Add agentRoutingPrompt for full agent routing support

🤖 Generated with [Claude Code](https://claude.com/claude-code)

Co-Authored-By: Claude <[email protected]>

Author: NiallJoeMaher

app/(chat)/api/chat/route.ts

@@ -7,15 +7,15 @@ import {
   stepCountIs,
   streamText,
 } from "ai";
+import { unstable_cache as cache } from "next/cache";
+import type { ModelCatalog } from "tokenlens/core";
 import {
   createAnalystAgent,
   createPlannerAgent,
   createQuizMasterAgent,
   createTutorAgent,
 } from "@/lib/ai/agents";
 import { getWeather } from "@/lib/ai/tools/get-weather";
-import { unstable_cache as cache } from "next/cache";
-import type { ModelCatalog } from "tokenlens/core";
 
 // Type definition for resumable stream context (feature currently disabled - requires Redis)
 type ResumableStreamContext = {

lib/ai/prompts.ts

@@ -4,6 +4,39 @@ import type { ArtifactKind } from "@/components/artifact";
 export const regularPrompt =
   "You are a friendly study buddy assistant! Keep your responses concise and helpful.";
 
+export const agentRoutingPrompt = `
+You are a Study Buddy with specialized agents available as tools. Choose the right agent based on what the user needs:
+
+**tutor** - Explain concepts with examples and analogies
+Use for: "explain", "teach me", "how does X work", "what is X", understanding concepts
+
+**quizMaster** - Create quizzes and practice questions (creates interactive flashcard artifact)
+Use for: "quiz me", "test my knowledge", "practice questions", "assessment"
+
+**planner** - Create study plans and learning roadmaps (creates interactive study-plan artifact)
+Use for: "study plan", "learning roadmap", "how should I learn", "schedule"
+
+**analyst** - Analyze content and extract key insights
+Use for: "summarize", "key points", "analyze this", "what's important"
+
+IMPORTANT ROUTING RULES:
+1. Match user intent to the most appropriate agent
+2. If the request doesn't clearly match an agent, respond conversationally
+3. After using an agent, suggest related follow-ups (e.g., after explaining, offer to quiz)
+4. You can chain agents - explain first, then offer to create a study plan
+
+CRITICAL: Agents (quizMaster, planner) create their own artifacts automatically. After using these agents:
+- Do NOT call createDocument - the artifact is already created
+- Do NOT try to display or reformat the agent's output
+- Simply acknowledge the artifact was created and offer follow-up suggestions
+
+Example flows:
+- "Explain machine learning" → use tutor
+- "Quiz me on what we just discussed" → use quizMaster (creates flashcard artifact automatically)
+- "Create a study plan for learning Python" → use planner (creates study-plan artifact automatically)
+- "Summarize this article" → use analyst
+`;
+
 export type RequestHints = {
   latitude: Geo["latitude"];
   longitude: Geo["longitude"];
@@ -28,7 +61,11 @@ export const systemPrompt = ({
 }) => {
   const requestPrompt = getRequestPromptFromHints(requestHints);
 
-  return `${regularPrompt}\n\n${requestPrompt}`;
+  if (selectedChatModel === "chat-model-reasoning") {
+    return `${regularPrompt}\n\n${requestPrompt}`;
+  }
+
+  return `${regularPrompt}\n\n${agentRoutingPrompt}\n\n${requestPrompt}`;
 };
 
 export const codePrompt = `