[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6F7WS6M14CSW22434BRMCKY":3,"skill-same:01M6F7WS6M14CSW22434BRMCKY":79},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":23,"publishedAt":47,"linkOnly":48,"markdownContent":49,"markdownBody":50,"frontMatter":51,"refName":56,"commitSha":57,"skillDirectory":58,"forksCount":59,"repositoryHtmlUrl":60,"repositoryHomepageUrl":6,"ownerHtmlUrl":61,"ownerBlogUrl":62,"ownerDescription":63,"updatedAt":64,"install":65,"resources":78},"01M6F7WS6M14CSW22434BRMCKY","linear-cost-tuning",null,"Optimize Linear API usage and manage costs effectively.\nUse when reducing API calls, managing rate limits efficiently,\nor optimizing integration costs.\nTrigger with phrases like \"linear cost\", \"reduce linear API calls\",\n\"linear efficiency\", \"linear API usage\", \"optimize linear costs\".","Dicklesworthstone\u002Fpi_agent_rust","Dicklesworthstone","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F35050222?v=4","01M6CG26AR942CSVMN1M5E3DSE","Jeff Emanuel","01M6CG26EPP71PSHW1VDS71121",1991,"MIT","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Flinear-pack\u002Fskills\u002Flinear-cost-tuning\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000030","开发工程师","PROFESSION","适用职业",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43,44,45,46],"tuning","linear cost tuning","cost","linear","optimize","when","limits","rate","reduce","usage","calls","with","trigger","io","efficiency","manage","use","edit","write","read","grep","api","integration","2026-11-10 10:12:30",false,"---\nname: linear-cost-tuning\ndescription: |\n  Optimize Linear API usage and manage costs effectively.\n  Use when reducing API calls, managing rate limits efficiently,\n  or optimizing integration costs.\n  Trigger with phrases like \"linear cost\", \"reduce linear API calls\",\n  \"linear efficiency\", \"linear API usage\", \"optimize linear costs\".\nallowed-tools: Read, Write, Edit, Grep\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\n---\n\n# Linear Cost Tuning\n\n## Overview\nOptimize Linear API usage to maximize efficiency and minimize costs.\n\n## Prerequisites\n- Working Linear integration\n- Monitoring in place\n- Understanding of usage patterns\n\n## Cost Factors\n\n### API Request Costs\n| Factor | Impact | Optimization Strategy |\n|--------|--------|----------------------|\n| Request count | Direct rate limit | Batch operations |\n| Query complexity | Complexity limit | Minimal field selection |\n| Payload size | Bandwidth\u002Flatency | Pagination, filtering |\n| Webhook volume | Processing costs | Event filtering |\n\n## Instructions\n\n### Step 1: Audit Current Usage\n```typescript\n\u002F\u002F lib\u002Fusage-tracker.ts\ninterface UsageStats {\n  requests: number;\n  complexity: number;\n  bytesTransferred: number;\n  period: { start: Date; end: Date };\n}\n\nclass UsageTracker {\n  private stats: UsageStats = {\n    requests: 0,\n    complexity: 0,\n    bytesTransferred: 0,\n    period: { start: new Date(), end: new Date() },\n  };\n\n  recordRequest(complexity: number, bytes: number): void {\n    this.stats.requests++;\n    this.stats.complexity += complexity;\n    this.stats.bytesTransferred += bytes;\n    this.stats.period.end = new Date();\n  }\n\n  getStats(): UsageStats {\n    return { ...this.stats };\n  }\n\n  getDaily(): {\n    avgRequestsPerHour: number;\n    avgComplexityPerRequest: number;\n    projectedMonthlyRequests: number;\n  } {\n    const hours =\n      (this.stats.period.end.getTime() - this.stats.period.start.getTime()) \u002F\n      (1000 * 60 * 60);\n\n    return {\n      avgRequestsPerHour: this.stats.requests \u002F Math.max(hours, 1),\n      avgComplexityPerRequest: this.stats.complexity \u002F Math.max(this.stats.requests, 1),\n      projectedMonthlyRequests: (this.stats.requests \u002F Math.max(hours, 1)) * 24 * 30,\n    };\n  }\n\n  reset(): void {\n    this.stats = {\n      requests: 0,\n      complexity: 0,\n      bytesTransferred: 0,\n      period: { start: new Date(), end: new Date() },\n    };\n  }\n}\n\nexport const usageTracker = new UsageTracker();\n```\n\n### Step 2: Reduce Request Volume\n\n**Polling vs Webhooks:**\n```typescript\n\u002F\u002F BAD: Polling every minute\nsetInterval(async () => {\n  const issues = await client.issues({ first: 100 });\n  await syncIssues(issues.nodes);\n}, 60000);\n\n\u002F\u002F GOOD: Use webhooks for real-time updates\n\u002F\u002F See linear-webhooks-events skill\napp.post(\"\u002Fwebhooks\u002Flinear\", async (req, res) => {\n  const event = req.body;\n  await handleEvent(event);\n  res.sendStatus(200);\n});\n```\n\n**Conditional Fetching:**\n```typescript\n\u002F\u002F lib\u002Fconditional-fetch.ts\ninterface ETagCache {\n  data: any;\n  etag: string;\n  timestamp: Date;\n}\n\nconst etagCache = new Map\u003Cstring, ETagCache>();\n\nasync function fetchWithETag(key: string, fetcher: () => Promise\u003Cany>) {\n  const cached = etagCache.get(key);\n\n  \u002F\u002F Only fetch if cache is stale (> 5 minutes)\n  if (cached && Date.now() - cached.timestamp.getTime() \u003C 5 * 60 * 1000) {\n    return cached.data;\n  }\n\n  const data = await fetcher();\n  etagCache.set(key, {\n    data,\n    etag: JSON.stringify(data).slice(0, 50), \u002F\u002F Simple hash\n    timestamp: new Date(),\n  });\n\n  return data;\n}\n```\n\n### Step 3: Optimize Query Complexity\n\n**Calculate Complexity:**\n```typescript\n\u002F\u002F Linear complexity estimation\n\u002F\u002F - Each field costs 1\n\u002F\u002F - Each connection costs 1 + (first * child_complexity)\n\u002F\u002F - Nested connections multiply\n\n\u002F\u002F BAD: High complexity query (~500 complexity)\nconst expensiveQuery = `\n  query {\n    issues(first: 50) {\n      nodes {\n        id\n        title\n        assignee { name }\n        labels { nodes { name } }\n        comments(first: 10) {\n          nodes { body user { name } }\n        }\n      }\n    }\n  }\n`;\n\n\u002F\u002F GOOD: Low complexity query (~100 complexity)\nconst cheapQuery = `\n  query {\n    issues(first: 50) {\n      nodes {\n        id\n        identifier\n        title\n        priority\n      }\n    }\n  }\n`;\n```\n\n### Step 4: Implement Request Coalescing\n```typescript\n\u002F\u002F lib\u002Fcoalesce.ts\nclass RequestCoalescer {\n  private pending = new Map\u003Cstring, Promise\u003Cany>>();\n\n  async execute\u003CT>(key: string, fn: () => Promise\u003CT>): Promise\u003CT> {\n    \u002F\u002F If same request is already in flight, reuse it\n    const existing = this.pending.get(key);\n    if (existing) {\n      return existing;\n    }\n\n    const promise = fn().finally(() => {\n      this.pending.delete(key);\n    });\n\n    this.pending.set(key, promise);\n    return promise;\n  }\n}\n\nconst coalescer = new RequestCoalescer();\n\n\u002F\u002F Multiple simultaneous calls reuse the same request\nconst [teams1, teams2, teams3] = await Promise.all([\n  coalescer.execute(\"teams\", () => client.teams()),\n  coalescer.execute(\"teams\", () => client.teams()), \u002F\u002F Reuses first request\n  coalescer.execute(\"teams\", () => client.teams()), \u002F\u002F Reuses first request\n]);\n```\n\n### Step 5: Webhook Event Filtering\n```typescript\n\u002F\u002F Only process relevant events\nasync function shouldProcessEvent(event: any): boolean {\n  \u002F\u002F Skip events from bots\n  if (event.data?.actor?.isBot) return false;\n\n  \u002F\u002F Only process certain issue states\n  if (event.type === \"Issue\" && event.action === \"update\") {\n    const importantFields = [\"state\", \"priority\", \"assignee\"];\n    const changedFields = Object.keys(event.updatedFrom || {});\n\n    if (!changedFields.some(f => importantFields.includes(f))) {\n      return false; \u002F\u002F Skip trivial updates\n    }\n  }\n\n  \u002F\u002F Only process issues from specific teams\n  const allowedTeams = [\"ENG\", \"PROD\"];\n  if (event.data?.team?.key && !allowedTeams.includes(event.data.team.key)) {\n    return false;\n  }\n\n  return true;\n}\n```\n\n### Step 6: Lazy Loading Pattern\n```typescript\n\u002F\u002F lib\u002Flazy-client.ts\nclass LazyLinearClient {\n  private client: LinearClient;\n  private teamsCache: any[] | null = null;\n  private statesCache = new Map\u003Cstring, any[]>();\n\n  constructor(apiKey: string) {\n    this.client = new LinearClient({ apiKey });\n  }\n\n  async getTeams() {\n    if (!this.teamsCache) {\n      const teams = await this.client.teams();\n      this.teamsCache = teams.nodes;\n    }\n    return this.teamsCache;\n  }\n\n  async getStatesForTeam(teamKey: string) {\n    if (!this.statesCache.has(teamKey)) {\n      const teams = await this.client.teams({\n        filter: { key: { eq: teamKey } },\n      });\n      const states = await teams.nodes[0].states();\n      this.statesCache.set(teamKey, states.nodes);\n    }\n    return this.statesCache.get(teamKey)!;\n  }\n\n  \u002F\u002F Invalidate on known changes\n  invalidateTeams() {\n    this.teamsCache = null;\n    this.statesCache.clear();\n  }\n}\n```\n\n## Cost Reduction Checklist\n- [ ] Replace polling with webhooks\n- [ ] Implement request caching\n- [ ] Use request coalescing\n- [ ] Filter webhook events\n- [ ] Minimize query complexity\n- [ ] Batch related operations\n- [ ] Use lazy loading for static data\n- [ ] Monitor and track usage\n\n## Monitoring Dashboard\n```typescript\n\u002F\u002F Example metrics to track\nconst metrics = {\n  \u002F\u002F Request metrics\n  totalRequests: counter(\"linear_requests_total\"),\n  requestDuration: histogram(\"linear_request_duration_seconds\"),\n  complexityCost: histogram(\"linear_complexity_cost\"),\n\n  \u002F\u002F Cache metrics\n  cacheHits: counter(\"linear_cache_hits_total\"),\n  cacheMisses: counter(\"linear_cache_misses_total\"),\n\n  \u002F\u002F Webhook metrics\n  webhooksReceived: counter(\"linear_webhooks_received_total\"),\n  webhooksFiltered: counter(\"linear_webhooks_filtered_total\"),\n};\n```\n\n## Resources\n- [Linear Rate Limiting](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Frate-limiting)\n- [Query Complexity Guide](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Fcomplexity)\n- [Webhook Best Practices](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Fwebhooks)\n\n## Next Steps\nLearn production architecture with `linear-reference-architecture`.\n","# Linear Cost Tuning\n\n## Overview\nOptimize Linear API usage to maximize efficiency and minimize costs.\n\n## Prerequisites\n- Working Linear integration\n- Monitoring in place\n- Understanding of usage patterns\n\n## Cost Factors\n\n### API Request Costs\n| Factor | Impact | Optimization Strategy |\n|--------|--------|----------------------|\n| Request count | Direct rate limit | Batch operations |\n| Query complexity | Complexity limit | Minimal field selection |\n| Payload size | Bandwidth\u002Flatency | Pagination, filtering |\n| Webhook volume | Processing costs | Event filtering |\n\n## Instructions\n\n### Step 1: Audit Current Usage\n```typescript\n\u002F\u002F lib\u002Fusage-tracker.ts\ninterface UsageStats {\n  requests: number;\n  complexity: number;\n  bytesTransferred: number;\n  period: { start: Date; end: Date };\n}\n\nclass UsageTracker {\n  private stats: UsageStats = {\n    requests: 0,\n    complexity: 0,\n    bytesTransferred: 0,\n    period: { start: new Date(), end: new Date() },\n  };\n\n  recordRequest(complexity: number, bytes: number): void {\n    this.stats.requests++;\n    this.stats.complexity += complexity;\n    this.stats.bytesTransferred += bytes;\n    this.stats.period.end = new Date();\n  }\n\n  getStats(): UsageStats {\n    return { ...this.stats };\n  }\n\n  getDaily(): {\n    avgRequestsPerHour: number;\n    avgComplexityPerRequest: number;\n    projectedMonthlyRequests: number;\n  } {\n    const hours =\n      (this.stats.period.end.getTime() - this.stats.period.start.getTime()) \u002F\n      (1000 * 60 * 60);\n\n    return {\n      avgRequestsPerHour: this.stats.requests \u002F Math.max(hours, 1),\n      avgComplexityPerRequest: this.stats.complexity \u002F Math.max(this.stats.requests, 1),\n      projectedMonthlyRequests: (this.stats.requests \u002F Math.max(hours, 1)) * 24 * 30,\n    };\n  }\n\n  reset(): void {\n    this.stats = {\n      requests: 0,\n      complexity: 0,\n      bytesTransferred: 0,\n      period: { start: new Date(), end: new Date() },\n    };\n  }\n}\n\nexport const usageTracker = new UsageTracker();\n```\n\n### Step 2: Reduce Request Volume\n\n**Polling vs Webhooks:**\n```typescript\n\u002F\u002F BAD: Polling every minute\nsetInterval(async () => {\n  const issues = await client.issues({ first: 100 });\n  await syncIssues(issues.nodes);\n}, 60000);\n\n\u002F\u002F GOOD: Use webhooks for real-time updates\n\u002F\u002F See linear-webhooks-events skill\napp.post(\"\u002Fwebhooks\u002Flinear\", async (req, res) => {\n  const event = req.body;\n  await handleEvent(event);\n  res.sendStatus(200);\n});\n```\n\n**Conditional Fetching:**\n```typescript\n\u002F\u002F lib\u002Fconditional-fetch.ts\ninterface ETagCache {\n  data: any;\n  etag: string;\n  timestamp: Date;\n}\n\nconst etagCache = new Map\u003Cstring, ETagCache>();\n\nasync function fetchWithETag(key: string, fetcher: () => Promise\u003Cany>) {\n  const cached = etagCache.get(key);\n\n  \u002F\u002F Only fetch if cache is stale (> 5 minutes)\n  if (cached && Date.now() - cached.timestamp.getTime() \u003C 5 * 60 * 1000) {\n    return cached.data;\n  }\n\n  const data = await fetcher();\n  etagCache.set(key, {\n    data,\n    etag: JSON.stringify(data).slice(0, 50), \u002F\u002F Simple hash\n    timestamp: new Date(),\n  });\n\n  return data;\n}\n```\n\n### Step 3: Optimize Query Complexity\n\n**Calculate Complexity:**\n```typescript\n\u002F\u002F Linear complexity estimation\n\u002F\u002F - Each field costs 1\n\u002F\u002F - Each connection costs 1 + (first * child_complexity)\n\u002F\u002F - Nested connections multiply\n\n\u002F\u002F BAD: High complexity query (~500 complexity)\nconst expensiveQuery = `\n  query {\n    issues(first: 50) {\n      nodes {\n        id\n        title\n        assignee { name }\n        labels { nodes { name } }\n        comments(first: 10) {\n          nodes { body user { name } }\n        }\n      }\n    }\n  }\n`;\n\n\u002F\u002F GOOD: Low complexity query (~100 complexity)\nconst cheapQuery = `\n  query {\n    issues(first: 50) {\n      nodes {\n        id\n        identifier\n        title\n        priority\n      }\n    }\n  }\n`;\n```\n\n### Step 4: Implement Request Coalescing\n```typescript\n\u002F\u002F lib\u002Fcoalesce.ts\nclass RequestCoalescer {\n  private pending = new Map\u003Cstring, Promise\u003Cany>>();\n\n  async execute\u003CT>(key: string, fn: () => Promise\u003CT>): Promise\u003CT> {\n    \u002F\u002F If same request is already in flight, reuse it\n    const existing = this.pending.get(key);\n    if (existing) {\n      return existing;\n    }\n\n    const promise = fn().finally(() => {\n      this.pending.delete(key);\n    });\n\n    this.pending.set(key, promise);\n    return promise;\n  }\n}\n\nconst coalescer = new RequestCoalescer();\n\n\u002F\u002F Multiple simultaneous calls reuse the same request\nconst [teams1, teams2, teams3] = await Promise.all([\n  coalescer.execute(\"teams\", () => client.teams()),\n  coalescer.execute(\"teams\", () => client.teams()), \u002F\u002F Reuses first request\n  coalescer.execute(\"teams\", () => client.teams()), \u002F\u002F Reuses first request\n]);\n```\n\n### Step 5: Webhook Event Filtering\n```typescript\n\u002F\u002F Only process relevant events\nasync function shouldProcessEvent(event: any): boolean {\n  \u002F\u002F Skip events from bots\n  if (event.data?.actor?.isBot) return false;\n\n  \u002F\u002F Only process certain issue states\n  if (event.type === \"Issue\" && event.action === \"update\") {\n    const importantFields = [\"state\", \"priority\", \"assignee\"];\n    const changedFields = Object.keys(event.updatedFrom || {});\n\n    if (!changedFields.some(f => importantFields.includes(f))) {\n      return false; \u002F\u002F Skip trivial updates\n    }\n  }\n\n  \u002F\u002F Only process issues from specific teams\n  const allowedTeams = [\"ENG\", \"PROD\"];\n  if (event.data?.team?.key && !allowedTeams.includes(event.data.team.key)) {\n    return false;\n  }\n\n  return true;\n}\n```\n\n### Step 6: Lazy Loading Pattern\n```typescript\n\u002F\u002F lib\u002Flazy-client.ts\nclass LazyLinearClient {\n  private client: LinearClient;\n  private teamsCache: any[] | null = null;\n  private statesCache = new Map\u003Cstring, any[]>();\n\n  constructor(apiKey: string) {\n    this.client = new LinearClient({ apiKey });\n  }\n\n  async getTeams() {\n    if (!this.teamsCache) {\n      const teams = await this.client.teams();\n      this.teamsCache = teams.nodes;\n    }\n    return this.teamsCache;\n  }\n\n  async getStatesForTeam(teamKey: string) {\n    if (!this.statesCache.has(teamKey)) {\n      const teams = await this.client.teams({\n        filter: { key: { eq: teamKey } },\n      });\n      const states = await teams.nodes[0].states();\n      this.statesCache.set(teamKey, states.nodes);\n    }\n    return this.statesCache.get(teamKey)!;\n  }\n\n  \u002F\u002F Invalidate on known changes\n  invalidateTeams() {\n    this.teamsCache = null;\n    this.statesCache.clear();\n  }\n}\n```\n\n## Cost Reduction Checklist\n- [ ] Replace polling with webhooks\n- [ ] Implement request caching\n- [ ] Use request coalescing\n- [ ] Filter webhook events\n- [ ] Minimize query complexity\n- [ ] Batch related operations\n- [ ] Use lazy loading for static data\n- [ ] Monitor and track usage\n\n## Monitoring Dashboard\n```typescript\n\u002F\u002F Example metrics to track\nconst metrics = {\n  \u002F\u002F Request metrics\n  totalRequests: counter(\"linear_requests_total\"),\n  requestDuration: histogram(\"linear_request_duration_seconds\"),\n  complexityCost: histogram(\"linear_complexity_cost\"),\n\n  \u002F\u002F Cache metrics\n  cacheHits: counter(\"linear_cache_hits_total\"),\n  cacheMisses: counter(\"linear_cache_misses_total\"),\n\n  \u002F\u002F Webhook metrics\n  webhooksReceived: counter(\"linear_webhooks_received_total\"),\n  webhooksFiltered: counter(\"linear_webhooks_filtered_total\"),\n};\n```\n\n## Resources\n- [Linear Rate Limiting](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Frate-limiting)\n- [Query Complexity Guide](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Fcomplexity)\n- [Webhook Best Practices](https:\u002F\u002Fdevelopers.linear.app\u002Fdocs\u002Fgraphql\u002Fwebhooks)\n\n## Next Steps\nLearn production architecture with `linear-reference-architecture`.\n",{"name":5,"author":52,"license":15,"version":53,"description":54,"allowed-tools":55},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Optimize Linear API usage and manage costs effectively.\nUse when reducing API calls, managing rate limits efficiently,\nor optimizing integration costs.\nTrigger with phrases like \"linear cost\", \"reduce linear API calls\",\n\"linear efficiency\", \"linear API usage\", \"optimize linear costs\".\n","Read, Write, Edit, Grep","main","90b50ed0778745a80fd5bfb13b1843d45b9e82f7","tests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Flinear-pack\u002Fskills\u002Flinear-cost-tuning",234,"https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust","https:\u002F\u002Fgithub.com\u002FDicklesworthstone","https:\u002F\u002Fwww.jeffreyemanuel.com\u002F","Building in NY","2026-11-13 11:50:27",{"source":8,"skillName":5,"commands":66,"prompt":76,"zipAvailable":77},[67,70,73],{"tool":68,"command":69},"npx","npx skills add Dicklesworthstone\u002Fpi_agent_rust --skill linear-cost-tuning",{"tool":71,"command":72},"bunx","bunx skills add Dicklesworthstone\u002Fpi_agent_rust --skill linear-cost-tuning",{"tool":74,"command":75},"pnpm","pnpm dlx skills add Dicklesworthstone\u002Fpi_agent_rust --skill linear-cost-tuning","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Fplugins-community\u002Fplugins\u002Fsaas-packs\u002Flinear-pack\u002Fskills\u002Flinear-cost-tuning\u002FSKILL.md",true,[],[80,120,144,170,197,219],{"skillNo":81,"name":82,"nameZh":6,"description":83,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":85,"sourceHtmlUrl":86,"categories":87,"keywords":93,"publishedAt":47},"01M6FEGPPK0ZTKCCM0R3E3KS33","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[88],{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000009","前端开发","SCENARIO","使用场景",[94,95,96,97,98,99,100,101,102,103,104,105,106,107,108,109,110,111,40,112,113,114,115,116,117,118,119],"web artifacts builder","web","artifacts","artifacts builder","builder","frontend","css","components","react","component","routing","state management","state","shadcn","file","ui","Tools","Tailwind","html","single-file","simple","ui components","multi","for","jsx","suite",{"skillNo":121,"name":122,"nameZh":6,"description":123,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":124,"sourceHtmlUrl":125,"categories":126,"keywords":131,"publishedAt":47},"01M6FEE9VTK1W4GY21AKREJXRG","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fsecurity\u002Fwebapp-testing\u002FSKILL.md",[127,130],{"categoryNo":128,"categoryName":129,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000008","测试与质量",{"categoryNo":89,"categoryName":90,"taxonomyType":91,"taxonomyTypeDesc":92},[132,133,134,99,135,136,95,137,138,139,109,140,141,142,143,35,117],"testing","webapp testing","webapp","screenshots","playwright","debugging","toolkit","browser","logs","applications","behavior","local",{"skillNo":145,"name":146,"nameZh":6,"description":147,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":148,"sourceHtmlUrl":149,"categories":150,"keywords":151,"publishedAt":47},"01M6FE20F7ZTQBFWKF4MPJ2SBX","neuropixels-analysis","Neuropixels neural recording analysis. Load SpikeGLX\u002FOpenEphys data, preprocess, motion correction, Kilosort4 spike sorting, quality metrics, Allen\u002FIBL curation, AI-assisted visual analysis, for Neuropixels 1.0\u002F2.0 extracellular electrophysiology. Use when working with neural recordings, spike sorting, extracellular electrophysiology, or when the user mentions Neuropixels, SpikeGLX, Open Ephys, Kilosort, quality metrics, or unit curation.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fneuropixels-analysis\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Fneuropixels-analysis\u002FSKILL.md",[],[152,153,154,155,156,157,158,159,40,160,161,162,163,164,165,166,35,167,168,169,117,29],"analysis","neuropixels analysis","spike","metrics","data","open","quality","user","recordings","Neural","motion","visual","quality metrics","unit","sorting","curation","recording","load",{"skillNo":171,"name":172,"nameZh":6,"description":173,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":174,"sourceHtmlUrl":175,"categories":176,"keywords":180,"publishedAt":47},"01M6FDP0PDK6F1GGX395C7625Z","skill-creator","Guide for creating effective skills. This skill should be used when users want to create a new skill (or update an existing skill) that extends Claude's capabilities with specialized knowledge, workflows, or tool integrations.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fskill-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fskill-creator\u002FSKILL.md",[177],{"categoryNo":178,"categoryName":179,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000023","Skill与智能体开发",[181,182,183,184,185,186,187,188,189,190,191,192,193,194,35,117,195,29,196],"skill creator","creator","workflows","create","update","capabilities","knowledge","tool","integrations","specialized","guide","new skill","existing skill","users","Existing","new",{"skillNo":198,"name":199,"nameZh":6,"description":200,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":201,"sourceHtmlUrl":202,"categories":203,"keywords":205,"publishedAt":47},"01M6FDM8Y7VK7NYG9SM7QPA3PW","notebooklm","Use this skill to query your Google NotebookLM notebooks directly from Claude Code for source-grounded, citation-backed answers from Gemini. Browser automation, library management, persistent auth. Drastically reduced hallucinations through document-only responses.","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fnotebooklm\u002FLICENSE","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fnotebooklm\u002FSKILL.md",[204],{"categoryNo":178,"categoryName":179,"taxonomyType":91,"taxonomyTypeDesc":92},[199,206,207,208,209,210,211,139,212,213,40,214,215,216,217,117,218],"google","browser automation","gemini","automation","auth","code","library","management","only","document","query","Citation","source",{"skillNo":220,"name":221,"nameZh":6,"description":222,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":84,"licenseFileUrl":223,"sourceHtmlUrl":224,"categories":225,"keywords":232,"publishedAt":47},"01M6FDHPXE10J3XGTCH5HBHS1M","slack-gif-creator","Knowledge and utilities for creating animated GIFs optimized for Slack. Provides constraints, validation tools, and animation concepts. Use when users request animated GIFs for Slack like \"make me a GIF of X doing Y for Slack.\"","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fenterprise-communication\u002Fslack-gif-creator\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002FDicklesworthstone\u002Fpi_agent_rust\u002Fblob\u002Fmain\u002Ftests\u002Fext_conformance\u002Fartifacts\u002Ftemplates-davila7\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fenterprise-communication\u002Fslack-gif-creator\u002FSKILL.md",[226,229],{"categoryNo":227,"categoryName":228,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000005","邮件与沟通",{"categoryNo":230,"categoryName":231,"taxonomyType":91,"taxonomyTypeDesc":92},"01JBSEEDCAT000000000000016","图像与多媒体",[233,234,235,182,236,110,237,238,187,40,239,194,240,241,242,117,243,29],"slack gif creator","slack","gif","validation","constraints","Animation","me","make","Utilities","concepts","request"]