[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill-microsoft-add-workiq":3,"mdc-rkga8a-key":33,"related-repo-microsoft-add-workiq":9000,"related-org-microsoft-add-workiq":9073},{"slug":4,"name":4,"fn":5,"description":6,"org":7,"tags":11,"stars":23,"repoUrl":24,"updatedAt":25,"license":26,"forks":27,"topics":28,"repo":29,"sourceUrl":31,"mdContent":32},"add-workiq","add Work IQ Copilot MCP","Adds Work IQ Copilot MCP by delegating to \u002Fadd-connector with api-id=shared_a365copilotchatmcp and action mode. Use when users need Microsoft 365 knowledge-grounded Work IQ search\u002Fchat.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},"microsoft","Microsoft","https:\u002F\u002Fpexgzepcugksgbtrxkhf.supabase.co\u002Fstorage\u002Fv1\u002Fobject\u002Fpublic\u002Forg-logos\u002Fmicrosoft.png",[12,16,19,20],{"name":13,"slug":14,"type":15},"Copilot","copilot","tag",{"name":17,"slug":18,"type":15},"Microsoft 365","microsoft-365",{"name":9,"slug":8,"type":15},{"name":21,"slug":22,"type":15},"MCP","mcp",2,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FManaged-Apps","2026-07-03T16:31:35.439156",null,3,[],{"repoUrl":24,"stars":23,"forks":27,"topics":30,"description":26},[],"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002FManaged-Apps\u002Ftree\u002FHEAD\u002Fplugins\u002Fmicrosoft-managed-apps\u002Fskills\u002Fadd-workiq","---\nname: add-workiq\ndescription: Adds Work IQ Copilot MCP by delegating to \u002Fadd-connector with api-id=shared_a365copilotchatmcp and action mode. Use when users need Microsoft 365 knowledge-grounded Work IQ search\u002Fchat.\nuser-invocable: true\nallowed-tools: Read, AskUserQuestion, Skill\nmodel: sonnet\n---\n\n**šŸ“‹ Shared Instructions: [shared-instructions.md](${CLAUDE_PLUGIN_ROOT}\u002Fshared\u002Fshared-instructions.md)** ā€” Cross-cutting concerns.\n\n# Add Work IQ Copilot MCP (Wrapper)\n\nThis skill is a thin wrapper. Use `\u002Fadd-connector` as the single implementation path.\n\n## Delegation contract\n\nInvoke `\u002Fadd-connector` with:\n\n- `api-id`: `shared_a365copilotchatmcp`\n- `mode`: `action`\n\n---\n\n# Work IQ Integration: MCP Session Pattern\n\nAfter the connector is added, you'll have access to `WorkIQCopilotMCPService`. **Work IQ uses MCP (Model Context Protocol), a stateful protocol. Use the `McpSession` wrapper class to manage this properly.**\n\n## Setup: Create McpSession Wrapper\n\nāš ļø **CRITICAL:** The McpSession implementation is complex. Copy the production-ready code below exactly. It handles session negotiation, auto-retry on errors, proper JSON-RPC ID sequencing, and response parsing.\n\nCreate `src\u002Fconnectors\u002FmcpClient.ts`:\n\n```typescript\nimport type { IOperationResult } from '@microsoft\u002Fmanaged-apps\u002Fdata'\nimport { WorkIQCopilotMCPService } from '..\u002F..\u002Fgenerated\u002Fservices\u002FWorkIQCopilotMCPService'\nimport type { QueryRequest } from '..\u002F..\u002Fgenerated\u002Fmodels\u002FWorkIQCopilotMCPModel'\n\nexport interface JsonRpcRequest {\n jsonrpc: '2.0'\n id?: string\n method: string\n params?: Record\u003Cstring, unknown>\n}\n\nexport interface JsonRpcResponse {\n jsonrpc?: string\n id?: string\n result?: Record\u003Cstring, unknown>\n error?: { code?: number; message?: string; data?: unknown }\n}\n\ntype CopilotConversationMessage = {\n text?: string\n attributions?: Array\u003C{ attributionType?: string; providerDisplayName?: string; seeMoreWebUrl?: string }>\n}\n\ntype CopilotConversation = {\n messages?: CopilotConversationMessage[]\n}\n\nfunction parseRpc(result: IOperationResult\u003Cunknown>): JsonRpcResponse {\n if (!result.success && result.error) {\n return { error: { message: result.error.message } }\n }\n\n const data: unknown = result.data\n if (data == null) return {}\n if (typeof data === 'object') return data as JsonRpcResponse\n if (typeof data === 'string') {\n const dataLines = data\n .split(\u002F\\r?\\n\u002F)\n .filter((line) => line.startsWith('data:'))\n .map((line) => line.slice(5).trim())\n const payload = dataLines.length ? dataLines.join('') : data\n try {\n return JSON.parse(payload) as JsonRpcResponse\n } catch {\n return { result: { raw: data } }\n }\n }\n\n return { result: { raw: data } }\n}\n\nexport class McpSession {\n private nextId = 1\n private sessionId: string | undefined\n private conversationId: string | undefined\n private initialized = false\n\n private extractSessionId(raw: IOperationResult\u003Cunknown>): string | undefined {\n const container = raw as unknown as Record\u003Cstring, unknown>\n const dataObj =\n raw.data && typeof raw.data === 'object' ? (raw.data as Record\u003Cstring, unknown>) : undefined\n const resultObj =\n dataObj?.result && typeof dataObj.result === 'object'\n ? (dataObj.result as Record\u003Cstring, unknown>)\n : undefined\n\n const candidates: Array\u003Cunknown> = [\n dataObj?.['Mcp-Session-Id'],\n dataObj?.mcpSessionId,\n dataObj?.sessionId,\n resultObj?.['Mcp-Session-Id'],\n resultObj?.mcpSessionId,\n resultObj?.sessionId,\n container['Mcp-Session-Id'],\n container.mcpSessionId,\n container.sessionId,\n ]\n\n const found = candidates.find((value) => typeof value === 'string' && value.length > 0)\n return typeof found === 'string' ? found : undefined\n }\n\n private isSessionNotFound(res: JsonRpcResponse): boolean {\n const message = (res.error?.message ?? '').toLowerCase()\n return message.includes('session not found') || res.error?.code === -32001\n }\n\n private resetSession(): void {\n this.sessionId = undefined\n this.initialized = false\n }\n\n private async send(\n method: string,\n params?: Record\u003Cstring, unknown>,\n allowRetry = true\n ): Promise\u003CJsonRpcResponse> {\n const req: JsonRpcRequest = { jsonrpc: '2.0', id: String(this.nextId++), method, params }\n const raw = (await WorkIQCopilotMCPService.mcp_m365copilot(\n this.sessionId,\n req as QueryRequest\n )) as unknown as IOperationResult\u003Cunknown>\n\n const negotiatedSessionId = this.extractSessionId(raw)\n if (negotiatedSessionId) {\n this.sessionId = negotiatedSessionId\n }\n\n const parsed = parseRpc(raw)\n\n if (allowRetry && method !== 'initialize' && this.isSessionNotFound(parsed)) {\n this.resetSession()\n await this.initialize()\n return this.send(method, params, false)\n }\n\n return parsed\n }\n\n async initialize(): Promise\u003CJsonRpcResponse> {\n const res = await this.send('initialize', {\n protocolVersion: '2025-06-18',\n capabilities: {},\n clientInfo: { name: 'Custom App', version: '1.0.0' },\n })\n this.initialized = !res.error\n return res\n }\n\n async callCopilotChat(message: string): Promise\u003C{ text: string; conversationId?: string }> {\n if (!this.initialized) await this.initialize()\n const raw = await this.send('tools\u002Fcall', {\n name: 'CopilotChat',\n arguments: {\n message,\n ...(this.conversationId ? { conversationId: this.conversationId } : {}),\n },\n })\n\n const parsed = extractCopilotText(raw)\n if (parsed.conversationId) {\n this.conversationId = parsed.conversationId\n }\n\n return { text: parsed.text, conversationId: parsed.conversationId }\n }\n}\n\nfunction extractContentText(res: JsonRpcResponse): string | undefined {\n const content = res.result?.content as Array\u003C{ type?: string; text?: string }> | undefined\n if (!Array.isArray(content)) {\n return undefined\n }\n\n const textBlocks = content\n .filter((c) => c.type === 'text' && typeof c.text === 'string')\n .map((c) => c.text!.trim())\n .filter((value) => value.length > 0)\n\n if (textBlocks.length === 0) {\n return undefined\n }\n\n \u002F\u002F Prefer the JSON payload block. Some responses append metadata text blocks\n \u002F\u002F such as \"CorrelationId: ...\" that should not be concatenated.\n const jsonBlock = textBlocks.find(\n (block) => block.startsWith('{') && \u002F\"conversationId\"|\"rawResponse\"|\"reply\"\u002F.test(block)\n )\n if (jsonBlock) {\n return jsonBlock\n }\n\n const nonMetadata = textBlocks.find((block) => !\u002F^CorrelationId\\s*:\u002Fi.test(block))\n return nonMetadata ?? textBlocks[0]\n}\n\nexport function extractCopilotText(res: JsonRpcResponse): { text: string; conversationId?: string } {\n if (res.error) {\n return { text: `Error: ${res.error.message ?? JSON.stringify(res.error)}` }\n }\n\n const rawText = extractContentText(res)\n if (!rawText) {\n return { text: res.result ? JSON.stringify(res.result, null, 2) : '(no content returned)' }\n }\n\n try {\n const inner = JSON.parse(rawText) as {\n conversationId?: string\n reply?: string\n message?: string\n rawResponse?: string\n }\n\n if (typeof inner.rawResponse === 'string') {\n try {\n const convo = JSON.parse(inner.rawResponse) as CopilotConversation\n const messages = Array.isArray(convo.messages) ? convo.messages : []\n const attributed = messages.find(\n (m) => Array.isArray(m.attributions) && m.attributions.length > 0\n )\n const selected = attributed ?? messages[1] ?? messages[messages.length - 1]\n const replyText = selected?.text?.trim()\n if (replyText) {\n return { text: replyText, conversationId: inner.conversationId }\n }\n } catch {\n \u002F\u002F Fall through to simple reply extraction.\n }\n }\n\n const fallbackText = inner.reply?.trim() || inner.message?.trim() || rawText\n return { text: fallbackText, conversationId: inner.conversationId }\n } catch {\n return { text: rawText }\n }\n}\n```\n\n## Usage: Generic Work IQ Integration Pattern\n\nInitialize **once per app** (typically on component mount or app boot) and reuse for all Work IQ calls:\n\n```typescript\nimport { McpSession } from '.\u002Fconnectors\u002FmcpClient'\n\n\u002F\u002F Initialize once per app session (e.g., in React useEffect on app boot)\nconst workIqSession = new McpSession()\n\n\u002F\u002F Call with any knowledge-grounded prompt\nexport async function queryWorkIQ(userPrompt: string): Promise\u003Cstring> {\n try {\n const { text } = await workIqSession.callCopilotChat(userPrompt)\n return text\n } catch (error) {\n const msg = error instanceof Error ? error.message : 'Work IQ query failed'\n console.error('Work IQ Error:', msg)\n throw error\n }\n}\n```\n\n**Key Patterns:**\n- āœ… Initialize once, reuse across multiple calls\n- āœ… Pass context-specific prompts to `callCopilotChat()`\n- āœ… Adapt prompts for your specific scenario (meetings, priorities, analysis, etc.)\n- āœ… Session automatically reinitializes if \"Session not found\" error occurs\n- āœ… Conversation ID is automatically persisted across calls for multi-turn chats\n\n## Prompt Structure\n\nWork IQ responds well to **context-rich, structured prompts**. Use this pattern and adapt it for your specific scenario:\n\n```typescript\n\u002F\u002F Generic pattern to adapt for your use case:\nconst prompt = `\nYou are [role\u002Fexpert description].\n\n**Context:**\n- [Relevant data or background information]\n- [Additional context as needed]\n\n**Task:** [Clear, specific instruction]\n\n**Format:** [If you need structured output, specify the format]\n- Use markdown with clear section headings (## Section, ## Action Items, etc.)\n- Specify limits (word count, number of items, etc.)\n`.trim()\n\nconst { text } = await workIqSession.callCopilotChat(prompt)\n```\n\n**How to adapt this pattern:**\n- āœ… Customize the role and context for your scenario (e.g., \"meeting summarizer\", \"action item prioritizer\", \"project analyst\")\n- āœ… Add domain-specific information from your app\n- āœ… Define the exact format you need (structured markdown, JSON, bullets, etc.)\n- āœ… Adjust word limits and output expectations for your use case\n\n**Examples of adaptable scenarios:**\n- Meeting summaries with action items\n- Prioritized daily action items from emails\n- Project risk analysis from documents\n- Team performance insights from communications\n- Or any other knowledge-grounded analysis task\n\n## Response Parsing\n\nWork IQ returns text that you parse based on your use case.\n\n**For structured markdown output** (when you asked for ## sections):\n\n```typescript\nconst { text } = await workIqSession.callCopilotChat(prompt)\n\n\u002F\u002F Extract markdown sections\nfunction extractSection(text: string, sectionName: string): string[] {\n const regex = new RegExp(`##\\\\s*${sectionName}\\\\s*([\\\\s\\\\S]*?)(?=##|$)`)\n const match = text.match(regex)\n if (!match) return []\n \n return match[1]\n .split('\\n')\n .filter(line => line.trim().startsWith('-'))\n .map(line => line.replace(\u002F^-\\s*\u002F, '').trim())\n .filter(Boolean)\n}\n\nconst summary = extractSection(text, 'Summary')\nconst actionItems = extractSection(text, 'Action Items')\n```\n\n**For unstructured output** (when format is not critical):\n\n```typescript\nconst { text } = await workIqSession.callCopilotChat(prompt)\n\u002F\u002F Use text directly - display as-is or format as needed for your UI\n```\n\n**Adjust parsing based on:**\n- āœ… The format you specified in the prompt\n- āœ… Your response structure (markdown sections, JSON, numbered lists, etc.)\n- āœ… Both structured (markdown, JSON) and unstructured (text) outputs\n\n## Error Handling & Auto-Recovery\n\nMcpSession automatically handles \"Session not found\" errors by reinitializing. Surface errors appropriately:\n\n```typescript\ntry {\n const { text } = await workIqSession.callCopilotChat(prompt)\n \n if (text.includes('Error:')) {\n throw new Error(text)\n }\n \n return text\n} catch (error) {\n const errorMsg = error instanceof Error ? error.message : 'Query failed'\n console.error('Work IQ Error:', errorMsg)\n throw error\n}\n```\n\n**What McpSession handles automatically:**\n- āœ… Detects \"Session not found\" (-32001) errors\n- āœ… Closes the session and auto-reinitializes\n- āœ… Retries the failed request with the new session\n- āœ… No manual retry logic needed\n\n**You only need to:**\n- āœ… Wrap calls in try\u002Fcatch\n- āœ… Surface errors to users appropriately\n- āœ… Let exceptions propagate for app-level error handling\n\n---\n\n## Implementation Guidance\n\n**Step 1: Copy mcpClient.ts**\nUse the provided McpSession implementation as-is. It handles all MCP protocol complexity.\n\n**Step 2: Initialize once**\nCreate the McpSession instance once per app session (in useEffect or on boot).\n\n**Step 3: Craft your prompts**\nFor your specific use case, provide context-rich prompts that include:\n- Your domain context (meetings, priorities, risks, etc.)\n- Specific data from your app\n- Expected output format\n\n**Step 4: Parse and display**\nExtract the relevant data from Work IQ's response based on the format you requested.\n\n---\n\n## Common Use Cases\n\n**Meeting Summaries:**\n- Prompt Work IQ with meeting context (date, organizer, attendees, description)\n- Request ## Summary and ## Action Items sections\n- Parse markdown sections and display in modal\n\n**Prioritized Daily Action Items:**\n- Query Work IQ to extract high-priority tasks from emails\u002Fmessages\n- Request ranked list format with due dates and owners\n- Parse and display as prioritized task list\n\n**Project Risk Analysis:**\n- Prompt Work IQ to analyze project communications\n- Request structured risk assessment with mitigation recommendations\n- Parse JSON and display risk dashboard\n\n**Team Performance Insights:**\n- Query collaboration patterns from Teams\u002Femails\n- Request insights on productivity and blockers\n- Parse and display performance dashboard\n\n**Any Knowledge-Grounded Analysis:**\n- Adapt the pattern for your domain\n- Use Work IQ's access to M365 data (emails, Teams, calendar, documents)\n- Return structured or unstructured output as needed\n\n## Why This Pattern is Required\n\n**Work IQ uses MCP (Model Context Protocol)**, a stateful protocol that requires:\n1. **Session initialization** before first call (handshake to exchange capabilities)\n2. **Session ID tracking** across all requests\n3. **Proper JSON-RPC ID sequencing** (each request must have a unique numeric ID)\n4. **Multi-turn conversation support** with conversation ID persistence\n5. **Complex response parsing** (nested JSON-RPC + optional streaming)\n6. **Automatic error recovery** on session timeouts\n\nThe `McpSession` class handles all of this. Attempting to bypass it (using random session IDs, hardcoded IDs, or direct API calls) will result in \"Session not found\" errors and failed integrations.\n",{"data":34,"body":38},{"name":4,"description":6,"user-invocable":35,"allowed-tools":36,"model":37},true,"Read, AskUserQuestion, Skill","sonnet",{"type":39,"children":40},"root",[41,62,69,83,90,102,140,144,150,176,182,194,207,6811,6817,6829,7232,7240,7274,7280,7292,7486,7494,7517,7525,7553,7559,7564,7574,8212,8222,8280,8288,8306,8312,8317,8639,8647,8670,8678,8696,8699,8705,8715,8725,8735,8753,8763,8766,8772,8780,8798,8806,8824,8832,8850,8858,8876,8884,8902,8908,8918,8982,8994],{"type":42,"tag":43,"props":44,"children":45},"element","p",{},[46,60],{"type":42,"tag":47,"props":48,"children":49},"strong",{},[50,53],{"type":51,"value":52},"text","šŸ“‹ Shared Instructions: ",{"type":42,"tag":54,"props":55,"children":57},"a",{"href":56},"$%7BCLAUDE_PLUGIN_ROOT%7D\u002Fshared\u002Fshared-instructions.md",[58],{"type":51,"value":59},"shared-instructions.md",{"type":51,"value":61}," ā€” Cross-cutting concerns.",{"type":42,"tag":63,"props":64,"children":66},"h1",{"id":65},"add-work-iq-copilot-mcp-wrapper",[67],{"type":51,"value":68},"Add Work IQ Copilot MCP (Wrapper)",{"type":42,"tag":43,"props":70,"children":71},{},[72,74,81],{"type":51,"value":73},"This skill is a thin wrapper. 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",{"type":42,"tag":47,"props":164,"children":165},{},[166,168,174],{"type":51,"value":167},"Work IQ uses MCP (Model Context Protocol), a stateful protocol. Use the ",{"type":42,"tag":75,"props":169,"children":171},{"className":170},[],[172],{"type":51,"value":173},"McpSession",{"type":51,"value":175}," wrapper class to manage this properly.",{"type":42,"tag":84,"props":177,"children":179},{"id":178},"setup-create-mcpsession-wrapper",[180],{"type":51,"value":181},"Setup: Create McpSession Wrapper",{"type":42,"tag":43,"props":183,"children":184},{},[185,187,192],{"type":51,"value":186},"āš ļø ",{"type":42,"tag":47,"props":188,"children":189},{},[190],{"type":51,"value":191},"CRITICAL:",{"type":51,"value":193}," The McpSession implementation is complex. Copy the production-ready code below exactly. It handles session negotiation, auto-retry on errors, proper JSON-RPC ID sequencing, and response parsing.",{"type":42,"tag":43,"props":195,"children":196},{},[197,199,205],{"type":51,"value":198},"Create ",{"type":42,"tag":75,"props":200,"children":202},{"className":201},[],[203],{"type":51,"value":204},"src\u002Fconnectors\u002FmcpClient.ts",{"type":51,"value":206},":",{"type":42,"tag":208,"props":209,"children":214},"pre",{"className":210,"code":211,"language":212,"meta":213,"style":213},"language-typescript shiki shiki-themes material-theme-lighter material-theme material-theme-palenight","import type { IOperationResult } from '@microsoft\u002Fmanaged-apps\u002Fdata'\nimport { WorkIQCopilotMCPService } from '..\u002F..\u002Fgenerated\u002Fservices\u002FWorkIQCopilotMCPService'\nimport type { QueryRequest } from '..\u002F..\u002Fgenerated\u002Fmodels\u002FWorkIQCopilotMCPModel'\n\nexport interface JsonRpcRequest {\n jsonrpc: '2.0'\n id?: string\n method: string\n params?: Record\u003Cstring, unknown>\n}\n\nexport interface JsonRpcResponse {\n jsonrpc?: string\n id?: string\n result?: Record\u003Cstring, unknown>\n error?: { code?: number; message?: string; data?: unknown }\n}\n\ntype CopilotConversationMessage = {\n text?: string\n attributions?: Array\u003C{ attributionType?: string; providerDisplayName?: string; seeMoreWebUrl?: string }>\n}\n\ntype CopilotConversation = {\n messages?: CopilotConversationMessage[]\n}\n\nfunction parseRpc(result: IOperationResult\u003Cunknown>): JsonRpcResponse {\n if (!result.success && result.error) {\n return { error: { message: result.error.message } }\n }\n\n const data: unknown = result.data\n if (data == null) return {}\n if (typeof data === 'object') return data as JsonRpcResponse\n if (typeof data === 'string') {\n const dataLines = data\n .split(\u002F\\r?\\n\u002F)\n .filter((line) => line.startsWith('data:'))\n .map((line) => line.slice(5).trim())\n const payload = dataLines.length ? dataLines.join('') : data\n try {\n return JSON.parse(payload) as JsonRpcResponse\n } catch {\n return { result: { raw: data } }\n }\n }\n\n return { result: { raw: data } }\n}\n\nexport class McpSession {\n private nextId = 1\n private sessionId: string | undefined\n private conversationId: string | undefined\n private initialized = false\n\n private extractSessionId(raw: IOperationResult\u003Cunknown>): string | undefined {\n const container = raw as unknown as Record\u003Cstring, unknown>\n const dataObj =\n raw.data && typeof raw.data === 'object' ? 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calendar, documents)",{"type":42,"tag":107,"props":8898,"children":8899},{},[8900],{"type":51,"value":8901},"Return structured or unstructured output as needed",{"type":42,"tag":84,"props":8903,"children":8905},{"id":8904},"why-this-pattern-is-required",[8906],{"type":51,"value":8907},"Why This Pattern is Required",{"type":42,"tag":43,"props":8909,"children":8910},{},[8911,8916],{"type":42,"tag":47,"props":8912,"children":8913},{},[8914],{"type":51,"value":8915},"Work IQ uses MCP (Model Context Protocol)",{"type":51,"value":8917},", a stateful protocol that requires:",{"type":42,"tag":8919,"props":8920,"children":8921},"ol",{},[8922,8932,8942,8952,8962,8972],{"type":42,"tag":107,"props":8923,"children":8924},{},[8925,8930],{"type":42,"tag":47,"props":8926,"children":8927},{},[8928],{"type":51,"value":8929},"Session initialization",{"type":51,"value":8931}," before first call (handshake to exchange capabilities)",{"type":42,"tag":107,"props":8933,"children":8934},{},[8935,8940],{"type":42,"tag":47,"props":8936,"children":8937},{},[8938],{"type":51,"value":8939},"Session ID tracking",{"type":51,"value":8941}," across all requests",{"type":42,"tag":107,"props":8943,"children":8944},{},[8945,8950],{"type":42,"tag":47,"props":8946,"children":8947},{},[8948],{"type":51,"value":8949},"Proper JSON-RPC ID sequencing",{"type":51,"value":8951}," (each request must have a unique numeric ID)",{"type":42,"tag":107,"props":8953,"children":8954},{},[8955,8960],{"type":42,"tag":47,"props":8956,"children":8957},{},[8958],{"type":51,"value":8959},"Multi-turn conversation support",{"type":51,"value":8961}," with conversation ID persistence",{"type":42,"tag":107,"props":8963,"children":8964},{},[8965,8970],{"type":42,"tag":47,"props":8966,"children":8967},{},[8968],{"type":51,"value":8969},"Complex response parsing",{"type":51,"value":8971}," (nested JSON-RPC + optional streaming)",{"type":42,"tag":107,"props":8973,"children":8974},{},[8975,8980],{"type":42,"tag":47,"props":8976,"children":8977},{},[8978],{"type":51,"value":8979},"Automatic error recovery",{"type":51,"value":8981}," on session timeouts",{"type":42,"tag":43,"props":8983,"children":8984},{},[8985,8987,8992],{"type":51,"value":8986},"The ",{"type":42,"tag":75,"props":8988,"children":8990},{"className":8989},[],[8991],{"type":51,"value":173},{"type":51,"value":8993}," class handles all of this. Attempting to bypass it (using random session IDs, hardcoded IDs, or direct API calls) will result in \"Session not found\" errors and failed integrations.",{"type":42,"tag":8995,"props":8996,"children":8997},"style",{},[8998],{"type":51,"value":8999},"html .light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html.light .shiki span {color: var(--shiki-light);background: var(--shiki-light-bg);font-style: var(--shiki-light-font-style);font-weight: var(--shiki-light-font-weight);text-decoration: var(--shiki-light-text-decoration);}html .default .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .shiki span {color: var(--shiki-default);background: var(--shiki-default-bg);font-style: var(--shiki-default-font-style);font-weight: var(--shiki-default-font-weight);text-decoration: var(--shiki-default-text-decoration);}html .dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}html.dark .shiki span {color: var(--shiki-dark);background: var(--shiki-dark-bg);font-style: var(--shiki-dark-font-style);font-weight: var(--shiki-dark-font-weight);text-decoration: var(--shiki-dark-text-decoration);}",{"items":9001,"total":388},[9002,9016,9031,9038,9049,9061],{"slug":9003,"name":9003,"fn":9004,"description":9005,"org":9006,"tags":9007,"stars":23,"repoUrl":24,"updatedAt":9015},"add-azuredevops","integrate Azure DevOps into Microsoft Apps","Adds Azure DevOps by delegating to `\u002Fadd-connector` with `api-id=shared_visualstudioteamservices` and action mode. Use when adding Azure DevOps integration.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9008,9011,9014],{"name":9009,"slug":9010,"type":15},"Azure DevOps","azure-devops",{"name":9012,"slug":9013,"type":15},"Integrations","integrations",{"name":9,"slug":8,"type":15},"2026-07-07T06:53:11.295258",{"slug":9017,"name":9017,"fn":9018,"description":9019,"org":9020,"tags":9021,"stars":23,"repoUrl":24,"updatedAt":9030},"add-office365","integrate Office 365 Outlook","Adds Office 365 Outlook by delegating to `\u002Fadd-connector` with `api-id=shared_office365` and action mode. Use when integrating Outlook mail\u002Fcalendar.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9022,9023,9024,9027],{"name":9,"slug":8,"type":15},{"name":17,"slug":18,"type":15},{"name":9025,"slug":9026,"type":15},"Outlook Calendar","outlook-calendar",{"name":9028,"slug":9029,"type":15},"Outlook Email","outlook-email","2026-07-03T16:31:36.717786",{"slug":4,"name":4,"fn":5,"description":6,"org":9032,"tags":9033,"stars":23,"repoUrl":24,"updatedAt":25},{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9034,9035,9036,9037],{"name":13,"slug":14,"type":15},{"name":21,"slug":22,"type":15},{"name":9,"slug":8,"type":15},{"name":17,"slug":18,"type":15},{"slug":9039,"name":9039,"fn":9040,"description":9041,"org":9042,"tags":9043,"stars":23,"repoUrl":24,"updatedAt":9048},"delete-app","delete Microsoft Apps","Deletes a Microsoft App via `ms app delete`. Use when the user asks to delete an app; always require explicit confirmation.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9044,9045],{"name":9,"slug":8,"type":15},{"name":9046,"slug":9047,"type":15},"Operations","operations","2026-07-07T06:53:08.459223",{"slug":9050,"name":9050,"fn":9051,"description":9052,"org":9053,"tags":9054,"stars":23,"repoUrl":24,"updatedAt":9060},"list-apps","discover Microsoft Apps in the environment","Discovers Microsoft Apps in the active environment via `ms app list --json` and optional `ms app show --json`. Use when listing or locating apps.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9055,9058,9059],{"name":9056,"slug":9057,"type":15},"CLI","cli",{"name":9,"slug":8,"type":15},{"name":9046,"slug":9047,"type":15},"2026-07-03T16:31:37.983568",{"slug":9062,"name":9062,"fn":9063,"description":9064,"org":9065,"tags":9066,"stars":23,"repoUrl":24,"updatedAt":9072},"list-connectors","discover Microsoft App connectors and data sources","Lists connectors reachable in the active environment and the connection-bound data sources already wired into a Microsoft App. Use when discovering connectors and their operations before adding data sources.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9067,9070,9071],{"name":9068,"slug":9069,"type":15},"API Development","api-development",{"name":9012,"slug":9013,"type":15},{"name":9,"slug":8,"type":15},"2026-07-07T06:53:09.758008",{"items":9074,"total":9266},[9075,9097,9118,9139,9154,9171,9182,9193,9208,9223,9242,9254],{"slug":9076,"name":9076,"fn":9077,"description":9078,"org":9079,"tags":9080,"stars":9094,"repoUrl":9095,"updatedAt":9096},"rushstack-best-practices","manage Rush monorepos with best practices","Provides best practices and guidance for working with Rush monorepos. Use when the user is working in a Rush-based repository, asks about Rush commands (install, update, build, rebuild), needs help with project selection, dependency management, build caching, subspace configuration, or troubleshooting Rush-specific issues.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9081,9084,9087,9088,9091],{"name":9082,"slug":9083,"type":15},"Engineering","engineering",{"name":9085,"slug":9086,"type":15},"Local Development","local-development",{"name":9,"slug":8,"type":15},{"name":9089,"slug":9090,"type":15},"Project Management","project-management",{"name":9092,"slug":9093,"type":15},"Rush","rush",6484,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Frushstack","2026-04-06T18:34:44.965032",{"slug":9098,"name":9098,"fn":9099,"description":9100,"org":9101,"tags":9102,"stars":9115,"repoUrl":9116,"updatedAt":9117},"azure-ai-agents-persistent-dotnet","build AI agents with Azure .NET SDK","Azure AI Agents Persistent SDK for .NET. Low-level SDK for creating and managing AI agents with threads, messages, runs, and tools. Use for agent CRUD, conversation threads, streaming responses, function calling, file search, and code interpreter. Triggers: \"PersistentAgentsClient\", \"persistent agents\", \"agent threads\", \"agent runs\", \"streaming agents\", \"function calling agents .NET\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9103,9106,9109,9112],{"name":9104,"slug":9105,"type":15},".NET","net",{"name":9107,"slug":9108,"type":15},"Agents","agents",{"name":9110,"slug":9111,"type":15},"Azure","azure",{"name":9113,"slug":9114,"type":15},"LLM","llm",2804,"https:\u002F\u002Fgithub.com\u002Fmicrosoft\u002Fskills","2026-07-03T16:32:10.297433",{"slug":9119,"name":9119,"fn":9120,"description":9121,"org":9122,"tags":9123,"stars":9115,"repoUrl":9116,"updatedAt":9138},"azure-ai-anomalydetector-java","build anomaly detection applications with Java","Build anomaly detection applications with Azure AI Anomaly Detector SDK for Java. Use when implementing univariate\u002Fmultivariate anomaly detection, time-series analysis, or AI-powered monitoring.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9124,9127,9128,9131,9134,9135],{"name":9125,"slug":9126,"type":15},"Analytics","analytics",{"name":9110,"slug":9111,"type":15},{"name":9129,"slug":9130,"type":15},"Data Analysis","data-analysis",{"name":9132,"slug":9133,"type":15},"Java","java",{"name":9,"slug":8,"type":15},{"name":9136,"slug":9137,"type":15},"Monitoring","monitoring","2026-05-13T06:14:16.261754",{"slug":9140,"name":9140,"fn":9141,"description":9142,"org":9143,"tags":9144,"stars":9115,"repoUrl":9116,"updatedAt":9153},"azure-ai-contentsafety-java","build content moderation applications with Azure AI","Build content moderation applications with Azure AI Content Safety SDK for Java. Use when implementing text\u002Fimage analysis, blocklist management, or harm detection for hate, violence, sexual content, and self-harm.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9145,9148,9149,9150],{"name":9146,"slug":9147,"type":15},"AI Infrastructure","ai-infrastructure",{"name":9110,"slug":9111,"type":15},{"name":9132,"slug":9133,"type":15},{"name":9151,"slug":9152,"type":15},"Security","security","2026-07-07T06:53:31.293235",{"slug":9155,"name":9155,"fn":9156,"description":9157,"org":9158,"tags":9159,"stars":9115,"repoUrl":9116,"updatedAt":9170},"azure-ai-contentsafety-py","detect harmful content with Azure AI Content Safety","Azure AI Content Safety SDK for Python. Use for detecting harmful content in text and images with multi-severity classification.\nTriggers: \"azure-ai-contentsafety\", \"ContentSafetyClient\", \"content moderation\", \"harmful content\", \"text analysis\", \"image analysis\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9160,9161,9164,9165,9166,9169],{"name":9110,"slug":9111,"type":15},{"name":9162,"slug":9163,"type":15},"Compliance","compliance",{"name":9113,"slug":9114,"type":15},{"name":9,"slug":8,"type":15},{"name":9167,"slug":9168,"type":15},"Python","python",{"name":9151,"slug":9152,"type":15},"2026-07-18T05:14:23.017504",{"slug":9172,"name":9172,"fn":9173,"description":9174,"org":9175,"tags":9176,"stars":9115,"repoUrl":9116,"updatedAt":9181},"azure-ai-language-conversations-py","implement conversational language understanding with Python","Implement Conversational Language Understanding (CLU) using the azure-ai-language-conversations Python SDK. Use when working with ConversationAnalysisClient to analyze conversation intent and entities, building NLP features, or integrating language understanding into applications.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9177,9178,9179,9180],{"name":9125,"slug":9126,"type":15},{"name":9110,"slug":9111,"type":15},{"name":9113,"slug":9114,"type":15},{"name":9167,"slug":9168,"type":15},"2026-07-31T05:54:29.068751",{"slug":9183,"name":9183,"fn":9184,"description":9185,"org":9186,"tags":9187,"stars":9115,"repoUrl":9116,"updatedAt":9192},"azure-ai-translation-text-py","translate text using Azure AI services","Azure AI Text Translation SDK for real-time text translation, transliteration, language detection, and dictionary lookup. Use for translating text content in applications.\nTriggers: \"text translation\", \"translator\", \"translate text\", \"transliterate\", \"TextTranslationClient\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9188,9189,9190,9191],{"name":9068,"slug":9069,"type":15},{"name":9110,"slug":9111,"type":15},{"name":9,"slug":8,"type":15},{"name":9167,"slug":9168,"type":15},"2026-07-18T05:14:16.988376",{"slug":9194,"name":9194,"fn":9195,"description":9196,"org":9197,"tags":9198,"stars":9115,"repoUrl":9116,"updatedAt":9207},"azure-ai-vision-imageanalysis-py","analyze images with Azure AI Vision","Azure AI Vision Image Analysis SDK for captions, tags, objects, OCR, people detection, and smart cropping. Use for computer vision and image understanding tasks.\nTriggers: \"image analysis\", \"computer vision\", \"OCR\", \"object detection\", \"ImageAnalysisClient\", \"image caption\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9199,9200,9203,9206],{"name":9110,"slug":9111,"type":15},{"name":9201,"slug":9202,"type":15},"Computer Vision","computer-vision",{"name":9204,"slug":9205,"type":15},"Images","images",{"name":9167,"slug":9168,"type":15},"2026-07-18T05:14:18.007737",{"slug":9209,"name":9209,"fn":9210,"description":9211,"org":9212,"tags":9213,"stars":9115,"repoUrl":9116,"updatedAt":9222},"azure-appconfiguration-java","manage configuration with Azure App Configuration","Azure App Configuration SDK for Java. Centralized application configuration management with key-value settings, feature flags, and snapshots.\nTriggers: \"ConfigurationClient java\", \"app configuration java\", \"feature flag java\", \"configuration setting java\", \"azure config java\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9214,9215,9218,9221],{"name":9110,"slug":9111,"type":15},{"name":9216,"slug":9217,"type":15},"Configuration","configuration",{"name":9219,"slug":9220,"type":15},"Feature Flags","feature-flags",{"name":9132,"slug":9133,"type":15},"2026-07-03T16:32:01.278468",{"slug":9224,"name":9224,"fn":9225,"description":9226,"org":9227,"tags":9228,"stars":9115,"repoUrl":9116,"updatedAt":9241},"azure-cosmos-rust","build applications with Azure Cosmos DB","Azure Cosmos DB library for Rust (NoSQL API). Document CRUD, containers, and globally distributed data.\nTriggers: \"cosmos db rust\", \"CosmosClient rust\", \"document crud rust\", \"NoSQL rust\", \"partition key rust\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9229,9232,9235,9238],{"name":9230,"slug":9231,"type":15},"Cosmos DB","cosmos-db",{"name":9233,"slug":9234,"type":15},"Database","database",{"name":9236,"slug":9237,"type":15},"NoSQL","nosql",{"name":9239,"slug":9240,"type":15},"Rust","rust","2026-07-31T05:54:27.021432",{"slug":9243,"name":9243,"fn":9225,"description":9244,"org":9245,"tags":9246,"stars":9115,"repoUrl":9116,"updatedAt":9253},"azure-cosmos-ts","Azure Cosmos DB JavaScript\u002FTypeScript SDK (@azure\u002Fcosmos) for data plane operations. Use for CRUD operations on documents, queries, bulk operations, and container management. Triggers: \"Cosmos DB\", \"@azure\u002Fcosmos\", \"CosmosClient\", \"document CRUD\", \"NoSQL queries\", \"bulk operations\", \"partition key\", \"container.items\".\n",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9247,9248,9249,9250,9251],{"name":9230,"slug":9231,"type":15},{"name":9233,"slug":9234,"type":15},{"name":9,"slug":8,"type":15},{"name":9236,"slug":9237,"type":15},{"name":9252,"slug":212,"type":15},"TypeScript","2026-07-03T16:31:19.368382",{"slug":9255,"name":9255,"fn":9256,"description":9257,"org":9258,"tags":9259,"stars":9115,"repoUrl":9116,"updatedAt":9265},"azure-data-tables-java","build table storage applications with Java","Build table storage applications with Azure Tables SDK for Java. Use when working with Azure Table Storage or Cosmos DB Table API for NoSQL key-value data, schemaless storage, or structured data at scale.",{"slug":8,"name":9,"logoUrl":10,"githubOrg":8},[9260,9261,9262,9263,9264],{"name":9110,"slug":9111,"type":15},{"name":9230,"slug":9231,"type":15},{"name":9233,"slug":9234,"type":15},{"name":9132,"slug":9133,"type":15},{"name":9236,"slug":9237,"type":15},"2026-05-13T06:14:17.582229",267]