feat: Enhance system prompt JSON schema and clarify tool result formatting in conversational agent

src/cli/service/agent/conversational_agent_service.cc

@@ -270,7 +270,12 @@ absl::StatusOr<ChatMessage> ConversationalAgentService::SendMessage(
           }
           
           // Add tool result with a clear marker for the LLM
-          std::string marked_output = "[TOOL RESULT] " + tool_output;
+          // Format as plain text to avoid confusing the LLM with nested JSON
+          std::string marked_output = absl::StrCat(
+              "[TOOL RESULT for ", tool_call.tool_name, "]\n",
+              "The tool returned the following data:\n",
+              tool_output, "\n\n",
+              "Please provide a text_response field in your JSON to summarize this information for the user.");
           history_.push_back(
               CreateMessage(ChatMessage::Sender::kUser, marked_output));
         }

src/cli/service/ai/ollama_ai_service.cc

@@ -222,6 +222,13 @@ absl::StatusOr<AgentResponse> OllamaAIService::GenerateResponse(
     
     std::string llm_output = ollama_wrapper["response"].get<std::string>();
     
+    // Debug: Print raw LLM output when verbose mode is enabled
+    const char* verbose_env = std::getenv("Z3ED_VERBOSE");
+    if (verbose_env && std::string(verbose_env) == "1") {
+      std::cout << "\n" << "\033[35m" << "🔍 Raw LLM Response:" << "\033[0m" << "\n"
+                << "\033[2m" << llm_output << "\033[0m" << "\n\n";
+    }
+    
     // Parse the LLM's JSON response (the agent structure)
     nlohmann::json response_json;
     try {