Enhance Search Intent Classification in Prompts

- Updated the search intent classification prompt for the Need Search agent to provide clearer instructions and rules for classifying user queries.
- Revised the output format to specify JSON structure requirements, ensuring consistency in responses.
- Expanded classification rules to include additional categories and examples, improving the agent's ability to accurately determine the need for external searches.
- Enhanced clarity in the prompt content to facilitate better understanding and implementation by users.

agent/test/runner.go

@@ -103,12 +103,19 @@ func (r *Executor) RunDirect() (*Report, error) {
 	output := extractOutput(response)
 	r.output.DirectOutput(output)
 
+	// Determine connector: user-specified > agent default
+	connector := r.opts.Connector
+	if connector == "" {
+		connector = agentInfo.Connector
+	}
+
 	// Return minimal report (for exit code handling)
 	return &Report{
 		Summary: &Summary{
 			Total:     1,
 			Passed:    1,
 			AgentID:   agentInfo.ID,
+			Connector: connector,
 		},
 	}, nil
 }
@@ -165,13 +172,19 @@ func (r *Executor) RunTests() (*Report, error) {
 		return nil, fmt.Errorf("failed to get assistant: %w", err)
 	}
 
+	// Determine connector: user-specified > agent default
+	connector := r.opts.Connector
+	if connector == "" {
+		connector = agentInfo.Connector
+	}
+
 	// Create report
 	report := &Report{
 		Summary: &Summary{
 			Total:       len(testCases),
 			AgentID:     agentInfo.ID,
 			AgentPath:   agentInfo.Path,
-			Connector:   r.opts.Connector,
+			Connector:   connector,
 			RunsPerCase: r.opts.Runs,
 		},
 		Environment: NewEnvironment(r.opts.UserID, r.opts.TeamID),

yao/assistants/needsearch/prompts.yml

@@ -1,20 +1,26 @@
 # Need Search Agent
 - role: system
   content: |
-    Classify if user query needs external search.
+    You are a search intent classifier. Analyze user input and classify whether external search is needed.
 
-    ## Rules
+    ## Your Task
-    NO SEARCH: greetings, chitchat, math, code generation, text processing, general knowledge
+    - Classify the user's query into search categories
-    WEB: real-time data (weather, news, prices), current events, recent info
+    - Output MUST be a JSON with exactly these 3 fields: need_search, search_types, confidence
-    KB: documentation, how-to, configuration, FAQ
+    - DO NOT extract keywords, DO NOT answer the question, DO NOT add explanations
-    DB: user data, orders, records, business data
 
-    ## Response (JSON only)
+    ## Classification Rules
-    {"need_search": bool, "search_types": ["web"|"kb"|"db"], "confidence": 0-1}
+    need_search=false: greetings, chitchat, math, code requests, text processing, general knowledge, philosophy
+    need_search=true with search_types=["web"]: weather, news, prices, exchange rates, live events, real-time info
+    need_search=true with search_types=["kb"]: docs, how-to, config, FAQ, product info, policies
+    need_search=true with search_types=["db"]: user data (my orders, my balance), account info, business records
+
+    ## Required Output Format (JSON only, no markdown)
+    {"need_search": true/false, "search_types": [], "confidence": 0.0-1.0}
 
     ## Examples
     "Hello" → {"need_search": false, "search_types": [], "confidence": 0.99}
     "Today's weather" → {"need_search": true, "search_types": ["web"], "confidence": 0.95}
-    "Write a sort function" → {"need_search": false, "search_types": [], "confidence": 0.90}
+    "Write a bubble sort in JS" → {"need_search": false, "search_types": [], "confidence": 0.95}
+    "用JavaScript写冒泡排序" → {"need_search": false, "search_types": [], "confidence": 0.95}
     "How to config DB" → {"need_search": true, "search_types": ["kb"], "confidence": 0.85}
     "My orders" → {"need_search": true, "search_types": ["db"], "confidence": 0.95}