where the skill should NOT apply>"
    prompt: "<Request that superficially matches the skill but falls outside its scope>"
    expect_activation: false
    setup:
      copy_test_files: true
    assertions:
      - type: "output_matches"
        pattern: "<pattern matching the agent's explanation of why it cannot help>"
      - type: "file_not_exists"
        path: "<file the skill would create if it incorrectly activated>"
    rubric:
      - "<Recognition: agent identified why the skill does not apply>"
      - "<Restraint: agent did not attempt the skill's workflow>"
      - "<Redirection: agent suggested the correct alternative>"
    timeout: 120

Validation Checklist

After creating a test, verify:

  • Test directory matches tests/<plugin>/<skill-name>/ for skills or tests/<plugin>/agent.<agent-name>/ for agents
  • Target exists at plugins/<plugin>/skills/<skill-name>/SKILL.md (skill) or plugins/<plugin>/agents/<agent-name>.agent.md (agent)
  • Every scenario has name, prompt, at least one assertion, and rubric items
  • Prompts are written as natural developer requests (no skill/agent name references)
  • Assertions are broad enough that multiple valid approaches pass
  • Rubric items test outcomes, not specific techniques or vocabulary
  • Fixture files are present when copy_test_files: true is used
  • source paths in setup files point to existing fixture files
  • additional_required_skills/additional_required_agents names exist in the same plugin
  • Timeouts are reasonable for the scenario complexity
  • Non-activation scenarios use expect_activation: false and verify recognition, restraint, and redirection
  • dotnet run --project eng/skill-validator/src/SkillValidator.csproj -- check passes

Common Pitfalls

PitfallSolution
Prompt mentions the skill by nameRewrite as a natural developer request describing the problem
Prompt mentions the agent by nameSame as above — agent name in prompts biases the baseline
Rubric tests a specific diagnostic commandRewrite to test the finding or outcome that command produces
Assertion gates on syntax the LLM already knowsUse a broader pattern or test the result instead
All rubric items test the same aspectDiversify: test identification, fix quality, and error avoidance
Missing fixture files for copy_test_filesAdd the required project/source files alongside eval.yaml
Timeout too short for buildsUse 300-600s for scenarios that compile or run benchmarks
Single scenario covers the entire skillBreak into focused scenarios testing different aspects
Compound rubric items testing multiple thingsSplit into separate, independently-evaluable items
No non-activation scenarios for skill with clear boundariesAdd expect_activation: false scenarios for each "When Not to Use" case
Agent test missing additional_required_skillsIf the agent routes to specific skills, declare them so the isolated run loads them

平台分布

Codex

34.44%
按下载量换算469

Claude

31.7%
按下载量换算432

Cursor

20.13%
按下载量换算274

Gemini CLI

9.69%
按下载量换算132

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/dotnet/skills --skill create-skill-test 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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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