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testing-ci测试 CI

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

339

周安装

14

GitHub Stars

4

下载量

111
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:testing-ci(测试 CI)
来源仓库:https://github.com/alphaonedev/openclaw-graph
仓库路径:skills/testing-ci
安装命令:
npx skills add https://github.com/alphaonedev/openclaw-graph --skill testing-ci
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/alphaonedev/openclaw-graph --skill testing-ci

简介

用于持续集成流程中的自动化测试执行与管理。

  • 适合配置测试任务、解析日志和触发告警通知。
  • 支持并行测试、缓存优化和资源调度策略。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。
  • 应与代码提交频率匹配以保证反馈及时性。
  • testing-ci 属于开发类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

testing-ci

Purpose

This skill automates CI/CD pipelines using GitHub Actions, focusing on testing workflows. It handles parallel test execution, quarantines flaky tests, generates reports in JUnit XML or Allure formats, and enforces coverage gates to ensure code quality in repositories.

When to Use

Use this skill when setting up or optimizing CI for GitHub repos, especially for projects with large test suites (e.g., >1000 tests), to reduce run times via parallel sharding. Apply it for flaky test management in unstable environments or when integrating coverage checks before merges.

Key Capabilities

  • Configure GitHub Actions workflows with parallel sharding using the matrix strategy in YAML.
  • Quarantine flaky tests by marking them in reports and rerunning subsets automatically.
  • Generate JUnit XML reports via tools like junit-report or Allure for detailed test insights.
  • Enforce coverage gates with thresholds (e.g., >80% line coverage) using tools like Codecov.
  • Integrate with GitHub APIs for workflow dispatching and status checks, requiring authentication via $GITHUB_TOKEN.

Usage Patterns

Invoke this skill via OpenClaw CLI commands prefixed with openclaw testing-ci. For API usage, send requests to the OpenClaw endpoint (e.g., POST /api/skills/testing-ci). In code, embed it in scripts by checking for the skill ID and passing parameters like workflow names or test shards. Always set environment variables for secrets, such as $GITHUB_TOKEN, before execution. For parallel testing, define shards in your workflow YAML and trigger runs programmatically.

Common Commands/API

  • CLI: Run a workflow with parallel sharding: openclaw testing-ci run --workflow my-repo/tests.yml --parallel 4 --token $GITHUB_TOKEN
  • CLI: Quarantine flaky tests: openclaw testing-ci quarantine --pattern "flaky-*" --report junit.xml
  • API: Create a workflow: POST /api/skills/testing-ci/workflows with JSON body: {"name": "build", "matrix": {"shards": [1,2,3,4]}}
  • API: Get coverage report: GET /api/skills/testing-ci/coverage?gate=80
  • Code snippet (YAML config for GitHub Actions): jobs: test: strategy: matrix: shard: [1, 2, 3, 4] run: npm test --shard=${{matrix.shard}}/4
  • Code snippet (Shell script to handle flaky tests): if grep -q "flaky" junit.xml; then openclaw testing-ci quarantine --file junit.xml fi

Integration Notes

Integrate with GitHub by providing a personal access token in $GITHUB_TOKEN for API calls. For JUnit/Allure reports, ensure your workflow outputs XML files and upload them via GitHub Actions artifacts. Use parallel sharding by defining matrices in workflow YAML, then trigger via OpenClaw: openclaw testing-ci dispatch --repo owner/repo --ref main. For coverage gates, integrate with services like Codecov by adding a step in your workflow: curl -Os codecov.io/bash && bash codecov -t $CODECOV_TOKEN. Always validate inputs to avoid errors, such as checking if $GITHUB_TOKEN is set.

Error Handling

Handle workflow failures by checking exit codes in scripts (e.g., if $?!= 0, retry with openclaw testing-ci rerun --workflow ID). For API errors, parse responses for status codes (e.g., 401 for auth issues, resolve by verifying $GITHUB_TOKEN). In parallel runs, use sharding to isolate failures; quarantine flaky tests to prevent false negatives. Common issues: Invalid YAML syntax—validate with yamllint before running; coverage gate failures—adjust thresholds via config flags like --gate 75.

Concrete Usage Examples

  1. Set up parallel CI for a Node.js repo: Create a workflow file, then run: openclaw testing-ci run --workflow.github/workflows/tests.yml --parallel 4 --token $GITHUB_TOKEN. This shards tests across 4 runners, reducing execution time from 10m to 3m, and generates a JUnit report for analysis.
  2. Quarantine and report flaky tests: After a failed run, execute: openclaw testing-ci quarantine --report allure-results.xml --pattern "test_flaky_*". This isolates flaky tests, reruns them, and integrates the Allure report into your GitHub workflow for visual debugging.

Graph Relationships

  • Related to cluster: "testing" (e.g., links to skills like "unit-testing" for deeper test implementation).
  • Tagged with: "ci-cd" (connects to "deployment" skills), "github-actions" (integrates with "repo-management"), "parallel" (shares with "scalability" tools), "flaky" (links to "error-analysis"), "testing" (groups with "test-automation").

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

38.06%
按下载量换算42

Claude

32.15%
按下载量换算36

Cursor

16.76%
按下载量换算19

Gemini CLI

8.73%
按下载量换算10

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

可疑

权限和风险

敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。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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