[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6F7VP3D8Z7ZVEQ5XDFMP9HB":3,"skill-same:01M6F7VP3D8Z7ZVEQ5XDFMP9HB":73},{"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":18,"publishedAt":41,"linkOnly":42,"markdownContent":43,"markdownBody":44,"frontMatter":45,"refName":50,"commitSha":51,"skillDirectory":52,"forksCount":53,"repositoryHtmlUrl":54,"repositoryHomepageUrl":6,"ownerHtmlUrl":55,"ownerBlogUrl":56,"ownerDescription":57,"updatedAt":58,"install":59,"resources":72},"01M6F7VP3D8Z7ZVEQ5XDFMP9HB","lindy-reference-architecture",null,"Reference architectures for Lindy AI integrations.\nUse when designing systems, planning architecture,\nor implementing production patterns.\nTrigger with phrases like \"lindy architecture\", \"lindy design\",\n\"lindy system design\", \"lindy patterns\".","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\u002Flindy-pack\u002Fskills\u002Flindy-reference-architecture\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"architecture","lindy reference architecture","reference","patterns","when","for","implementing","design","with","architectures","trigger","io","systems","Production","planning","system design","use","edit","write","read","integrations","system","2026-11-10 10:12:30",false,"---\nname: lindy-reference-architecture\ndescription: |\n  Reference architectures for Lindy AI integrations.\n  Use when designing systems, planning architecture,\n  or implementing production patterns.\n  Trigger with phrases like \"lindy architecture\", \"lindy design\",\n  \"lindy system design\", \"lindy patterns\".\nallowed-tools: Read, Write, Edit\nversion: 1.0.0\nlicense: MIT\nauthor: Jeremy Longshore \u003Cjeremy@intentsolutions.io>\n---\n\n# Lindy Reference Architecture\n\n## Overview\nProduction-ready reference architectures for Lindy AI integrations.\n\n## Prerequisites\n- Understanding of system design principles\n- Familiarity with cloud services\n- Production requirements defined\n\n## Architecture Patterns\n\n### Pattern 1: Basic Integration\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│   Client    │────▶│   Backend   │────▶│   Lindy AI  │\n│   (React)   │◀────│   (Node.js) │◀────│   API       │\n└─────────────┘     └─────────────┘     └─────────────┘\n```\n\n```typescript\n\u002F\u002F Simple backend integration\nimport express from 'express';\nimport { Lindy } from '@lindy-ai\u002Fsdk';\n\nconst app = express();\nconst lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });\n\napp.post('\u002Fapi\u002Fchat', async (req, res) => {\n  const { message, agentId } = req.body;\n  const result = await lindy.agents.run(agentId, { input: message });\n  res.json({ response: result.output });\n});\n```\n\n### Pattern 2: Event-Driven Architecture\n```\n┌──────────────────────────────────────────────────────────┐\n│                     Event Bus (Redis\u002FSQS)                │\n└────┬─────────────────┬─────────────────┬────────────────┘\n     │                 │                 │\n     ▼                 ▼                 ▼\n┌─────────┐      ┌─────────┐      ┌─────────┐\n│ Worker  │      │ Worker  │      │ Worker  │\n│ (Agent) │      │ (Agent) │      │ (Agent) │\n└────┬────┘      └────┬────┘      └────┬────┘\n     │                │                │\n     └────────────────┼────────────────┘\n                      ▼\n              ┌─────────────┐\n              │  Lindy AI   │\n              │    API      │\n              └─────────────┘\n```\n\n```typescript\n\u002F\u002F Event-driven worker\nimport { Queue } from 'bullmq';\nimport { Lindy } from '@lindy-ai\u002Fsdk';\n\nconst lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });\nconst queue = new Queue('lindy-tasks');\n\n\u002F\u002F Producer\nasync function enqueueTask(agentId: string, input: string) {\n  await queue.add('run-agent', { agentId, input });\n}\n\n\u002F\u002F Consumer\nconst worker = new Worker('lindy-tasks', async (job) => {\n  const { agentId, input } = job.data;\n  const result = await lindy.agents.run(agentId, { input });\n\n  \u002F\u002F Emit result event\n  await eventBus.publish('agent.completed', {\n    jobId: job.id,\n    result: result.output,\n  });\n});\n```\n\n### Pattern 3: Multi-Agent Orchestration\n```\n                    ┌─────────────────┐\n                    │   Orchestrator  │\n                    │     Agent       │\n                    └────────┬────────┘\n                             │\n           ┌─────────────────┼─────────────────┐\n           │                 │                 │\n           ▼                 ▼                 ▼\n    ┌─────────────┐   ┌─────────────┐   ┌─────────────┐\n    │  Research   │   │  Analysis   │   │  Writing    │\n    │   Agent     │   │   Agent     │   │   Agent     │\n    └─────────────┘   └─────────────┘   └─────────────┘\n```\n\n```typescript\n\u002F\u002F Multi-agent orchestrator\nclass AgentOrchestrator {\n  private lindy: Lindy;\n  private agents: Record\u003Cstring, string> = {\n    research: 'agt_research',\n    analysis: 'agt_analysis',\n    writing: 'agt_writing',\n    orchestrator: 'agt_orchestrator',\n  };\n\n  async execute(task: string): Promise\u003Cstring> {\n    \u002F\u002F Step 1: Orchestrator plans the work\n    const plan = await this.lindy.agents.run(this.agents.orchestrator, {\n      input: `Plan steps for: ${task}`,\n    });\n\n    \u002F\u002F Step 2: Execute each step\n    const steps = JSON.parse(plan.output);\n    const results: string[] = [];\n\n    for (const step of steps) {\n      const result = await this.lindy.agents.run(\n        this.agents[step.agent],\n        { input: step.task }\n      );\n      results.push(result.output);\n    }\n\n    \u002F\u002F Step 3: Synthesize results\n    const synthesis = await this.lindy.agents.run(this.agents.orchestrator, {\n      input: `Synthesize: ${results.join('\\n')}`,\n    });\n\n    return synthesis.output;\n  }\n}\n```\n\n### Pattern 4: High-Availability Setup\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│   Load      │────▶│   App       │────▶│   Lindy     │\n│   Balancer  │     │   Server 1  │     │   Primary   │\n└─────────────┘     └─────────────┘     └──────┬──────┘\n                                               │\n                    ┌─────────────┐     ┌──────▼──────┐\n                    │   App       │────▶│   Lindy     │\n                    │   Server 2  │     │   Fallback  │\n                    └─────────────┘     └─────────────┘\n                                               │\n┌─────────────┐     ┌─────────────┐            │\n│   Cache     │◀────│   Shared    │◀───────────┘\n│   (Redis)   │     │   State     │\n└─────────────┘     └─────────────┘\n```\n\n```typescript\n\u002F\u002F HA client with failover\nclass HALindyClient {\n  private primary: Lindy;\n  private fallback: Lindy;\n  private cache: Redis;\n\n  async run(agentId: string, input: string) {\n    \u002F\u002F Check cache first\n    const cached = await this.cache.get(`${agentId}:${input}`);\n    if (cached) return JSON.parse(cached);\n\n    try {\n      \u002F\u002F Try primary\n      const result = await this.primary.agents.run(agentId, { input });\n      await this.cache.setex(`${agentId}:${input}`, 300, JSON.stringify(result));\n      return result;\n    } catch (error) {\n      \u002F\u002F Fallback\n      console.warn('Primary failed, using fallback');\n      return this.fallback.agents.run(agentId, { input });\n    }\n  }\n}\n```\n\n## Output\n- Architecture diagrams\n- Implementation patterns\n- HA\u002Ffailover strategies\n- Multi-agent orchestration\n\n## Error Handling\n| Pattern | Failure Mode | Recovery |\n|---------|--------------|----------|\n| Basic | API error | Retry with backoff |\n| Event-driven | Worker crash | Queue retry |\n| Multi-agent | Step failure | Skip or fallback |\n| HA | Primary down | Automatic failover |\n\n## Resources\n- [Lindy Architecture Guide](https:\u002F\u002Fdocs.lindy.ai\u002Farchitecture)\n- [Best Practices](https:\u002F\u002Fdocs.lindy.ai\u002Fbest-practices)\n- [Case Studies](https:\u002F\u002Flindy.ai\u002Fcase-studies)\n\n## Next Steps\nProceed to Flagship tier skills for enterprise features.\n","# Lindy Reference Architecture\n\n## Overview\nProduction-ready reference architectures for Lindy AI integrations.\n\n## Prerequisites\n- Understanding of system design principles\n- Familiarity with cloud services\n- Production requirements defined\n\n## Architecture Patterns\n\n### Pattern 1: Basic Integration\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│   Client    │────▶│   Backend   │────▶│   Lindy AI  │\n│   (React)   │◀────│   (Node.js) │◀────│   API       │\n└─────────────┘     └─────────────┘     └─────────────┘\n```\n\n```typescript\n\u002F\u002F Simple backend integration\nimport express from 'express';\nimport { Lindy } from '@lindy-ai\u002Fsdk';\n\nconst app = express();\nconst lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });\n\napp.post('\u002Fapi\u002Fchat', async (req, res) => {\n  const { message, agentId } = req.body;\n  const result = await lindy.agents.run(agentId, { input: message });\n  res.json({ response: result.output });\n});\n```\n\n### Pattern 2: Event-Driven Architecture\n```\n┌──────────────────────────────────────────────────────────┐\n│                     Event Bus (Redis\u002FSQS)                │\n└────┬─────────────────┬─────────────────┬────────────────┘\n     │                 │                 │\n     ▼                 ▼                 ▼\n┌─────────┐      ┌─────────┐      ┌─────────┐\n│ Worker  │      │ Worker  │      │ Worker  │\n│ (Agent) │      │ (Agent) │      │ (Agent) │\n└────┬────┘      └────┬────┘      └────┬────┘\n     │                │                │\n     └────────────────┼────────────────┘\n                      ▼\n              ┌─────────────┐\n              │  Lindy AI   │\n              │    API      │\n              └─────────────┘\n```\n\n```typescript\n\u002F\u002F Event-driven worker\nimport { Queue } from 'bullmq';\nimport { Lindy } from '@lindy-ai\u002Fsdk';\n\nconst lindy = new Lindy({ apiKey: process.env.LINDY_API_KEY });\nconst queue = new Queue('lindy-tasks');\n\n\u002F\u002F Producer\nasync function enqueueTask(agentId: string, input: string) {\n  await queue.add('run-agent', { agentId, input });\n}\n\n\u002F\u002F Consumer\nconst worker = new Worker('lindy-tasks', async (job) => {\n  const { agentId, input } = job.data;\n  const result = await lindy.agents.run(agentId, { input });\n\n  \u002F\u002F Emit result event\n  await eventBus.publish('agent.completed', {\n    jobId: job.id,\n    result: result.output,\n  });\n});\n```\n\n### Pattern 3: Multi-Agent Orchestration\n```\n                    ┌─────────────────┐\n                    │   Orchestrator  │\n                    │     Agent       │\n                    └────────┬────────┘\n                             │\n           ┌─────────────────┼─────────────────┐\n           │                 │                 │\n           ▼                 ▼                 ▼\n    ┌─────────────┐   ┌─────────────┐   ┌─────────────┐\n    │  Research   │   │  Analysis   │   │  Writing    │\n    │   Agent     │   │   Agent     │   │   Agent     │\n    └─────────────┘   └─────────────┘   └─────────────┘\n```\n\n```typescript\n\u002F\u002F Multi-agent orchestrator\nclass AgentOrchestrator {\n  private lindy: Lindy;\n  private agents: Record\u003Cstring, string> = {\n    research: 'agt_research',\n    analysis: 'agt_analysis',\n    writing: 'agt_writing',\n    orchestrator: 'agt_orchestrator',\n  };\n\n  async execute(task: string): Promise\u003Cstring> {\n    \u002F\u002F Step 1: Orchestrator plans the work\n    const plan = await this.lindy.agents.run(this.agents.orchestrator, {\n      input: `Plan steps for: ${task}`,\n    });\n\n    \u002F\u002F Step 2: Execute each step\n    const steps = JSON.parse(plan.output);\n    const results: string[] = [];\n\n    for (const step of steps) {\n      const result = await this.lindy.agents.run(\n        this.agents[step.agent],\n        { input: step.task }\n      );\n      results.push(result.output);\n    }\n\n    \u002F\u002F Step 3: Synthesize results\n    const synthesis = await this.lindy.agents.run(this.agents.orchestrator, {\n      input: `Synthesize: ${results.join('\\n')}`,\n    });\n\n    return synthesis.output;\n  }\n}\n```\n\n### Pattern 4: High-Availability Setup\n```\n┌─────────────┐     ┌─────────────┐     ┌─────────────┐\n│   Load      │────▶│   App       │────▶│   Lindy     │\n│   Balancer  │     │   Server 1  │     │   Primary   │\n└─────────────┘     └─────────────┘     └──────┬──────┘\n                                               │\n                    ┌─────────────┐     ┌──────▼──────┐\n                    │   App       │────▶│   Lindy     │\n                    │   Server 2  │     │   Fallback  │\n                    └─────────────┘     └─────────────┘\n                                               │\n┌─────────────┐     ┌─────────────┐            │\n│   Cache     │◀────│   Shared    │◀───────────┘\n│   (Redis)   │     │   State     │\n└─────────────┘     └─────────────┘\n```\n\n```typescript\n\u002F\u002F HA client with failover\nclass HALindyClient {\n  private primary: Lindy;\n  private fallback: Lindy;\n  private cache: Redis;\n\n  async run(agentId: string, input: string) {\n    \u002F\u002F Check cache first\n    const cached = await this.cache.get(`${agentId}:${input}`);\n    if (cached) return JSON.parse(cached);\n\n    try {\n      \u002F\u002F Try primary\n      const result = await this.primary.agents.run(agentId, { input });\n      await this.cache.setex(`${agentId}:${input}`, 300, JSON.stringify(result));\n      return result;\n    } catch (error) {\n      \u002F\u002F Fallback\n      console.warn('Primary failed, using fallback');\n      return this.fallback.agents.run(agentId, { input });\n    }\n  }\n}\n```\n\n## Output\n- Architecture diagrams\n- Implementation patterns\n- HA\u002Ffailover strategies\n- Multi-agent orchestration\n\n## Error Handling\n| Pattern | Failure Mode | Recovery |\n|---------|--------------|----------|\n| Basic | API error | Retry with backoff |\n| Event-driven | Worker crash | Queue retry |\n| Multi-agent | Step failure | Skip or fallback |\n| HA | Primary down | Automatic failover |\n\n## Resources\n- [Lindy Architecture Guide](https:\u002F\u002Fdocs.lindy.ai\u002Farchitecture)\n- [Best Practices](https:\u002F\u002Fdocs.lindy.ai\u002Fbest-practices)\n- [Case Studies](https:\u002F\u002Flindy.ai\u002Fcase-studies)\n\n## Next Steps\nProceed to Flagship tier skills for enterprise features.\n",{"name":5,"author":46,"license":15,"version":47,"description":48,"allowed-tools":49},"Jeremy Longshore \u003Cjeremy@intentsolutions.io>","1.0.0","Reference architectures for Lindy AI integrations.\nUse when designing systems, planning architecture,\nor implementing production patterns.\nTrigger with phrases like \"lindy architecture\", \"lindy design\",\n\"lindy system design\", \"lindy patterns\".\n","Read, Write, 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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",[],[145,146,147,148,149,150,151,152,35,153,154,155,156,157,158,159,27,160,161,162,24,23],"analysis","neuropixels analysis","spike","metrics","data","open","quality","user","recordings","Neural","motion","visual","quality metrics","unit","sorting","curation","recording","load",{"skillNo":164,"name":165,"nameZh":6,"description":166,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":78,"licenseFileUrl":167,"sourceHtmlUrl":168,"categories":169,"keywords":173,"publishedAt":41},"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",[170],{"categoryNo":171,"categoryName":172,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000023","Skill与智能体开发",[174,175,176,177,178,179,180,181,39,182,183,184,185,186,27,24,187,23,188],"skill creator","creator","workflows","create","update","capabilities","knowledge","tool","specialized","guide","new skill","existing skill","users","Existing","new",{"skillNo":190,"name":191,"nameZh":6,"description":192,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":193,"sourceHtmlUrl":194,"categories":195,"keywords":197,"publishedAt":41},"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",[196],{"categoryNo":171,"categoryName":172,"taxonomyType":85,"taxonomyTypeDesc":86},[191,198,199,200,201,202,203,132,204,205,35,206,207,208,209,24,210],"google","browser automation","gemini","automation","auth","code","library","management","only","document","query","Citation","source",{"skillNo":212,"name":213,"nameZh":6,"description":214,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":78,"licenseFileUrl":215,"sourceHtmlUrl":216,"categories":217,"keywords":224,"publishedAt":41},"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",[218,221],{"categoryNo":219,"categoryName":220,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000005","邮件与沟通",{"categoryNo":222,"categoryName":223,"taxonomyType":85,"taxonomyTypeDesc":86},"01JBSEEDCAT000000000000016","图像与多媒体",[225,226,227,175,228,104,229,230,180,35,231,186,232,233,234,24,235,23],"slack gif creator","slack","gif","validation","constraints","Animation","me","make","Utilities","concepts","request"]