mirror of
https://github.com/modelcontextprotocol/servers.git
synced 2026-02-19 11:54:58 -05:00
fix(everything): send elicitation directly from background task
Instead of waiting for the client to call tasks/result to trigger elicitation, the server now sends elicitation/create directly from the background process using sendRequest. This simplifies the flow: - Server sends elicitation proactively when clarification is needed - Client receives and handles it via existing elicitation handler - Task resumes and completes after receiving the response - Client's polling sees completed status This approach avoids requiring the client to detect input_required status and call tasks/result as a side-channel. Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>
This commit is contained in:
@@ -5,8 +5,10 @@ import {
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GetTaskResult,
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Task,
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ElicitResultSchema,
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ServerRequest,
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} from "@modelcontextprotocol/sdk/types.js";
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import { CreateTaskResult } from "@modelcontextprotocol/sdk/experimental";
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import type { AnySchema, SchemaOutput } from "@modelcontextprotocol/sdk/server/zod-compat.js";
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// Tool input schema
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const SimulateResearchQuerySchema = z.object({
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@@ -36,7 +38,6 @@ interface ResearchState {
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ambiguous: boolean;
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currentStage: number;
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clarification?: string;
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waitingForClarification: boolean;
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completed: boolean;
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result?: CallToolResult;
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}
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@@ -47,6 +48,7 @@ const researchStates = new Map<string, ResearchState>();
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/**
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* Runs the background research process.
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* Updates task status as it progresses through stages.
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* If clarification is needed, sends elicitation request directly.
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*/
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async function runResearchProcess(
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taskId: string,
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@@ -62,7 +64,12 @@ async function runResearchProcess(
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status: "completed" | "failed",
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result: CallToolResult
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) => Promise<void>;
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}
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},
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sendRequest: <U extends AnySchema>(
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request: ServerRequest,
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resultSchema: U,
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options?: { timeout?: number }
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) => Promise<SchemaOutput<U>>
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): Promise<void> {
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const state = researchStates.get(taskId);
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if (!state) return;
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@@ -79,14 +86,59 @@ async function runResearchProcess(
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// At synthesis stage (index 2), check if clarification is needed
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if (i === 2 && state.ambiguous && !state.clarification) {
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state.waitingForClarification = true;
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// Update status to show we're requesting input
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await taskStore.updateTaskStatus(
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taskId,
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"input_required",
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`Found multiple interpretations for "${state.topic}". Please clarify your intent.`
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`Found multiple interpretations for "${state.topic}". Requesting clarification...`
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);
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// Wait for clarification - the getTaskResult handler will resume this
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return;
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// Send elicitation directly and await response
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const elicitationResult = await sendRequest(
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{
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method: "elicitation/create",
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params: {
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message: `The research query "${state.topic}" could have multiple interpretations. Please clarify what you're looking for:`,
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requestedSchema: {
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type: "object",
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properties: {
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interpretation: {
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type: "string",
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title: "Clarification",
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description: "Which interpretation of the topic do you mean?",
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oneOf: getInterpretationsForTopic(state.topic),
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},
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},
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required: ["interpretation"],
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},
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},
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},
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ElicitResultSchema,
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{ timeout: 5 * 60 * 1000 /* 5 minutes */ }
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);
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// Process elicitation response
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if (
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elicitationResult.action === "accept" &&
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elicitationResult.content
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) {
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state.clarification =
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(elicitationResult.content as { interpretation?: string })
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.interpretation || "User accepted without selection";
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} else if (elicitationResult.action === "decline") {
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state.clarification = "User declined - using default interpretation";
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} else {
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state.clarification = "User cancelled - using default interpretation";
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}
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// Resume with working status
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await taskStore.updateTaskStatus(
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taskId,
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"working",
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`Received clarification: "${state.clarification}". Continuing...`
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);
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// Continue processing (no return - just keep going through the loop)
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}
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// Simulate work for this stage
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@@ -131,17 +183,18 @@ This tool demonstrates MCP's task-based execution pattern for long-running opera
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3. Status progressed: \`working\` → ${state.clarification ? `\`input_required\` → \`working\` → ` : ""}\`completed\`
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4. Client calls \`tasks/result\` → Server returns this final result
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${state.clarification ? `**input_required Flow:**
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When the query was ambiguous, the task paused with \`input_required\` status.
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The client called \`tasks/result\` prematurely, which triggered an elicitation
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request via the side-channel. After receiving clarification ("${state.clarification}"),
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the task resumed processing.
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${state.clarification ? `**Elicitation Flow:**
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When the query was ambiguous, the server sent an \`elicitation/create\` request
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directly to the client. The task status changed to \`input_required\` while
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awaiting user input. After receiving clarification ("${state.clarification}"),
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the task resumed processing and completed.
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` : ""}
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**Key Concepts:**
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- Tasks enable "call now, fetch later" patterns
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- \`statusMessage\` provides human-readable progress updates
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- Tasks have TTL (time-to-live) for automatic cleanup
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- \`pollInterval\` suggests how often to check status
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- Elicitation requests can be sent directly during task execution
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*This is a simulated research report from the Everything MCP Server.*
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`;
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@@ -178,7 +231,7 @@ export const registerSimulateResearchQueryTool = (server: McpServer) => {
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description:
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"Simulates a deep research operation that gathers, analyzes, and synthesizes information. " +
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"Demonstrates MCP task-based operations with progress through multiple stages. " +
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"If 'ambiguous' is true and client supports elicitation, pauses for clarification (input_required status).",
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"If 'ambiguous' is true and client supports elicitation, sends an elicitation request for clarification.",
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inputSchema: SimulateResearchQuerySchema,
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execution: { taskSupport: "required" },
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},
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@@ -200,20 +253,23 @@ export const registerSimulateResearchQueryTool = (server: McpServer) => {
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topic: validatedArgs.topic,
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ambiguous: validatedArgs.ambiguous && clientSupportsElicitation,
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currentStage: 0,
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waitingForClarification: false,
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completed: false,
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};
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researchStates.set(task.taskId, state);
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// Start background research (don't await - runs asynchronously)
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runResearchProcess(task.taskId, validatedArgs, extra.taskStore).catch(
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(error) => {
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console.error(`Research task ${task.taskId} failed:`, error);
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extra.taskStore
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.updateTaskStatus(task.taskId, "failed", String(error))
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.catch(console.error);
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}
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);
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// Pass sendRequest so elicitation can be sent directly from the background process
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runResearchProcess(
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task.taskId,
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validatedArgs,
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extra.taskStore,
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extra.sendRequest
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).catch((error) => {
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console.error(`Research task ${task.taskId} failed:`, error);
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extra.taskStore
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.updateTaskStatus(task.taskId, "failed", String(error))
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.catch(console.error);
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});
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return { task };
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},
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@@ -228,77 +284,11 @@ export const registerSimulateResearchQueryTool = (server: McpServer) => {
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},
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/**
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* Returns the task result, or handles input_required via elicitation side-channel.
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* Returns the task result.
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* Elicitation is now handled directly in the background process.
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*/
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getTaskResult: async (args, extra): Promise<CallToolResult> => {
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const task = await extra.taskStore.getTask(extra.taskId);
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const state = researchStates.get(extra.taskId);
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// Handle input_required - use tasks/result as side-channel for elicitation
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if (task?.status === "input_required" && state?.waitingForClarification) {
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// Send elicitation request through the side-channel
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const elicitationResult = await extra.sendRequest(
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{
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method: "elicitation/create",
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params: {
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message: `The research query "${state.topic}" could have multiple interpretations. Please clarify what you're looking for:`,
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requestedSchema: {
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type: "object",
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properties: {
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interpretation: {
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type: "string",
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title: "Clarification",
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description: "Which interpretation of the topic do you mean?",
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oneOf: getInterpretationsForTopic(state.topic),
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},
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},
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required: ["interpretation"],
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},
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},
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},
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ElicitResultSchema,
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{ timeout: 5 * 60 * 1000 /* 5 minutes */ }
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);
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// Process elicitation response
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if (
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elicitationResult.action === "accept" &&
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elicitationResult.content
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) {
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state.clarification =
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(elicitationResult.content as { interpretation?: string })
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.interpretation || "User accepted without selection";
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} else if (elicitationResult.action === "decline") {
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state.clarification = "User declined - using default interpretation";
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} else {
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state.clarification = "User cancelled - using default interpretation";
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}
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state.waitingForClarification = false;
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// Resume background processing from current stage
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runResearchProcess(extra.taskId, {
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topic: state.topic,
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ambiguous: false, // Don't ask again
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}, extra.taskStore).catch((error) => {
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console.error(`Research task ${extra.taskId} failed:`, error);
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extra.taskStore
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.updateTaskStatus(extra.taskId, "failed", String(error))
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.catch(console.error);
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});
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// Return indication that work is resuming (client should poll again)
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return {
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content: [
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{
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type: "text",
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text: `Resuming research with clarification: "${state.clarification}"`,
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},
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],
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};
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}
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// Normal case: return the stored result
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// Return the stored result
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const result = await extra.taskStore.getTaskResult(extra.taskId);
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// Clean up state
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