Refactor project templates to remove the Example Agent and update related documentation. Updated the copilot behaviour aswell.

apps/rowboat/app/lib/project_templates.ts

@@ -18,21 +18,8 @@ function loadTemplatesFromFiles(): { [key: string]: z.infer<typeof WorkflowTempl
     templates['default'] = {
         name: 'Blank Template',
         description: 'A blank canvas to build your agents.',
-        startAgent: "Example Agent",
-        agents: [
-            {
-                name: "Example Agent",
-                type: "conversation",
-                description: "An example agent",
-                instructions: "## 🧑‍ Role:\nYou are an helpful customer support assistant\n\n---\n## ⚙️ Steps to Follow:\n1. Ask the user what they would like help with\n2. Ask the user for their email address and let them know someone will contact them soon.\n\n---\n## 🎯 Scope:\n✅ In Scope:\n- Asking the user their issue\n- Getting their email\n\n❌ Out of Scope:\n- Questions unrelated to customer support\n- If a question is out of scope, politely inform the user and avoid providing an answer.\n\n---\n## 📋 Guidelines:\n✔️ Dos:\n- ask user their issue\n\n❌ Don'ts:\n- don't ask user any other detail than email",
-                model: DEFAULT_MODEL,
-                toggleAble: true,
-                ragReturnType: "chunks",
-                ragK: 3,
-                controlType: "retain",
-                outputVisibility: "user_facing",
-            },
-        ],
+        startAgent: "",
+        agents: [],
         prompts: [],
         tools: [],
     };

apps/rowboat/src/application/lib/copilot/current_workflow.ts

@@ -7,7 +7,7 @@ The design of the multi-agent system is represented by the following JSON schema
 {workflow_schema}
 \`\`\`
 
-If the workflow has an 'Example Agent' as the main agent, it means the user is yet to create the main agent. You should treat the user's first request as a request to plan out and create the multi-agent system.
+If the workflow has no agents or an empty startAgent, it means the user is yet to create their first agent. You should treat the user's first request as a request to plan out and create the multi-agent system.
 
 ---
 `;

apps/rowboat/src/application/lib/copilot/example_multi_agent_1.ts

@@ -116,14 +116,14 @@ I'll add the suggested tools for Google Calendar, web search, and email:
 ### 2. Create Agents
 
 #### a. Hub Agent (Meeting Assistant Hub)
-I'll edit the Example Agent to become the hub agent:
+I'll create the hub agent:
 
 \`\`\`copilot_change
 // action: edit
 // config_type: agent
-// name: Example Agent
+// name: Meeting Assistant Hub
 {
-  "change_description": "Transformed Example Agent into the main hub agent orchestrating the meeting summary workflow.",
+  "change_description": "Created the main hub agent orchestrating the meeting summary workflow.",
   "config_changes": {
     "name": "Meeting Assistant Hub",
     "type": "conversation",
@@ -241,7 +241,7 @@ searchRelevantTools output:
 I'll make the following changes to your workflow:
 
 1. Add the "Get document by id" tool for retrieving the content of a Google Doc.
-2. Replace the Example Agent with a single user-facing agent that:
+2. Create a single user-facing agent that:
    * Asks the user for the Google Doc ID and their question.
    * Uses the tool to fetch the document content.
    * Answers the user's question based only on the content of the fetched Google Doc (no RAG or external search).
@@ -277,14 +277,14 @@ I'm adding the "Get document by id" tool to fetch the content of a Google Doc by
 }
 \`\`\`
 
-I'm replacing the Example Agent with a user-facing agent that fetches a Google Doc by ID and answers questions based on its content:
+I'm creating a user-facing agent that fetches a Google Doc by ID and answers questions based on its content:
 
 \`\`\`copilot_change
 // action: edit
 // config_type: agent
-// name: Example Agent
+// name: Meeting Assistant Hub
 {
-  "change_description": "Replaced Example Agent with a user-facing agent that fetches a Google Doc by ID and answers user questions based only on its content.",
+  "change_description": "Created a user-facing agent that fetches a Google Doc by ID and answers user questions based only on its content.",
   "config_changes": {
     "name": "Google Doc QnA Assistant",
     "type": "conversation",