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Agent Skill · 开发

python-testing(Python 测试)

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。它适合让 Agent 阅读 Python 代码、定位测试问题、整理运行命令、生成脚本或分析数据处理逻辑。使用时需要确认项目虚拟环境、依赖版本和测试入口;涉及执行脚本、读写文件、访问数据库或调用外部 API 时,应先明确运行目录和输入输出范围,避免误改生产数据。

python-testing 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,按安装量在开发类的 21,746 个 Skill 里排第 18,332。

总安装 346周安装 14GitHub Stars 9,988下载 109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:python-testing(Python 测试)
来源仓库:https://github.com/microsoft/agent-framework
仓库路径:skills/python-testing
安装命令:
npx skills add https://github.com/microsoft/agent-framework --skill python-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。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/microsoft/agent-framework --skill python-testing

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。

用于辅助 Python 项目开发、测试、依赖管理和常见框架工作流。适合阅读代码、定位测试问题、生成脚本或分析数据处理逻辑。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。使用时需确认虚拟环境、依赖版本和测试入口,避免误改生产数据。

python-testing 属于开发类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/python-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/microsoft/agent-framework --skill python-testi…;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

python-testing 怎么安装?

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

python-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。

python-testing 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。

python-testing 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。

python-testing 用的人多吗?

公开数据是累计安装 346 次,近一周安装 14 次,下载 109 次,GitHub 9,988 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。

python-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。
  • 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 9,988 星,维护活跃度相对可查。

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
python-testing

Python 测试 · 本页

3469,988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

Python Testing

We strive for at least 85% test coverage across the codebase, with a focus on core packages and critical paths. Tests should be fast, reliable, and maintainable. When adding new code, check that the relevant sections of the codebase are covered by tests, and add new tests as needed. When modifying existing code, update or add tests to cover the changes. We run tests in two stages, for a PR each commit is tested with unit tests only (using -m "not integration"), and the full suite including integration tests is run when merging.

Running Tests

# Run tests for all packages in parallel
uv run poe test

# Run tests for a specific workspace package
uv run poe test -P core

# Run all selected tests in a single pytest invocation
uv run poe test -A

# With coverage
uv run poe test -A -C
uv run poe test -P core -C

# Run only unit tests (exclude integration tests)
uv run poe test -A -m "not integration"

# Run only integration tests
uv run poe test -A -m integration

Direct package execution still works when you need it:

uv run --directory packages/core poe test

Test Configuration

  • Async mode: asyncio_mode = "auto" is enabled — do NOT use @pytest.mark.asyncio, but do mark tests with async def and use await for async calls
  • Timeout: Default 60 seconds per test
  • Import mode: importlib for cross-package isolation
  • Parallelization: Large packages (core, ag-ui, orchestrations, anthropic) use pytest-xdist (-n auto --dist worksteal) in their poe test task. The aggregate uv run poe test -A sweep also uses xdist across the selected packages.

Test Directory Structure

Test directories must NOT contain __init__.py files.

Non-core packages must place tests in a uniquely-named subdirectory:

packages/anthropic/
├── tests/
│   └── anthropic/       # Unique subdirectory matching package name
│       ├── conftest.py
│       └── test_client.py

Core package can use tests/ directly with topic subdirectories:

packages/core/
├── tests/
│   ├── conftest.py
│   ├── core/
│   │   └── test_agents.py
│   └── openai/
│       └── test_client.py

Fixture Guidelines

  • Use conftest.py for shared fixtures within a test directory
  • Before adding new fixtures, check if existing ones can be reused or extended
  • Use descriptive names: mapper, test_request, mock_client

File Naming

  • Files starting with test_ are test files — do not use this prefix for helpers
  • Use conftest.py for shared utilities

Integration Tests

Integration tests require external services (OpenAI, Azure, etc.) and are controlled by three markers:

  1. @pytest.mark.flaky — marks the test as potentially flaky since it depends on external services
  2. @pytest.mark.integration — used for test selection, so integration tests can be included/excluded with -m integration / -m "not integration"
  3. @skip_if_..._integration_tests_disabled decorator — skips the test when the required API keys or service endpoints are missing

Adding New Integration Tests

All three markers must be applied to every new integration test:

@pytest.mark.flaky
@pytest.mark.integration
@skip_if_openai_integration_tests_disabled
async def test_openai_chat_completion() -> None:
    ...

For test files where all tests are integration tests (e.g., Azure Functions, Durable Task), use the module-level pytestmark list:

pytestmark = [
    pytest.mark.flaky,
    pytest.mark.integration,
    pytest.mark.sample("01_single_agent"),
    pytest.mark.usefixtures("function_app_for_test"),
]

CI Workflow

The merge CI workflow (python-merge-tests.yml) splits integration tests into parallel jobs by provider with change-based detection:

  • Unit tests — always run all non-integration tests
  • OpenAI integration — runs when packages/core/agent_framework/openai/ or core infrastructure changes
  • Azure OpenAI integration — runs when packages/core/agent_framework/azure/ or core changes
  • Misc integration — Anthropic, Ollama, MCP tests; runs when their packages or core change
  • Functions integration — Azure Functions + Durable Task; runs when their packages or core change
  • Foundry integration — runs when packages/foundry/ or core changes

Core infrastructure changes (e.g., _agents.py, _types.py) trigger all integration test jobs. Scheduled and manual runs always execute all jobs.

Keeping CI Workflows in Sync

Two workflow files define the same set of parallel test jobs:

  • python-merge-tests.yml — runs on PRs, merge queue, schedule, and manual dispatch. Uses path-based change detection to skip unaffected integration jobs.
  • python-integration-tests.yml — called from the manual integration test orchestrator (integration-tests-manual.yml). Always runs all jobs (no path filtering).

These workflows must be kept in sync. When you add, remove, or modify a test job, update both files. The job structure, pytest commands, and xdist flags should match between them. The only difference is that python-merge-tests.yml has path filters and conditional job execution, while python-integration-tests.yml does not.

Updating the CI When Adding Integration Tests for a New Provider

When adding integration tests for a new provider package, you must update both python-merge-tests.yml and python-integration-tests.yml:

  1. Add a path filter for the new provider in the paths-filter job in python-merge-tests.yml so the CI knows which file changes should trigger those tests.
  2. Add the test job to both workflow files — either add them to the existing python-tests-misc-integration job, or create a dedicated job if the provider:

- Has a large number of integration tests - Requires special infrastructure setup (emulators, Docker containers, etc.) - Has long-running tests that would slow down the misc job

The python-tests-misc-integration job is intended for small integration test suites that don't need dedicated infrastructure. When a provider's integration tests grow large or gain special requirements, split them out into their own job (like python-tests-functions was split out for Azure Functions + Durable Task).

Best Practices

  • Run only related tests, not the entire suite
  • Review existing tests to understand coding style before creating new ones
  • Use print statements for debugging, then remove them when done
  • Resolve all errors and warnings before committing

平台分布

Codex

37.78%
按下载量换算41

Claude

31.41%
按下载量换算34

Cursor

18.61%
按下载量换算20

Gemini CLI

8.96%
按下载量换算10

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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