MCP Agent Tracker

#!/usr/bin/env python3 """ 🔍 Diagnostic Script: Check Goals Flow and Updates """ def diagnose_goals_flow(): """Diagnose why the goals flow is broken""" print("🔍 DIAGNOSING GOALS FLOW AND UPDATES") print("=" * 60) try: # Test 1: Check if prompt generator is working print("1️⃣ Testing prompt generator availability...") from prompt_generator import PromptGenerator generator = PromptGenerator() print("✅ PromptGenerator available") # Test 2: Check context gathering print("\n2️⃣ Testing context gathering...") try: context = generator._gather_context_data("test goals flow", "smart") print("✅ Context gathering successful") print(f"📋 Context type: {type(context)}") # Check specific fields print(f"💬 Conversation summary: {hasattr(context, 'conversation_summary')}") print(f"📝 Action history: {hasattr(context, 'action_history')}") print(f"🎯 Project plans: {hasattr(context, 'project_plans')}") if hasattr(context, 'project_plans'): print(f"🎯 Project plans content: {context.project_plans[:100]}...") else: print("❌ Project plans field missing!") except Exception as e: print(f"❌ Context gathering failed: {e}") return # Test 3: Check optimized prompt generator print("\n3️⃣ Testing optimized prompt generator...") try: from optimized_prompt_generator import OptimizedPromptGenerator opt_generator = OptimizedPromptGenerator() print("✅ OptimizedPromptGenerator available") # Test context conversion context_dict = opt_generator._context_to_dict(context) print(f"✅ Context conversion successful") print(f"📋 Available keys: {list(context_dict.keys())}") print(f"🎯 Project plans in dict: {'project_plans' in context_dict}") except Exception as e: print(f"❌ Optimized prompt generator failed: {e}") return # Test 4: Check intent classification print("\n4️⃣ Testing intent classification...") try: if opt_generator.intent_selector: relevant_context, intent_analysis = opt_generator.intent_selector.select_relevant_context( "test goals flow and updates", context_dict ) print(f"✅ Intent classification successful") print(f"🎯 Intent: {intent_analysis.primary_intent.value}") print(f"📋 Context requirements: {intent_analysis.context_requirements}") print(f"🔧 Selected context: {list(relevant_context.keys())}") print(f"🎯 Project plans in selected: {'project_plans' in relevant_context}") else: print("⚠️ Intent selector not available") except Exception as e: print(f"❌ Intent classification failed: {e}") # Test 5: Check conversation context formatting print("\n5️⃣ Testing conversation context formatting...") try: conversation_context = opt_generator._format_phase1_conversation_context(context_dict) print(f"✅ Conversation context formatting successful") print(f"📋 Result length: {len(conversation_context)}") print(f"💬 Contains context: {'💬 CONTEXT:' in conversation_context}") print(f"📝 Contains recent: {'📝 RECENT:' in conversation_context}") print(f"🎯 Contains goals: {'🎯 GOALS:' in conversation_context}") print(f"📋 Formatted result:\n{conversation_context}") except Exception as e: print(f"❌ Conversation context formatting failed: {e}") # Test 6: Check essential context safeguard print("\n6️⃣ Testing essential context safeguard...") try: # Create a filtered context that's missing some sections filtered_context = {'user_preferences': 'test', 'agent_metadata': 'test'} safeguarded_context = opt_generator._ensure_essential_context(filtered_context, context_dict) print(f"✅ Essential context safeguard successful") print(f"📋 Safeguarded keys: {list(safeguarded_context.keys())}") print(f"🎯 Project plans safeguarded: {'project_plans' in safeguarded_context}") except Exception as e: print(f"❌ Essential context safeguard failed: {e}") print("\n" + "=" * 60) print("🔍 DIAGNOSIS COMPLETE") # Final assessment if '🎯 GOALS:' in conversation_context: print("🎉 SUCCESS: Goals flow is working!") else: print("❌ FAILURE: Goals flow is broken!") print("🔍 Check the diagnostic output above for issues") except Exception as e: print(f"❌ Error during diagnosis: {e}") import traceback traceback.print_exc() if __name__ == "__main__": diagnose_goals_flow()