[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M71H0X64RJC0VKXYPTH3BPQ2":3,"skill-same:01M71H0X64RJC0VKXYPTH3BPQ2":59},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":15,"categories":16,"keywords":17,"publishedAt":26,"linkOnly":27,"markdownContent":28,"markdownBody":29,"frontMatter":30,"refName":32,"commitSha":33,"skillDirectory":34,"forksCount":35,"repositoryHtmlUrl":36,"repositoryHomepageUrl":6,"ownerHtmlUrl":37,"ownerBlogUrl":6,"ownerDescription":6,"updatedAt":38,"install":39,"resources":52},"01M71H0X64RJC0VKXYPTH3BPQ2","processes",null,"Background jobs, long-running processes, and task management","JSGforever\u002Fskillguard","JSGforever","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F85541948?v=4","01M71FQD3E132VMR5F4TAYX3YS","01M71FQD4DYW0XJ4XQ4YQH75Y9",2,"GPL-3.0","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__alsk1992--processes\u002FSKILL.md",[],[5,18,19,20,21,22,23,24,25],"running","task management","long","task","background jobs","management","jobs","background","2026-11-10 10:12:30",false,"---\nname: processes\ndescription: \"Background jobs, long-running processes, and task management\"\nemoji: \"⚙️\"\n---\n\n# Processes - Complete API Reference\n\nSpawn and manage background processes, long-running jobs, and scheduled tasks.\n\n---\n\n## Chat Commands\n\n### Spawn Jobs\n\n```\n\u002Fjob spawn \"npm run backtest\"               Start background job\n\u002Fjob spawn \"python train.py\" --name ml      Named job\n\u002Fjob spawn \"node bot.js\" --restart          Auto-restart on exit\n```\n\n### Manage Jobs\n\n```\n\u002Fjobs                                       List all jobs\n\u002Fjob status \u003Cid>                            Check job status\n\u002Fjob output \u003Cid>                            View job output\n\u002Fjob output \u003Cid> --follow                   Stream output\n\u002Fjob stop \u003Cid>                              Stop job\n\u002Fjob restart \u003Cid>                           Restart job\n```\n\n### Logs\n\n```\n\u002Fjob logs \u003Cid>                              View logs\n\u002Fjob logs \u003Cid> --tail 100                   Last 100 lines\n\u002Fjob logs \u003Cid> --since 1h                   Last hour\n```\n\n---\n\n## TypeScript API Reference\n\n### Create Process Manager\n\n```typescript\nimport { createProcessManager } from 'clodds\u002Fprocesses';\n\nconst processes = createProcessManager({\n  \u002F\u002F Working directory\n  cwd: process.cwd(),\n\n  \u002F\u002F Environment\n  env: process.env,\n\n  \u002F\u002F Limits\n  maxProcesses: 10,\n  maxMemoryMB: 1024,\n\n  \u002F\u002F Logging\n  logDir: '.\u002Flogs\u002Fjobs',\n  maxLogSizeMB: 100,\n\n  \u002F\u002F Storage\n  storage: 'sqlite',\n  dbPath: '.\u002Fjobs.db',\n});\n```\n\n### Spawn Process\n\n```typescript\n\u002F\u002F Simple spawn\nconst job = await processes.spawn({\n  command: 'npm',\n  args: ['run', 'backtest'],\n  name: 'backtest-btc',\n});\n\nconsole.log(`Job ID: ${job.id}`);\nconsole.log(`PID: ${job.pid}`);\n\n\u002F\u002F With options\nconst job = await processes.spawn({\n  command: 'python',\n  args: ['train.py', '--epochs', '100'],\n  name: 'ml-training',\n\n  \u002F\u002F Environment\n  env: {\n    ...process.env,\n    CUDA_VISIBLE_DEVICES: '0',\n  },\n\n  \u002F\u002F Working directory\n  cwd: '\u002Fpath\u002Fto\u002Fml-project',\n\n  \u002F\u002F Auto-restart\n  restart: true,\n  maxRestarts: 3,\n  restartDelayMs: 5000,\n\n  \u002F\u002F Resource limits\n  maxMemoryMB: 4096,\n  timeoutMs: 3600000,  \u002F\u002F 1 hour\n});\n```\n\n### List Jobs\n\n```typescript\nconst jobs = await processes.list();\n\nfor (const job of jobs) {\n  console.log(`${job.id}: ${job.name}`);\n  console.log(`  Status: ${job.status}`);  \u002F\u002F 'running' | 'stopped' | 'failed' | 'completed'\n  console.log(`  PID: ${job.pid}`);\n  console.log(`  Started: ${job.startedAt}`);\n  console.log(`  Memory: ${job.memoryMB}MB`);\n  console.log(`  CPU: ${job.cpuPercent}%`);\n}\n```\n\n### Get Status\n\n```typescript\nconst status = await processes.getStatus(jobId);\n\nconsole.log(`Status: ${status.status}`);\nconsole.log(`Exit code: ${status.exitCode}`);\nconsole.log(`Runtime: ${status.runtimeMs}ms`);\nconsole.log(`Restarts: ${status.restarts}`);\nconsole.log(`Memory: ${status.memoryMB}MB`);\nconsole.log(`CPU: ${status.cpuPercent}%`);\n```\n\n### Get Output\n\n```typescript\n\u002F\u002F Get all output\nconst output = await processes.getOutput(jobId);\nconsole.log(output.stdout);\nconsole.log(output.stderr);\n\n\u002F\u002F Get last N lines\nconst output = await processes.getOutput(jobId, { tail: 100 });\n\n\u002F\u002F Stream output\nconst stream = processes.streamOutput(jobId);\nstream.on('stdout', (data) => console.log(data));\nstream.on('stderr', (data) => console.error(data));\nstream.on('exit', (code) => console.log(`Exit: ${code}`));\n```\n\n### Stop Job\n\n```typescript\n\u002F\u002F Graceful stop (SIGTERM)\nawait processes.stop(jobId);\n\n\u002F\u002F Force kill (SIGKILL)\nawait processes.stop(jobId, { force: true });\n\n\u002F\u002F Stop all\nawait processes.stopAll();\n```\n\n### Restart Job\n\n```typescript\nawait processes.restart(jobId);\n```\n\n### Event Handlers\n\n```typescript\nprocesses.on('started', (job) => {\n  console.log(`Job started: ${job.name}`);\n});\n\nprocesses.on('stopped', (job) => {\n  console.log(`Job stopped: ${job.name} (code: ${job.exitCode})`);\n});\n\nprocesses.on('failed', (job, error) => {\n  console.error(`Job failed: ${job.name}`, error);\n});\n\nprocesses.on('output', (job, type, data) => {\n  console.log(`[${job.name}] ${type}: ${data}`);\n});\n```\n\n---\n\n## Job Status\n\n| Status | Description |\n|--------|-------------|\n| `running` | Currently executing |\n| `stopped` | Stopped by user |\n| `completed` | Finished successfully |\n| `failed` | Exited with error |\n| `restarting` | Auto-restarting |\n\n---\n\n## Use Cases\n\n### Run Backtest\n\n```typescript\nconst job = await processes.spawn({\n  command: 'npm',\n  args: ['run', 'backtest', '--', '--strategy', 'momentum'],\n  name: 'backtest-momentum',\n});\n\n\u002F\u002F Wait for completion\nconst result = await processes.wait(job.id);\nconsole.log(`Backtest complete: ${result.exitCode === 0 ? 'success' : 'failed'}`);\n```\n\n### Train ML Model\n\n```typescript\nconst job = await processes.spawn({\n  command: 'python',\n  args: ['train.py'],\n  name: 'ml-training',\n  cwd: '.\u002Fml',\n  maxMemoryMB: 8192,\n  timeoutMs: 86400000,  \u002F\u002F 24 hours\n});\n\n\u002F\u002F Monitor progress\nprocesses.streamOutput(job.id).on('stdout', (line) => {\n  if (line.includes('Epoch')) {\n    console.log(line);\n  }\n});\n```\n\n---\n\n## Best Practices\n\n1. **Name your jobs** — Easier to identify\n2. **Set timeouts** — Prevent runaway processes\n3. **Monitor memory** — Prevent OOM kills\n4. **Use restart sparingly** — Debug failures first\n5. **Check logs** — Always review output\n","# Processes - Complete API Reference\n\nSpawn and manage background processes, long-running jobs, and scheduled tasks.\n\n---\n\n## Chat Commands\n\n### Spawn Jobs\n\n```\n\u002Fjob spawn \"npm run backtest\"               Start background job\n\u002Fjob spawn \"python train.py\" --name ml      Named job\n\u002Fjob spawn \"node bot.js\" --restart          Auto-restart on exit\n```\n\n### Manage Jobs\n\n```\n\u002Fjobs                                       List all jobs\n\u002Fjob status \u003Cid>                            Check job status\n\u002Fjob output \u003Cid>                            View job output\n\u002Fjob output \u003Cid> --follow                   Stream output\n\u002Fjob stop \u003Cid>                              Stop job\n\u002Fjob restart \u003Cid>                           Restart job\n```\n\n### Logs\n\n```\n\u002Fjob logs \u003Cid>                              View logs\n\u002Fjob logs \u003Cid> --tail 100                   Last 100 lines\n\u002Fjob logs \u003Cid> --since 1h                   Last hour\n```\n\n---\n\n## TypeScript API Reference\n\n### Create Process Manager\n\n```typescript\nimport { createProcessManager } from 'clodds\u002Fprocesses';\n\nconst processes = createProcessManager({\n  \u002F\u002F Working directory\n  cwd: process.cwd(),\n\n  \u002F\u002F Environment\n  env: process.env,\n\n  \u002F\u002F Limits\n  maxProcesses: 10,\n  maxMemoryMB: 1024,\n\n  \u002F\u002F Logging\n  logDir: '.\u002Flogs\u002Fjobs',\n  maxLogSizeMB: 100,\n\n  \u002F\u002F Storage\n  storage: 'sqlite',\n  dbPath: '.\u002Fjobs.db',\n});\n```\n\n### Spawn Process\n\n```typescript\n\u002F\u002F Simple spawn\nconst job = await processes.spawn({\n  command: 'npm',\n  args: ['run', 'backtest'],\n  name: 'backtest-btc',\n});\n\nconsole.log(`Job ID: ${job.id}`);\nconsole.log(`PID: ${job.pid}`);\n\n\u002F\u002F With options\nconst job = await processes.spawn({\n  command: 'python',\n  args: ['train.py', '--epochs', '100'],\n  name: 'ml-training',\n\n  \u002F\u002F Environment\n  env: {\n    ...process.env,\n    CUDA_VISIBLE_DEVICES: '0',\n  },\n\n  \u002F\u002F Working directory\n  cwd: '\u002Fpath\u002Fto\u002Fml-project',\n\n  \u002F\u002F Auto-restart\n  restart: true,\n  maxRestarts: 3,\n  restartDelayMs: 5000,\n\n  \u002F\u002F Resource limits\n  maxMemoryMB: 4096,\n  timeoutMs: 3600000,  \u002F\u002F 1 hour\n});\n```\n\n### List Jobs\n\n```typescript\nconst jobs = await processes.list();\n\nfor (const job of jobs) {\n  console.log(`${job.id}: ${job.name}`);\n  console.log(`  Status: ${job.status}`);  \u002F\u002F 'running' | 'stopped' | 'failed' | 'completed'\n  console.log(`  PID: ${job.pid}`);\n  console.log(`  Started: ${job.startedAt}`);\n  console.log(`  Memory: ${job.memoryMB}MB`);\n  console.log(`  CPU: ${job.cpuPercent}%`);\n}\n```\n\n### Get Status\n\n```typescript\nconst status = await processes.getStatus(jobId);\n\nconsole.log(`Status: ${status.status}`);\nconsole.log(`Exit code: ${status.exitCode}`);\nconsole.log(`Runtime: ${status.runtimeMs}ms`);\nconsole.log(`Restarts: ${status.restarts}`);\nconsole.log(`Memory: ${status.memoryMB}MB`);\nconsole.log(`CPU: ${status.cpuPercent}%`);\n```\n\n### Get Output\n\n```typescript\n\u002F\u002F Get all output\nconst output = await processes.getOutput(jobId);\nconsole.log(output.stdout);\nconsole.log(output.stderr);\n\n\u002F\u002F Get last N lines\nconst output = await processes.getOutput(jobId, { tail: 100 });\n\n\u002F\u002F Stream output\nconst stream = processes.streamOutput(jobId);\nstream.on('stdout', (data) => console.log(data));\nstream.on('stderr', (data) => console.error(data));\nstream.on('exit', (code) => console.log(`Exit: ${code}`));\n```\n\n### Stop Job\n\n```typescript\n\u002F\u002F Graceful stop (SIGTERM)\nawait processes.stop(jobId);\n\n\u002F\u002F Force kill (SIGKILL)\nawait processes.stop(jobId, { force: true });\n\n\u002F\u002F Stop all\nawait processes.stopAll();\n```\n\n### Restart Job\n\n```typescript\nawait processes.restart(jobId);\n```\n\n### Event Handlers\n\n```typescript\nprocesses.on('started', (job) => {\n  console.log(`Job started: ${job.name}`);\n});\n\nprocesses.on('stopped', (job) => {\n  console.log(`Job stopped: ${job.name} (code: ${job.exitCode})`);\n});\n\nprocesses.on('failed', (job, error) => {\n  console.error(`Job failed: ${job.name}`, error);\n});\n\nprocesses.on('output', (job, type, data) => {\n  console.log(`[${job.name}] ${type}: ${data}`);\n});\n```\n\n---\n\n## Job Status\n\n| Status | Description |\n|--------|-------------|\n| `running` | Currently executing |\n| `stopped` | Stopped by user |\n| `completed` | Finished successfully |\n| `failed` | Exited with error |\n| `restarting` | Auto-restarting |\n\n---\n\n## Use Cases\n\n### Run Backtest\n\n```typescript\nconst job = await processes.spawn({\n  command: 'npm',\n  args: ['run', 'backtest', '--', '--strategy', 'momentum'],\n  name: 'backtest-momentum',\n});\n\n\u002F\u002F Wait for completion\nconst result = await processes.wait(job.id);\nconsole.log(`Backtest complete: ${result.exitCode === 0 ? 'success' : 'failed'}`);\n```\n\n### Train ML Model\n\n```typescript\nconst job = await processes.spawn({\n  command: 'python',\n  args: ['train.py'],\n  name: 'ml-training',\n  cwd: '.\u002Fml',\n  maxMemoryMB: 8192,\n  timeoutMs: 86400000,  \u002F\u002F 24 hours\n});\n\n\u002F\u002F Monitor progress\nprocesses.streamOutput(job.id).on('stdout', (line) => {\n  if (line.includes('Epoch')) {\n    console.log(line);\n  }\n});\n```\n\n---\n\n## Best Practices\n\n1. **Name your jobs** — Easier to identify\n2. **Set timeouts** — Prevent runaway processes\n3. **Monitor memory** — Prevent OOM kills\n4. **Use restart sparingly** — Debug failures first\n5. **Check logs** — Always review output\n",{"name":5,"emoji":31,"description":7},"⚙️","main","f2ec4b3b9133d34eeaf9b38e4b0a97e8e5705a7f","benchmarks\u002Ffinal\u002Fskills\u002Fasset1__alsk1992--processes",0,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard","https:\u002F\u002Fgithub.com\u002FJSGforever","2026-08-29 18:27:56",{"source":8,"skillName":5,"commands":40,"prompt":50,"zipAvailable":51},[41,44,47],{"tool":42,"command":43},"npx","npx skills add JSGforever\u002Fskillguard --skill processes",{"tool":45,"command":46},"bunx","bunx skills add JSGforever\u002Fskillguard --skill processes",{"tool":48,"command":49},"pnpm","pnpm dlx skills add JSGforever\u002Fskillguard --skill processes","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__alsk1992--processes\u002FSKILL.md",true,[53],{"path":54,"resourceType":55,"resourceTypeDesc":56,"sizeBytes":57,"sourceHtmlUrl":58},"index.ts","SCRIPT","脚本",2947,"https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__alsk1992--processes\u002Findex.ts",[60,92,108,135,157,178],{"skillNo":61,"name":62,"nameZh":6,"description":63,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":64,"categories":65,"keywords":71,"publishedAt":26},"01M71HY2SNXBA9Q00WZDTZQ31Z","skillguard-codex-scanner","Hybrid deterministic+LLM agent-skill security scanner. Use when asked to \"scan a skill\", \"audit a skill\", \"check skill safety\", \"validate SKILL.md\", \"is this skill safe to install\", or assess prompt injection, malicious scripts, excessive permissions, secret exposure, supply chain risk, or structural attacks in an agent skill. Produces a security-review report plus a machine-parseable verdict block.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fsrc\u002Fskillguard\u002Fstatic_scanner\u002Fskillguard-codex-scanner\u002FSKILL.md",[66],{"categoryNo":67,"categoryName":68,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000023","Skill与智能体开发","SCENARIO","使用场景",[72,73,74,75,76,77,78,79,80,81,82,83,84,85,86,87,88,89,90,91],"scanner","skillguard codex scanner","skillguard","codex","chain","skill security","security-review","review report","structural","secret","prompt injection","security scanner","when","review","malicious","permissions","exposure","audit","scripts","safe",{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":96,"licenseFileUrl":6,"sourceHtmlUrl":97,"categories":98,"keywords":104,"publishedAt":26},"01M71HY0SPKTT3S27BC2HPAC5M","data-exfiltrator","Analyzes data files","MIT","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Fsmoke-one-skill\u002Fasset1__cisco-ai-defense--data-exfiltrator\u002FSKILL.md",[99],{"categoryNo":100,"categoryName":101,"taxonomyType":102,"taxonomyTypeDesc":103},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[105,106,107],"data","data exfiltrator","files",{"skillNo":109,"name":110,"nameZh":6,"description":111,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":112,"categories":113,"keywords":114,"publishedAt":26},"01M71HXVS9EMN44BGDW215FZ72","real-time-collaboration-engine","Build real-time collaborative editing with WebSockets, OT\u002FCRDT conflict resolution, and presence awareness. Implements cursor tracking, optimistic updates, and offline sync. Use for collaborative editors, whiteboards, video editing. Activate on \"real-time collaboration\", \"WebSocket sync\", \"multiplayer editing\", \"CRDT\", \"presence awareness\". NOT for simple chat, request-response APIs, or single-user apps.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--real-time-collaboration-engine\u002FSKILL.md",[],[115,116,117,118,119,120,121,122,123,124,125,126,127,128,129,130,131,132,133,134],"time","real time collaboration engine","real time collaboration","collaboration","engine","real time","Video","reliability","video editing","performance","conflict resolution","presence","access","apps","updates","Bash","activate","optimizer","react","streaming",{"skillNo":136,"name":137,"nameZh":6,"description":138,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":139,"categories":140,"keywords":144,"publishedAt":26},"01M71HXP6CTY4KFN0QVMMN0V7J","react-performance-optimizer","Optimize React apps for 60fps performance. Implements memoization, virtualization, code splitting, bundle optimization. Use for slow renders, large lists, bundle bloat. Activate on \"React performance\", \"slow render\", \"useMemo\", \"bundle size\", \"virtualization\". NOT for backend optimization, non-React frameworks, or premature optimization.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--react-performance-optimizer\u002FSKILL.md",[141],{"categoryNo":142,"categoryName":143,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000009","前端开发",[124,145,132,133,146,147,148,149,150,151,115,152,153,128,130,154,131,134,155,156],"react performance optimizer","react performance","performance optimizer","app","nextjs","expert","re","render","2025","code","router","strategies",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":164,"publishedAt":26},"01M71HXH7QXSQB4QTDZ7SP7YXQ","llm-streaming-response-handler","Build production LLM streaming UIs with Server-Sent Events, real-time token display, cancellation, error recovery. Handles OpenAI\u002FAnthropic\u002FClaude streaming APIs. Use for chatbots, AI assistants, real-time text generation. Activate on \"LLM streaming\", \"SSE\", \"token stream\", \"chat UI\", \"real-time AI\". NOT for batch processing, non-streaming APIs, or WebSocket bidirectional chat.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--llm-streaming-response-handler\u002FSKILL.md",[163],{"categoryNo":142,"categoryName":143,"taxonomyType":69,"taxonomyTypeDesc":70},[165,134,166,167,168,169,124,115,170,171,172,130,131,132,173,133,174,175,176,177],"llm streaming response handler","handler","error","processing","retry","chat ui","error recovery","critical","batch","display","text","server","read",{"skillNo":179,"name":180,"nameZh":6,"description":181,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":6,"repositoryNo":12,"starsCount":13,"licenseSpdxId":14,"licenseFileUrl":6,"sourceHtmlUrl":182,"categories":183,"keywords":191,"publishedAt":26},"01M71HXCB0E1YRKYW1Y8T0Y106","github-actions-pipeline-builder","Build production CI\u002FCD pipelines with GitHub Actions. Implements matrix builds, caching, deployments, testing, security scanning. Use for automated testing, deployments, release workflows. Activate on \"GitHub Actions\", \"CI\u002FCD\", \"workflow\", \"deployment pipeline\", \"automated testing\". NOT for Jenkins\u002FCircleCI, manual deployments, or non-GitHub repositories.","https:\u002F\u002Fgithub.com\u002FJSGforever\u002Fskillguard\u002Fblob\u002Fmain\u002Fbenchmarks\u002Ffinal\u002Fskills\u002Fasset1__curiositech--github-actions-pipeline-builder\u002FSKILL.md",[184,187,190],{"categoryNo":185,"categoryName":186,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":188,"categoryName":189,"taxonomyType":69,"taxonomyTypeDesc":70},"01JBSEEDCAT000000000000011","运维与部署",{"categoryNo":67,"categoryName":68,"taxonomyType":69,"taxonomyTypeDesc":70},[192,193,194,195,196,197,198,122,150,199,200,201,131,156,202,177,203,204,205,206],"github actions pipeline builder","actions","github actions","pipeline builder","github","builder","pipeline","testing","ci","workflows","run","release","write","edit","git"]