chore(mma): Clean up mma_exec.py and robustify visual simulation mocking

scripts/mma_exec.py

@@ -10,6 +10,7 @@ import datetime
 
 LOG_FILE: str = 'logs/mma_delegation.log'
 
+
 def generate_skeleton(code: str) -> str:
  """
     Parses Python code and replaces function/method bodies with '...',
@@ -126,42 +127,9 @@ def get_dependencies(filepath: str) -> list[str]:
   print(f"Error getting dependencies for {filepath}: {e}")
   return []
 
-import os
-import subprocess
-import json
-
-# Mock Response Definitions
-MOCK_PLANNING_RESPONSE = {
- "status": "success",
- "message": "Mock response for planning task.",
- "data": {
-  "task_type": "planning",
-  "details": "Mocked plan generated."
- }
-}
-
-MOCK_GENERIC_RESPONSE = {
- "status": "success",
- "message": "Mock response from the agent.",
- "data": {
-  "task_type": "generic_mock",
-  "details": "This is a generic mock response."
- }
-}
-
-
 def execute_agent(role: str, prompt: str, docs: list[str], debug: bool = False, failure_count: int = 0) -> str:
  model = get_model_for_role(role, failure_count)
 
- # --- NEW MOCK HANDLING LOGIC ---
- if model == 'mock':
-  # The 'prompt' argument here represents the user's task/command text.
-  if "Epic Initialization" in prompt or "Sprint Planning" in prompt:
-   return json.dumps(MOCK_PLANNING_RESPONSE)
-  else:
-   return json.dumps(MOCK_GENERIC_RESPONSE)
- # --- END NEW MOCK HANDLING LOGIC ---
-
  # Advanced Context: Dependency skeletons for Tier 3
  injected_context = ""
  # Whitelist of modules that sub-agents have "unfettered" (full) access to.