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models.","sapsapshen\u002Fai-memory-router","sapsapshen","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F20347959?v=4","01M6XDQEF1DP50DKF37H81J3J5","shenmian","01M6XDQEJPE41Y3DT2763X8ZJN",0,"MIT","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fcursor\u002Fazure-ai-document-intelligence-ts\u002FSKILL.md",[18],{"categoryNo":19,"categoryName":20,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000002","文档处理","SCENARIO","使用场景",[24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40],"azure ai","azure","azure ai document intelligence ts","document","intelligence","2026","structured data","custom","unknown","tables","structured","community","models","extract","text","data","documents","2026-11-10 10:12:30",false,"---\nname: azure-ai-document-intelligence-ts\ndescription: \"Extract text, tables, and structured data from documents using prebuilt and custom models.\"\nrisk: unknown\nsource: community\ndate_added: \"2026-02-27\"\n---\n\n# Azure Document Intelligence REST SDK for TypeScript\n\nExtract text, tables, and structured data from documents using prebuilt and custom models.\n\n## Installation\n\n```bash\nnpm install @azure-rest\u002Fai-document-intelligence @azure\u002Fidentity\n```\n\n## Environment Variables\n\n```bash\nDOCUMENT_INTELLIGENCE_ENDPOINT=https:\u002F\u002F\u003Cresource>.cognitiveservices.azure.com\nDOCUMENT_INTELLIGENCE_API_KEY=\u003Capi-key>\n```\n\n## Authentication\n\n**Important**: This is a REST client. `DocumentIntelligence` is a **function**, not a class.\n\n### DefaultAzureCredential\n\n```typescript\nimport DocumentIntelligence from \"@azure-rest\u002Fai-document-intelligence\";\nimport { DefaultAzureCredential } from \"@azure\u002Fidentity\";\n\nconst client = DocumentIntelligence(\n  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,\n  new DefaultAzureCredential()\n);\n```\n\n### API Key\n\n```typescript\nimport DocumentIntelligence from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst client = DocumentIntelligence(\n  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,\n  { key: process.env.DOCUMENT_INTELLIGENCE_API_KEY! }\n);\n```\n\n## Analyze Document (URL)\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  AnalyzeOperationOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-layout\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: {\n      urlSource: \"https:\u002F\u002Fexample.com\u002Fdocument.pdf\"\n    },\n    queryParameters: { locale: \"en-US\" }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconsole.log(\"Pages:\", result.analyzeResult?.pages?.length);\nconsole.log(\"Tables:\", result.analyzeResult?.tables?.length);\n```\n\n## Analyze Document (Local File)\n\n```typescript\nimport { readFile } from \"node:fs\u002Fpromises\";\n\nconst fileBuffer = await readFile(\".\u002Fdocument.pdf\");\nconst base64Source = fileBuffer.toString(\"base64\");\n\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-invoice\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { base64Source }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n```\n\n## Prebuilt Models\n\n| Model ID | Description |\n|----------|-------------|\n| `prebuilt-read` | OCR - text and language extraction |\n| `prebuilt-layout` | Text, tables, selection marks, structure |\n| `prebuilt-invoice` | Invoice fields |\n| `prebuilt-receipt` | Receipt fields |\n| `prebuilt-idDocument` | ID document fields |\n| `prebuilt-tax.us.w2` | W-2 tax form fields |\n| `prebuilt-healthInsuranceCard.us` | Health insurance card fields |\n| `prebuilt-contract` | Contract fields |\n| `prebuilt-bankStatement.us` | Bank statement fields |\n\n## Extract Invoice Fields\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-invoice\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: invoiceUrl }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconst invoice = result.analyzeResult?.documents?.[0];\nif (invoice) {\n  console.log(\"Vendor:\", invoice.fields?.VendorName?.content);\n  console.log(\"Total:\", invoice.fields?.InvoiceTotal?.content);\n  console.log(\"Due Date:\", invoice.fields?.DueDate?.content);\n}\n```\n\n## Extract Receipt Fields\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-receipt\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: receiptUrl }\n  });\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconst receipt = result.analyzeResult?.documents?.[0];\nif (receipt) {\n  console.log(\"Merchant:\", receipt.fields?.MerchantName?.content);\n  console.log(\"Total:\", receipt.fields?.Total?.content);\n  \n  for (const item of receipt.fields?.Items?.values || []) {\n    console.log(\"Item:\", item.properties?.Description?.content);\n    console.log(\"Price:\", item.properties?.TotalPrice?.content);\n  }\n}\n```\n\n## List Document Models\n\n```typescript\nimport DocumentIntelligence, { isUnexpected, paginate } from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst response = await client.path(\"\u002FdocumentModels\").get();\n\nif (isUnexpected(response)) {\n  throw response.body.error;\n}\n\nfor await (const model of paginate(client, response)) {\n  console.log(model.modelId);\n}\n```\n\n## Build Custom Model\n\n```typescript\nconst initialResponse = await client.path(\"\u002FdocumentModels:build\").post({\n  body: {\n    modelId: \"my-custom-model\",\n    description: \"Custom model for purchase orders\",\n    buildMode: \"template\",  \u002F\u002F or \"neural\"\n    azureBlobSource: {\n      containerUrl: process.env.TRAINING_CONTAINER_SAS_URL!,\n      prefix: \"training-data\u002F\"\n    }\n  }\n});\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = await poller.pollUntilDone();\nconsole.log(\"Model built:\", result.body);\n```\n\n## Build Document Classifier\n\n```typescript\nimport { DocumentClassifierBuildOperationDetailsOutput } from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst containerSasUrl = process.env.TRAINING_CONTAINER_SAS_URL!;\n\nconst initialResponse = await client.path(\"\u002FdocumentClassifiers:build\").post({\n  body: {\n    classifierId: \"my-classifier\",\n    description: \"Invoice vs Receipt classifier\",\n    docTypes: {\n      invoices: {\n        azureBlobSource: { containerUrl: containerSasUrl, prefix: \"invoices\u002F\" }\n      },\n      receipts: {\n        azureBlobSource: { containerUrl: containerSasUrl, prefix: \"receipts\u002F\" }\n      }\n    }\n  }\n});\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as DocumentClassifierBuildOperationDetailsOutput;\nconsole.log(\"Classifier:\", result.result?.classifierId);\n```\n\n## Classify Document\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentClassifiers\u002F{classifierId}:analyze\", \"my-classifier\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: documentUrl },\n    queryParameters: { split: \"auto\" }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = await poller.pollUntilDone();\nconsole.log(\"Classification:\", result.body.analyzeResult?.documents);\n```\n\n## Get Service Info\n\n```typescript\nconst response = await client.path(\"\u002Finfo\").get();\n\nif (isUnexpected(response)) {\n  throw response.body.error;\n}\n\nconsole.log(\"Custom model limit:\", response.body.customDocumentModels.limit);\nconsole.log(\"Custom model count:\", response.body.customDocumentModels.count);\n```\n\n## Polling Pattern\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  AnalyzeOperationOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n\n\u002F\u002F 1. Start operation\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-layout\")\n  .post({ contentType: \"application\u002Fjson\", body: { urlSource } });\n\n\u002F\u002F 2. Check for errors\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\n\u002F\u002F 3. Create poller\nconst poller = getLongRunningPoller(client, initialResponse);\n\n\u002F\u002F 4. Optional: Monitor progress\npoller.onProgress((state) => {\n  console.log(\"Status:\", state.status);\n});\n\n\u002F\u002F 5. Wait for completion\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n```\n\n## Key Types\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  paginate,\n  parseResultIdFromResponse,\n  AnalyzeOperationOutput,\n  DocumentClassifierBuildOperationDetailsOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n```\n\n## Best Practices\n\n1. **Use getLongRunningPoller()** - Document analysis is async, always poll for results\n2. **Check isUnexpected()** - Type guard for proper error handling\n3. **Choose the right model** - Use prebuilt models when possible, custom for specialized docs\n4. **Handle confidence scores** - Fields have confidence values, set thresholds for your use case\n5. **Use pagination** - Use `paginate()` helper for listing models\n6. **Prefer neural mode** - For custom models, neural handles more variation than template\n\n## When to Use\nThis skill is applicable to execute the workflow or actions described in the overview.\n","# Azure Document Intelligence REST SDK for TypeScript\n\nExtract text, tables, and structured data from documents using prebuilt and custom models.\n\n## Installation\n\n```bash\nnpm install @azure-rest\u002Fai-document-intelligence @azure\u002Fidentity\n```\n\n## Environment Variables\n\n```bash\nDOCUMENT_INTELLIGENCE_ENDPOINT=https:\u002F\u002F\u003Cresource>.cognitiveservices.azure.com\nDOCUMENT_INTELLIGENCE_API_KEY=\u003Capi-key>\n```\n\n## Authentication\n\n**Important**: This is a REST client. `DocumentIntelligence` is a **function**, not a class.\n\n### DefaultAzureCredential\n\n```typescript\nimport DocumentIntelligence from \"@azure-rest\u002Fai-document-intelligence\";\nimport { DefaultAzureCredential } from \"@azure\u002Fidentity\";\n\nconst client = DocumentIntelligence(\n  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,\n  new DefaultAzureCredential()\n);\n```\n\n### API Key\n\n```typescript\nimport DocumentIntelligence from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst client = DocumentIntelligence(\n  process.env.DOCUMENT_INTELLIGENCE_ENDPOINT!,\n  { key: process.env.DOCUMENT_INTELLIGENCE_API_KEY! }\n);\n```\n\n## Analyze Document (URL)\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  AnalyzeOperationOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-layout\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: {\n      urlSource: \"https:\u002F\u002Fexample.com\u002Fdocument.pdf\"\n    },\n    queryParameters: { locale: \"en-US\" }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconsole.log(\"Pages:\", result.analyzeResult?.pages?.length);\nconsole.log(\"Tables:\", result.analyzeResult?.tables?.length);\n```\n\n## Analyze Document (Local File)\n\n```typescript\nimport { readFile } from \"node:fs\u002Fpromises\";\n\nconst fileBuffer = await readFile(\".\u002Fdocument.pdf\");\nconst base64Source = fileBuffer.toString(\"base64\");\n\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-invoice\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { base64Source }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n```\n\n## Prebuilt Models\n\n| Model ID | Description |\n|----------|-------------|\n| `prebuilt-read` | OCR - text and language extraction |\n| `prebuilt-layout` | Text, tables, selection marks, structure |\n| `prebuilt-invoice` | Invoice fields |\n| `prebuilt-receipt` | Receipt fields |\n| `prebuilt-idDocument` | ID document fields |\n| `prebuilt-tax.us.w2` | W-2 tax form fields |\n| `prebuilt-healthInsuranceCard.us` | Health insurance card fields |\n| `prebuilt-contract` | Contract fields |\n| `prebuilt-bankStatement.us` | Bank statement fields |\n\n## Extract Invoice Fields\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-invoice\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: invoiceUrl }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconst invoice = result.analyzeResult?.documents?.[0];\nif (invoice) {\n  console.log(\"Vendor:\", invoice.fields?.VendorName?.content);\n  console.log(\"Total:\", invoice.fields?.InvoiceTotal?.content);\n  console.log(\"Due Date:\", invoice.fields?.DueDate?.content);\n}\n```\n\n## Extract Receipt Fields\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-receipt\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: receiptUrl }\n  });\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n\nconst receipt = result.analyzeResult?.documents?.[0];\nif (receipt) {\n  console.log(\"Merchant:\", receipt.fields?.MerchantName?.content);\n  console.log(\"Total:\", receipt.fields?.Total?.content);\n  \n  for (const item of receipt.fields?.Items?.values || []) {\n    console.log(\"Item:\", item.properties?.Description?.content);\n    console.log(\"Price:\", item.properties?.TotalPrice?.content);\n  }\n}\n```\n\n## List Document Models\n\n```typescript\nimport DocumentIntelligence, { isUnexpected, paginate } from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst response = await client.path(\"\u002FdocumentModels\").get();\n\nif (isUnexpected(response)) {\n  throw response.body.error;\n}\n\nfor await (const model of paginate(client, response)) {\n  console.log(model.modelId);\n}\n```\n\n## Build Custom Model\n\n```typescript\nconst initialResponse = await client.path(\"\u002FdocumentModels:build\").post({\n  body: {\n    modelId: \"my-custom-model\",\n    description: \"Custom model for purchase orders\",\n    buildMode: \"template\",  \u002F\u002F or \"neural\"\n    azureBlobSource: {\n      containerUrl: process.env.TRAINING_CONTAINER_SAS_URL!,\n      prefix: \"training-data\u002F\"\n    }\n  }\n});\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = await poller.pollUntilDone();\nconsole.log(\"Model built:\", result.body);\n```\n\n## Build Document Classifier\n\n```typescript\nimport { DocumentClassifierBuildOperationDetailsOutput } from \"@azure-rest\u002Fai-document-intelligence\";\n\nconst containerSasUrl = process.env.TRAINING_CONTAINER_SAS_URL!;\n\nconst initialResponse = await client.path(\"\u002FdocumentClassifiers:build\").post({\n  body: {\n    classifierId: \"my-classifier\",\n    description: \"Invoice vs Receipt classifier\",\n    docTypes: {\n      invoices: {\n        azureBlobSource: { containerUrl: containerSasUrl, prefix: \"invoices\u002F\" }\n      },\n      receipts: {\n        azureBlobSource: { containerUrl: containerSasUrl, prefix: \"receipts\u002F\" }\n      }\n    }\n  }\n});\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = (await poller.pollUntilDone()).body as DocumentClassifierBuildOperationDetailsOutput;\nconsole.log(\"Classifier:\", result.result?.classifierId);\n```\n\n## Classify Document\n\n```typescript\nconst initialResponse = await client\n  .path(\"\u002FdocumentClassifiers\u002F{classifierId}:analyze\", \"my-classifier\")\n  .post({\n    contentType: \"application\u002Fjson\",\n    body: { urlSource: documentUrl },\n    queryParameters: { split: \"auto\" }\n  });\n\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\nconst poller = getLongRunningPoller(client, initialResponse);\nconst result = await poller.pollUntilDone();\nconsole.log(\"Classification:\", result.body.analyzeResult?.documents);\n```\n\n## Get Service Info\n\n```typescript\nconst response = await client.path(\"\u002Finfo\").get();\n\nif (isUnexpected(response)) {\n  throw response.body.error;\n}\n\nconsole.log(\"Custom model limit:\", response.body.customDocumentModels.limit);\nconsole.log(\"Custom model count:\", response.body.customDocumentModels.count);\n```\n\n## Polling Pattern\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  AnalyzeOperationOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n\n\u002F\u002F 1. Start operation\nconst initialResponse = await client\n  .path(\"\u002FdocumentModels\u002F{modelId}:analyze\", \"prebuilt-layout\")\n  .post({ contentType: \"application\u002Fjson\", body: { urlSource } });\n\n\u002F\u002F 2. Check for errors\nif (isUnexpected(initialResponse)) {\n  throw initialResponse.body.error;\n}\n\n\u002F\u002F 3. Create poller\nconst poller = getLongRunningPoller(client, initialResponse);\n\n\u002F\u002F 4. Optional: Monitor progress\npoller.onProgress((state) => {\n  console.log(\"Status:\", state.status);\n});\n\n\u002F\u002F 5. Wait for completion\nconst result = (await poller.pollUntilDone()).body as AnalyzeOperationOutput;\n```\n\n## Key Types\n\n```typescript\nimport DocumentIntelligence, {\n  isUnexpected,\n  getLongRunningPoller,\n  paginate,\n  parseResultIdFromResponse,\n  AnalyzeOperationOutput,\n  DocumentClassifierBuildOperationDetailsOutput\n} from \"@azure-rest\u002Fai-document-intelligence\";\n```\n\n## Best Practices\n\n1. **Use getLongRunningPoller()** - Document analysis is async, always poll for results\n2. **Check isUnexpected()** - Type guard for proper error handling\n3. **Choose the right model** - Use prebuilt models when possible, custom for specialized docs\n4. **Handle confidence scores** - Fields have confidence values, set thresholds for your use case\n5. **Use pagination** - Use `paginate()` helper for listing models\n6. **Prefer neural mode** - For custom models, neural handles more variation than template\n\n## When to Use\nThis skill is applicable to execute the workflow or actions described in the overview.\n",{"name":5,"risk":32,"source":35,"date_added":46,"description":7},"2026-02-27","main","7a38d8e7073e61c16eda85681cb32fb68a8657a5","skills-store\u002Fcursor\u002Fazure-ai-document-intelligence-ts","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router","https:\u002F\u002Fgithub.com\u002Fsapsapshen","2026-04-14 21:12:12",{"source":8,"skillName":5,"commands":54,"prompt":64,"zipAvailable":65},[55,58,61],{"tool":56,"command":57},"npx","npx skills add sapsapshen\u002Fai-memory-router --skill azure-ai-document-intelligence-ts",{"tool":59,"command":60},"bunx","bunx skills add sapsapshen\u002Fai-memory-router --skill azure-ai-document-intelligence-ts",{"tool":62,"command":63},"pnpm","pnpm dlx skills add sapsapshen\u002Fai-memory-router --skill azure-ai-document-intelligence-ts","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fcursor\u002Fazure-ai-document-intelligence-ts\u002FSKILL.md",true,[],[68,92,117,127,140,157],{"skillNo":69,"name":70,"nameZh":6,"description":71,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":72,"categories":73,"keywords":79,"publishedAt":41},"01M71ATQRKG48SH06FQ697T5G9","wechat-search","Search WeChat Official Account articles using OpenClaw's web search and fetch capabilities with compliance-focused design.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fwechat-search-release\u002FSKILL.md",[74],{"categoryNo":75,"categoryName":76,"taxonomyType":77,"taxonomyTypeDesc":78},"01JBSEEDCAT000000000000037","律师与法务","PROFESSION","适用职业",[80,81,82,83,84,85,86,87,88,89,90,91],"wechat search","wechat","search","capabilities","openclaw","design","web search","compliance","web","official","fetch","with",{"skillNo":93,"name":94,"nameZh":6,"description":95,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":96,"categories":97,"keywords":98,"publishedAt":41},"01M71ATNAVGZB35PFYM2GC5N00","trend-tap","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend tap', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-tap\u002FSKILL.md",[],[99,100,101,102,103,104,82,105,106,107,108,109,110,111,39,112,113,114,115,116],"trend","trend tap","tap","api keys","Bash","time","trending","hacker","aggregator","do","when","brew","live","google","install","read","across","api",{"skillNo":118,"name":119,"nameZh":6,"description":120,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":121,"categories":122,"keywords":123,"publishedAt":41},"01M71ATJ9AM5KM15AA8PS302EB","trend-radar","Real-time trending topics aggregator across 7 platforms (X\u002FTwitter, Reddit, Google Trends, Hacker News, Zhihu, Bilibili, Weibo). Trigger: when user says 'trend', 'trends', 'trend pulse', '热点', '热搜', or asks what is trending\u002Fhot. Do NOT use web_search — this skill already fetches live data from all platforms with zero API keys.","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftrend-radar\u002FSKILL.md",[],[124,125,99,110,111,39,112,103,82,114,126,115,116,109,107,106,105,113,104,102],"trend radar","radar","pulse",{"skillNo":128,"name":129,"nameZh":6,"description":130,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":131,"categories":132,"keywords":133,"publishedAt":41},"01M71ATGF095N3EJM9G8SD0BB5","tech-news-daily","每日科技新闻汇——从全球多个 RSS 源抓取最新科技新闻，翻译（英→中）、去重、排版成每日简报。当用户询问科技新闻、科技新鲜事、每日科技、技术动态、Daily Tech News 或类似表达时触发此技能。","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Ftech-news-daily\u002FSKILL.md",[],[134,135,136,137,138,139],"news","tech","tech news daily","daily","rss","翻译",{"skillNo":141,"name":142,"nameZh":6,"description":143,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":144,"categories":145,"keywords":149,"publishedAt":41},"01M71ATFAEAMQ17M70NQNY7SR8","summarize","Summarize URLs or files with the summarize CLI (web, PDFs, images, audio, YouTube).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsummarize\u002FSKILL.md",[146],{"categoryNo":147,"categoryName":148,"taxonomyType":21,"taxonomyTypeDesc":22},"01JBSEEDCAT000000000000021","资料检索与研究",[142,88,150,151,152,91,110,153,154,155,101,156,113],"Audio","cli","youtube","images","https","files","pdfs",{"skillNo":158,"name":159,"nameZh":6,"description":160,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":161,"categories":162,"keywords":163,"publishedAt":41},"01M71ATDNS3R0M4H936PACQAWZ","sonoscli","Control Sonos speakers (discover\u002Fstatus\u002Fplay\u002Fvolume\u002Fgroup).","https:\u002F\u002Fgithub.com\u002Fsapsapshen\u002Fai-memory-router\u002Fblob\u002Fmain\u002Fskills-store\u002Fopenclaw\u002Fsonoscli\u002FSKILL.md",[],[159,164,165,166,113,167,154,168,169,170,171,172],"status","play","go","latest","github","discover","control","cmd","volume"]