feat(web): apply chat preferences to agent system prompt

Threads the signed-in user's chat preferences through the agent so the
final answer is biased by their saved settings.

- `agent.ts` exports a new `ResolvedChatUserPreferences` interface and
  accepts it as an optional field on `CreateMessageStreamResponseProps`,
  `AgentOptions`, and `createPrompt`. When present,
  `renderChatPreferencesPromptBlock()` produces a `<user_preferences>`
  block that is appended after `</answer_instructions>` in the system
  prompt, where the model sees it last. When absent, no block is
  emitted and behavior is identical to today.

- `api/(server)/chat/route.ts` loads `chatPreferences` and
  `chatCustomInstructions` from the user's row (only when
  `user` is defined, which excludes anonymous chats), parses the JSONB
  through `chatPreferencesSchema` defensively, and passes the result to
  `createMessageStream`. The query is `select`-narrowed to the two
  columns the agent actually needs.

- `features/mcp/askCodebase.ts` does not load preferences. MCP has no
  user-settings surface yet; the call site has an explicit comment
  pointing back to #1242 so a future maintainer knows it was a
  conscious omission rather than an oversight.

Soft-bias framing in the prompt block is intentional: preferences are
described as guidance that shapes the final answer and must never
override correctness or the explicit user message. This keeps existing
agent behavior intact even when preferences are aggressive (e.g.
"one-paragraph summary" + "describe code only" together).

Refs #1242

Co-authored-by: Cursor <cursoragent@cursor.com>

Author: adam.wilson

packages/web/src/app/api/(server)/chat/route.ts

@@ -1,8 +1,9 @@
 import { sew } from "@/middleware/sew";
-import { createMessageStream } from "@/features/chat/agent";
+import { createMessageStream, ResolvedChatUserPreferences } from "@/features/chat/agent";
 import { additionalChatRequestParamsSchema } from "@/features/chat/types";
 import { getLanguageModelKey } from "@/features/chat/utils";
 import { getAISDKLanguageModelAndOptions, getConfiguredLanguageModels, isOwnerOfChat, updateChatMessages } from "@/features/chat/utils.server";
+import { chatPreferencesSchema } from "@/features/chat/userPreferences";
 import { apiHandler } from "@/lib/apiHandler";
 import { ErrorCode } from "@/lib/errorCodes";
 import { captureEvent } from "@/lib/posthog";
@@ -93,6 +94,27 @@ export const POST = apiHandler(async (req: NextRequest) => {
 
             const source = req.headers.get('X-Sourcebot-Client-Source') ?? undefined;
 
+            // Load the user's chat-style preferences. Anonymous users skip this
+            // entirely so the agent uses default behavior with no
+            // `<user_preferences>` block in the system prompt.
+            let userPreferences: ResolvedChatUserPreferences | undefined;
+            if (user) {
+                const row = await prisma.user.findUnique({
+                    where: { id: user.id },
+                    select: {
+                        chatPreferences: true,
+                        chatCustomInstructions: true,
+                    },
+                });
+                if (row) {
+                    const parsed = chatPreferencesSchema.safeParse(row.chatPreferences);
+                    userPreferences = {
+                        preferences: parsed.success ? parsed.data : {},
+                        customInstructions: row.chatCustomInstructions,
+                    };
+                }
+            }
+
             await captureEvent('ask_message_sent', {
                 chatId: id,
                 messageCount: messages.length,
@@ -112,6 +134,7 @@ export const POST = apiHandler(async (req: NextRequest) => {
                 modelName: languageModelConfig.displayName ?? languageModelConfig.model,
                 modelProviderOptions: providerOptions,
                 modelTemperature: temperature,
+                userPreferences,
                 onFinish: async ({ messages }) => {
                     await updateChatMessages({ chatId: id, messages, prisma });
                 },

packages/web/src/features/chat/agent.ts

@@ -17,6 +17,20 @@ import { ANSWER_TAG, FILE_REFERENCE_PREFIX } from "./constants";
 import { Source } from "./types";
 import { addLineNumbers, fileReferenceToString } from "./utils";
 import { createTools } from "./tools";
+import {
+    ChatPreferences,
+    renderChatPreferencesPromptBlock,
+} from "./userPreferences";
+
+/**
+ * Resolved chat-style preferences for the user who is sending this message.
+ * `undefined` means no signed-in user (or no preferences loaded) and the
+ * agent uses default behavior with no `<user_preferences>` block.
+ */
+export interface ResolvedChatUserPreferences {
+    preferences: ChatPreferences;
+    customInstructions: string | null;
+}
 
 const dedent = _dedent.withOptions({ alignValues: true });
 
@@ -43,6 +57,12 @@ interface CreateMessageStreamResponseProps {
     modelProviderOptions?: Record<string, Record<string, JSONValue>>;
     modelTemperature?: number;
     metadata?: Partial<SBChatMessageMetadata>;
+    /**
+     * Per-user response-style preferences. When omitted (e.g. anonymous user
+     * or MCP caller), the agent uses default behavior with no
+     * `<user_preferences>` block injected into the system prompt.
+     */
+    userPreferences?: ResolvedChatUserPreferences;
 }
 
 export const createMessageStream = async ({
@@ -56,6 +76,7 @@ export const createMessageStream = async ({
     modelTemperature,
     onFinish,
     onError,
+    userPreferences,
 }: CreateMessageStreamResponseProps) => {
     const latestMessage = messages[messages.length - 1];
     const sources = latestMessage.parts
@@ -109,6 +130,7 @@ export const createMessageStream = async ({
                 },
                 traceId,
                 chatId,
+                userPreferences,
             });
 
             await mergeStreamAsync(researchStream, writer, {
@@ -154,6 +176,7 @@ interface AgentOptions {
     onWriteSource: (source: Source) => void;
     traceId: string;
     chatId: string;
+    userPreferences?: ResolvedChatUserPreferences;
 }
 
 const createAgentStream = async ({
@@ -166,6 +189,7 @@ const createAgentStream = async ({
     onWriteSource,
     traceId,
     chatId,
+    userPreferences,
 }: AgentOptions) => {
     // For every file source, resolve the source code so that we can include it in the system prompt.
     const fileSources = inputSources.filter((source) => source.type === 'file');
@@ -195,6 +219,7 @@ const createAgentStream = async ({
     const systemPrompt = createPrompt({
         repos: selectedRepos,
         files: resolvedFileSources,
+        userPreferences,
     });
 
     const stream = streamText({
@@ -234,6 +259,7 @@ const createAgentStream = async ({
 const createPrompt = ({
     files,
     repos,
+    userPreferences,
 }: {
     files?: {
         path: string;
@@ -243,7 +269,12 @@ const createPrompt = ({
         revision: string;
     }[],
     repos: string[],
+    userPreferences?: ResolvedChatUserPreferences,
 }) => {
+    const preferencesBlock = userPreferences
+        ? renderChatPreferencesPromptBlock(userPreferences)
+        : null;
+
     return dedent`
     You are a powerful agentic AI code assistant built into Sourcebot, the world's best code-intelligence platform. Your job is to help developers understand and navigate their large codebases.
 
@@ -317,6 +348,8 @@ const createPrompt = ({
     Authentication in Sourcebot is built on NextAuth.js with a session-based approach using JWT tokens and Prisma as the database adapter ${fileReferenceToString({ repo: 'github.com/sourcebot-dev/sourcebot', path: 'auth.ts', range: { startLine: 135, endLine: 140 } })}. The system supports multiple authentication providers and implements organization-based authorization with role-defined permissions.
     \`\`\`
     </answer_instructions>
+
+    ${preferencesBlock ?? ''}
     `
 }
 

packages/web/src/features/mcp/askCodebase.ts

@@ -148,6 +148,10 @@ export const askCodebase = (params: AskCodebaseParams): Promise<AskCodebaseResul
                 } : {}),
             });
 
+            // `userPreferences` is intentionally omitted here. Chat preferences
+            // are a web-app UI feature and there is no MCP-side surface to set
+            // or override them today. Revisit if/when MCP grows a user-settings
+            // story (tracked in #1242).
             const stream = await createMessageStream({
                 chatId: chat.id,
                 messages: [userMessage],