sequential thinking tie off the request.

packages/ai/src/steps/analyst-agent-steps/extract-values-step/extract-values-search-step.int.test.ts

@@ -343,4 +343,51 @@ describe('extract-values-search-step integration', () => {
       expect(Array.isArray(result.values)).toBe(true);
     });
   });
+
+  it('should not create valuesMessage with empty content when search returns no results', async () => {
+    const messages: ModelMessage[] = [
+      { role: 'user', content: 'Show me sales for Red Bull' },
+    ];
+    
+    // Test with a dataSourceId that would trigger search but return empty results
+    const params = {
+      messages,
+      dataSourceId: 'test-datasource-id',
+    };
+
+    const result = await runExtractValuesAndSearchStep(params);
+
+    expect(result).toBeDefined();
+    expect(result.values).toBeDefined();
+    
+    // If valuesMessage exists, it should have non-empty content
+    if (result.valuesMessage) {
+      expect(result.valuesMessage.content).toBeTruthy();
+      expect(typeof result.valuesMessage.content).toBe('string');
+      expect((result.valuesMessage.content as string).length).toBeGreaterThan(0);
+    }
+  });
+
+  it('should not create valuesMessage when extracted values exist but search results are empty', async () => {
+    const messages: ModelMessage[] = [
+      { role: 'user', content: 'Show me Nike and Adidas products' },
+    ];
+    
+    const params = {
+      messages,
+      dataSourceId: 'test-datasource-id', 
+    };
+
+    const result = await runExtractValuesAndSearchStep(params);
+
+    expect(result).toBeDefined();
+    expect(result.values).toBeDefined();
+    
+    // Verify that if we have values but no search results, valuesMessage is undefined
+    // This prevents empty string messages from being created
+    if (result.values.length > 0 && result.valuesMessage) {
+      expect(result.valuesMessage.content).toBeTruthy();
+      expect((result.valuesMessage.content as string).trim()).not.toBe('');
+    }
+  });
 });

packages/ai/src/steps/analyst-agent-steps/extract-values-step/extract-values-search-step.ts

@@ -185,7 +185,7 @@ export async function runExtractValuesAndSearchStep(
     return {
       values: extractedValues,
       valuesMessage:
-        extractedValues.length > 0
+        extractedValues.length > 0 && storedValuesResult.searchResults
           ? {
               role: 'user',
               content: storedValuesResult.searchResults,

packages/ai/src/tools/planning-thinking-tools/sequential-thinking-tool/helpers/sequential-thinking-tool-transform-helper.ts

@@ -12,14 +12,14 @@ import type { SequentialThinkingState } from '../sequential-thinking-tool';
  */
 export function createSequentialThinkingReasoningMessage(
   sequentialThinkingState: SequentialThinkingState,
-  toolCallId?: string,
+  toolCallId: string,
   status: ChatMessageReasoning_status = 'loading'
-): ChatMessageReasoningMessage_Text | null {
+): ChatMessageReasoningMessage_Text {
   // Use entry_id from state or fallback to provided toolCallId
   const id = toolCallId;
 
   if (!id) {
-    return null;
+    throw new Error('Tool call ID is required');
   }
 
   // Determine title based on status
@@ -49,11 +49,11 @@ export function createSequentialThinkingReasoningMessage(
 export function createSequentialThinkingRawLlmMessageEntry(
   sequentialThinkingState: SequentialThinkingState,
   toolCallId?: string
-): ModelMessage | null {
+): ModelMessage {
   const id = toolCallId;
 
   if (!id) {
-    return null;
+    throw new Error('Tool call ID is required');
   }
 
   // Build the input object with available state

packages/ai/src/tools/planning-thinking-tools/sequential-thinking-tool/sequential-thinking-tool-execute.ts

@@ -1,4 +1,4 @@
-import { updateMessageEntries } from '@buster/database';
+import { type UpdateMessageEntriesParams, updateMessageEntries } from '@buster/database';
 import { wrapTraced } from 'braintrust';
 import { normalizeEscapedText } from '../../../utils/streaming/escape-normalizer';
 import { createRawToolResultEntry } from '../../shared/create-raw-llm-tool-result-entry';
@@ -16,24 +16,42 @@ import {
 
 // Process sequential thinking execution
 async function processSequentialThinking(
-  toolCallId: string,
+  state: SequentialThinkingState,
-  messageId: string
+  context: SequentialThinkingContext
 ): Promise<SequentialThinkingOutput> {
   const output: SequentialThinkingOutput = {
     success: true,
   };
 
+  const entries: UpdateMessageEntriesParams = {
+    messageId: context.messageId,
+    reasoningMessages: [],
+    rawLlmMessages: [],
+  };
+
+  const reasoningEntry = createSequentialThinkingReasoningMessage(
+    state,
+    context.messageId,
+    'completed'
+  );
+  const rawLlmMessage = createSequentialThinkingRawLlmMessageEntry(state, context.messageId);
+
   const rawToolResultEntry = createRawToolResultEntry(
-    toolCallId,
+    context.messageId,
     SEQUENTIAL_THINKING_TOOL_NAME,
     output
   );
 
+  if (reasoningEntry) {
+    entries.reasoningMessages = [reasoningEntry];
+  }
+
+  if (rawLlmMessage) {
+    entries.rawLlmMessages = [rawLlmMessage, rawToolResultEntry];
+  }
+
   try {
-    await updateMessageEntries({
+    await updateMessageEntries(entries);
-      messageId,
-      rawLlmMessages: [rawToolResultEntry],
-    });
   } catch (error) {
     console.error('[sequential-thinking] Error updating message entries:', error);
   }
@@ -54,7 +72,7 @@ export function createSequentialThinkingExecute(
         throw new Error('Tool call ID is required');
       }
 
-      return await processSequentialThinking(state.toolCallId, context.messageId);
+      return await processSequentialThinking(state, context);
     },
     { name: SEQUENTIAL_THINKING_TOOL_NAME }
   );