chore(mma): Checkpoint progress on visual simulation and UI refresh before sub-agent delegation

ai_client.py

@@ -1614,6 +1614,12 @@ def run_tier4_analysis(stderr: str) -> str:
   return f"[QA ANALYSIS FAILED] {e}"
   # ------------------------------------------------------------------ unified send
 
+import json
+from typing import Any, Callable, Optional, List
+
+# Assuming _model, _system_prompt, _provider, _send_lock are module-level variables
+# and the _send_xxx functions are also defined at module level.
+
 def send(
     md_content: str,
     user_message: str,
@@ -1639,6 +1645,62 @@ def send(
     pre_tool_callback  : Optional callback (payload: str) -> bool called before tool execution
     qa_callback        : Optional callback (stderr: str) -> str called for Tier 4 error analysis
     """
+    # --- START MOCK LOGIC ---
+    # Assuming _model, _custom_system_prompt, and _system_prompt are module-level variables.
+    # If _model is not 'mock', proceed to original provider logic.
+    if _model == 'mock':
+        mock_response_content = None
+        # Use _custom_system_prompt for keyword detection
+        current_system_prompt = _custom_system_prompt # Assuming _custom_system_prompt is accessible and defined
+
+        if 'tier1_epic_init' in current_system_prompt:
+            mock_response_content = [
+                {
+                    "id": "mock-track-1",
+                    "type": "epic",
+                    "module": "conductor",
+                    "persona": "Tier 1 Orchestrator",
+                    "severity": "high",
+                    "goal": "Initialize a new track.",
+                    "acceptance_criteria": "Track created successfully with required fields."
+                },
+                {
+                    "id": "mock-track-2",
+                    "type": "epic",
+                    "module": "conductor",
+                    "persona": "Tier 1 Orchestrator",
+                    "severity": "medium",
+                    "goal": "Initialize another track.",
+                    "acceptance_criteria": "Second track created successfully."
+                }
+            ]
+        elif 'tier2_sprint_planning' in current_system_prompt:
+            mock_response_content = [
+                {
+                    "id": "mock-ticket-1",
+                    "type": "story",
+                    "goal": "Implement feature X.",
+                    "target_file": "src/feature_x.py",
+                    "depends_on": [],
+                    "context_requirements": ["requirements.txt", "main.py"]
+                },
+                {
+                    "id": "mock-ticket-2",
+                    "type": "bug",
+                    "goal": "Fix bug Y.",
+                    "target_file": "src/bug_y.py",
+                    "depends_on": ["mock-ticket-1"],
+                    "context_requirements": ["tests/test_bug_y.py"]
+                }
+            ]
+        else:
+            mock_response_content = "Mock AI Response"
+        
+        # The function is typed to return 'str', so we return a JSON string.
+        # Ensure 'json' is imported at the module level.
+        return json.dumps(mock_response_content)
+    # --- END MOCK LOGIC ---
+
     with _send_lock:
         if _provider == "gemini":
             return _send_gemini(md_content, user_message, base_dir, file_items, discussion_history, pre_tool_callback, qa_callback)

api_hooks.py

@@ -1,4 +1,4 @@
-from __future__ import annotations
+from __future__ import annotations
 import json
 import threading
 import uuid
@@ -123,11 +123,15 @@ class HookHandler(BaseHTTPRequestHandler):
    def get_mma():
     try:
      result["mma_status"] = getattr(app, "mma_status", "idle")
+     result["ai_status"] = getattr(app, "ai_status", "idle")
      result["active_tier"] = getattr(app, "active_tier", None)
      result["active_track"] = getattr(app, "active_track", None)
      result["active_tickets"] = getattr(app, "active_tickets", [])
      result["mma_step_mode"] = getattr(app, "mma_step_mode", False)
      result["pending_approval"] = app._pending_mma_approval is not None
+     # Added lines for tracks and proposed_tracks
+     result["tracks"] = getattr(app, "tracks", [])
+     result["proposed_tracks"] = getattr(app, "proposed_tracks", [])
     finally:
      event.set()
    with app._pending_gui_tasks_lock:

conductor/tracks/robust_live_simulation_verification/plan.md

@@ -5,8 +5,8 @@
 - [x] Task: Implement helper methods in `ApiHookClient` for querying specific DearPyGui item states (e.g., `get_text_value`, `get_node_status`). 2a30e62
 
 ## Phase 2: Epic & Track Verification
-- [~] Task: Write the simulation routine to trigger a new Epic and verify the Track Browser updates correctly.
+- [x] Task: Write the simulation routine to trigger a new Epic and verify the Track Browser updates correctly. 605dfc3
-- [ ] Task: Verify that selecting a newly generated track successfully loads its initial (empty) state into the DAG visualizer.
+- [~] Task: Verify that selecting a newly generated track successfully loads its initial (empty) state into the DAG visualizer.
 
 ## Phase 3: DAG & Spawn Interception Verification
 - [ ] Task: Simulate the "Start Track" action and verify the DAG visualizer populates with tasks.

conductor/tracks/track_51dabc55/state.toml

@@ -0,0 +1,50 @@
+discussion = []
+
+[metadata]
+id = "track_51dabc55"
+name = "Implement a robust mathematical engine for basic a"
+status = "todo"
+created_at = "2026-02-28T21:06:22.065199"
+updated_at = "2026-02-28T21:06:22.065199"
+
+[[tasks]]
+id = "math_engine_add"
+description = "Implement the addition operation for the mathematical engine."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = []
+step_mode = false
+
+[[tasks]]
+id = "math_engine_subtract"
+description = "Implement the subtraction operation for the mathematical engine."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "math_engine_add",
+]
+step_mode = false
+
+[[tasks]]
+id = "math_engine_multiply"
+description = "Implement the multiplication operation for the mathematical engine."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "math_engine_subtract",
+]
+step_mode = false
+
+[[tasks]]
+id = "math_engine_divide"
+description = "Implement the division operation for the mathematical engine, including handling division by zero."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "math_engine_multiply",
+]
+step_mode = false

conductor/tracks/track_d01fdb6e/state.toml

@@ -0,0 +1,75 @@
+discussion = []
+
+[metadata]
+id = "track_d01fdb6e"
+name = "Implement a robust, testable arithmetic engine for"
+status = "todo"
+created_at = "2026-02-28T21:00:16.295678"
+updated_at = "2026-02-28T21:00:16.295678"
+
+[[tasks]]
+id = "AE-001"
+description = "Create the main ArithmeticEngine class with basic structure and initialization."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = []
+step_mode = false
+
+[[tasks]]
+id = "AE-002"
+description = "Implement the 'add' method in the ArithmeticEngine class."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "AE-001",
+]
+step_mode = false
+
+[[tasks]]
+id = "AE-003"
+description = "Implement the 'subtract' method in the ArithmeticEngine class."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "AE-001",
+]
+step_mode = false
+
+[[tasks]]
+id = "AE-004"
+description = "Implement the 'multiply' method in the ArithmeticEngine class."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "AE-001",
+]
+step_mode = false
+
+[[tasks]]
+id = "AE-005"
+description = "Implement the 'divide' method in the ArithmeticEngine class, including division by zero handling."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "AE-001",
+]
+step_mode = false
+
+[[tasks]]
+id = "AE-006"
+description = "Add comprehensive unit tests for all arithmetic operations."
+status = "todo"
+assigned_to = "unassigned"
+context_requirements = []
+depends_on = [
+    "AE-002",
+    "AE-003",
+    "AE-004",
+    "AE-005",
+]
+step_mode = false

conductor/workflow.md

@@ -29,12 +29,14 @@ All tasks follow a strict lifecycle:
    - **Analyze Changes:** Use `get_git_diff` if the task involves modifying recently updated code.
    - **Minimize Token Burn:** Only use `read_file` with `start_line`/`end_line` for specific implementation details once target areas are identified.
 4. **Write Failing Tests (Red Phase):**
-   - **Delegate Test Creation:** Do NOT write test code directly. Spawn a Tier 3 Worker (`python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`) with a prompt to create the necessary test files and unit tests based on the task criteria.
+   - **Pre-Delegation Checkpoint:** Before spawning a worker for dangerous or non-trivial changes, ensure your current progress is staged (`git add .`) or committed. This prevents losing iterations if a sub-agent incorrectly uses `git restore`.
+   - **Delegate Test Creation:** Do NOT write test code directly. Spawn a Tier 3 Worker (`python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`) with a prompt to create the necessary test files and unit tests based on the task criteria. (If repeating due to failures, pass `--failure-count X` to switch to a more capable model).
    - Take the code generated by the Worker and apply it.
    - **CRITICAL:** Run the tests and confirm that they fail as expected. This is the "Red" phase of TDD. Do not proceed until you have failing tests.
 
 4. **Implement to Pass Tests (Green Phase):**
-   - **Delegate Implementation:** Do NOT write the implementation code directly. Spawn a Tier 3 Worker (`python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`) with a highly specific prompt to write the minimum amount of application code necessary to make the failing tests pass.
+   - **Pre-Delegation Checkpoint:** Ensure current progress is staged or committed before delegating.
+   - **Delegate Implementation:** Do NOT write the implementation code directly. Spawn a Tier 3 Worker (`python scripts/mma_exec.py --role tier3-worker "[PROMPT]"`) with a highly specific prompt to write the minimum amount of application code necessary to make the failing tests pass. (If repeating due to failures, pass `--failure-count X` to switch to a more capable model).
    - Take the code generated by the Worker and apply it.
    - Run the test suite again and confirm that all tests now pass. This is the "Green" phase.
 

conductor_tech_lead.py

@@ -9,9 +9,9 @@ def generate_tickets(track_brief: str, module_skeletons: str) -> list[dict]:
     Breaks down a Track Brief and module skeletons into discrete Tier 3 Tickets.
     """
  # 1. Set Tier 2 Model (Tech Lead - Flash)
+ if ai_client._model != 'mock':
         ai_client.set_provider('gemini', 'gemini-2.5-flash-lite')
- ai_client.reset_session()
+        ai_client.reset_session() # 2. Construct Prompt
- # 2. Construct Prompt
  system_prompt = mma_prompts.PROMPTS.get("tier2_sprint_planning")
  user_message = (
   f"### TRACK BRIEF:\n{track_brief}\n\n"
@@ -77,3 +77,4 @@ if __name__ == "__main__":
  test_skeletons = "class NewFeature: pass"
  tickets = generate_tickets(test_brief, test_skeletons)
  print(json.dumps(tickets, indent=2))
+

config.toml

@@ -1,6 +1,6 @@
 [ai]
 provider = "gemini_cli"
-model = "gemini-2.5-flash-lite"
+model = "mock"
 temperature = 0.0
 max_tokens = 8192
 history_trunc_limit = 8000

gui_2.py

@@ -896,6 +896,8 @@ class App:
      user_data = task.get("user_data")
      if item == "btn_project_new_automated":
       self._cb_new_project_automated(user_data)
+     elif item == "btn_mma_load_track":
+      self._cb_load_track(user_data)
      elif item in self._clickable_actions:
      # Check if it's a method that accepts user_data
       import inspect
@@ -935,6 +937,8 @@ class App:
      self._pending_mma_approval = task
      if "dialog_container" in task:
       task["dialog_container"][0] = dlg
+    elif action == 'refresh_from_project':
+     self._refresh_from_project()
     elif action == "mma_spawn_approval":
      dlg = MMASpawnApprovalDialog(
       task.get("ticket_id"), 
@@ -1959,9 +1963,36 @@ class App:
 
  def _cb_accept_tracks(self) -> None:
   def _bg_task():
-   for track_data in self.proposed_tracks:
+   # Generate skeletons once
-    self._start_track_logic(track_data)
+   self.ai_status = "Phase 2: Generating skeletons for all tracks..."
-   self.ai_status = "Tracks accepted and execution started."
+   parser = ASTParser(language="python")
+   generated_skeletons = ""
+   try:
+       for i, file_path in enumerate(self.files):
+           try:
+               self.ai_status = f"Phase 2: Scanning files ({i+1}/{len(self.files)})..."
+               abs_path = Path(self.ui_files_base_dir) / file_path
+               if abs_path.exists() and abs_path.suffix == ".py":
+                   with open(abs_path, "r", encoding="utf-8") as f:
+                       code = f.read()
+                       generated_skeletons += f"\\nFile: {file_path}\\n{parser.get_skeleton(code)}\\n"
+           except Exception as e:
+               print(f"Error parsing skeleton for {file_path}: {e}")
+   except Exception as e:
+       self.ai_status = f"Error generating skeletons: {e}"
+       print(f"Error generating skeletons: {e}")
+       return # Exit if skeleton generation fails
+
+   # Now loop through tracks and call _start_track_logic with generated skeletons
+   total_tracks = len(self.proposed_tracks)
+   for i, track_data in enumerate(self.proposed_tracks):
+    title = track_data.get("title") or track_data.get("goal", "Untitled Track")
+    self.ai_status = f"Processing track {i+1} of {total_tracks}: '{title}'..."
+    self._start_track_logic(track_data, skeletons_str=generated_skeletons) # Pass skeletons
+
+   with self._pending_gui_tasks_lock:
+     self._pending_gui_tasks.append({'action': 'refresh_from_project'}) # Ensure UI refresh after tracks are started
+   self.ai_status = f"All {total_tracks} tracks accepted and execution started."
   threading.Thread(target=_bg_task, daemon=True).start()
 
  def _cb_start_track(self, user_data: Any = None) -> None:
@@ -1976,14 +2007,16 @@ class App:
    threading.Thread(target=lambda: self._start_track_logic(track_data), daemon=True).start()
    self.ai_status = f"Track '{title}' started."
 
- def _start_track_logic(self, track_data: dict[str, Any]) -> None:
+ def _start_track_logic(self, track_data: dict[str, Any], skeletons_str: str | None = None) -> None:
   try:
    goal = track_data.get("goal", "")
    title = track_data.get("title") or track_data.get("goal", "Untitled Track")
    self.ai_status = f"Phase 2: Generating tickets for {title}..."
+
+   skeletons = "" # Initialize skeletons variable
+   if skeletons_str is None: # Only generate if not provided
        # 1. Get skeletons for context
        parser = ASTParser(language="python")
-   skeletons = ""
        for i, file_path in enumerate(self.files):
            try:
                self.ai_status = f"Phase 2: Scanning files ({i+1}/{len(self.files)})..."
@@ -1991,9 +2024,12 @@ class App:
                if abs_path.exists() and abs_path.suffix == ".py":
                    with open(abs_path, "r", encoding="utf-8") as f:
                        code = f.read()
-       skeletons += f"\nFile: {file_path}\n{parser.get_skeleton(code)}\n"
+                       skeletons += f"\\nFile: {file_path}\\n{parser.get_skeleton(code)}\\n"
            except Exception as e:
                print(f"Error parsing skeleton for {file_path}: {e}")
+   else:
+       skeletons = skeletons_str # Use provided skeletons
+
    self.ai_status = "Phase 2: Calling Tech Lead..."
    raw_tickets = conductor_tech_lead.generate_tickets(goal, skeletons)
    if not raw_tickets:

manualslop_layout.ini

@@ -79,7 +79,7 @@ DockId=0x0000000F,2
 
 [Window][Theme]
 Pos=0,17
-Size=632,824
+Size=32,824
 Collapsed=0
 DockId=0x00000005,1
 
@@ -89,14 +89,14 @@ Size=900,700
 Collapsed=0
 
 [Window][Diagnostics]
-Pos=634,17
+Pos=34,17
-Size=911,643
+Size=765,545
 Collapsed=0
 DockId=0x00000010,0
 
 [Window][Context Hub]
 Pos=0,17
-Size=632,824
+Size=32,824
 Collapsed=0
 DockId=0x00000005,0
 
@@ -107,26 +107,26 @@ Collapsed=0
 DockId=0x0000000D,0
 
 [Window][Discussion Hub]
-Pos=1547,17
+Pos=801,17
-Size=879,1395
+Size=879,1183
 Collapsed=0
 DockId=0x00000004,0
 
 [Window][Operations Hub]
-Pos=634,17
+Pos=34,17
-Size=911,643
+Size=765,545
 Collapsed=0
 DockId=0x00000010,1
 
 [Window][Files & Media]
 Pos=0,843
-Size=632,569
+Size=32,357
 Collapsed=0
 DockId=0x00000006,1
 
 [Window][AI Settings]
 Pos=0,843
-Size=632,569
+Size=32,357
 Collapsed=0
 DockId=0x00000006,0
 
@@ -136,14 +136,14 @@ Size=416,325
 Collapsed=0
 
 [Window][MMA Dashboard]
-Pos=634,662
+Pos=34,564
-Size=911,750
+Size=765,636
 Collapsed=0
 DockId=0x00000011,0
 
 [Window][Log Management]
-Pos=1547,17
+Pos=801,17
-Size=879,1395
+Size=879,1183
 Collapsed=0
 DockId=0x00000004,1
 
@@ -173,7 +173,7 @@ Column 3  Weight=1.0000
 DockNode              ID=0x00000008 Pos=3125,170 Size=593,1157 Split=Y
   DockNode            ID=0x00000009 Parent=0x00000008 SizeRef=1029,147 Selected=0x0469CA7A
   DockNode            ID=0x0000000A Parent=0x00000008 SizeRef=1029,145 Selected=0xDF822E02
-DockSpace             ID=0xAFC85805 Window=0x079D3A04 Pos=0,17 Size=2426,1395 Split=Y
+DockSpace             ID=0xAFC85805 Window=0x079D3A04 Pos=0,17 Size=1680,1183 Split=Y
   DockNode            ID=0x0000000C Parent=0xAFC85805 SizeRef=1362,1041 Split=X Selected=0x5D11106F
     DockNode          ID=0x00000003 Parent=0x0000000C SizeRef=1545,1183 Split=X
       DockNode        ID=0x0000000B Parent=0x00000003 SizeRef=404,1186 Split=Y Selected=0xF4139CA2
@@ -182,7 +182,7 @@ DockSpace             ID=0xAFC85805 Window=0x079D3A04 Pos=0,17 Size=2426,1395 Sp
             DockNode  ID=0x00000005 Parent=0x00000007 SizeRef=295,824 Selected=0xF4139CA2
             DockNode  ID=0x00000006 Parent=0x00000007 SizeRef=295,724 CentralNode=1 Selected=0x7BD57D6A
           DockNode    ID=0x0000000E Parent=0x00000002 SizeRef=911,858 Split=Y Selected=0x418C7449
-            DockNode  ID=0x00000010 Parent=0x0000000E SizeRef=868,545 Selected=0x418C7449
+            DockNode  ID=0x00000010 Parent=0x0000000E SizeRef=868,545 Selected=0xB4CBF21A
             DockNode  ID=0x00000011 Parent=0x0000000E SizeRef=868,636 Selected=0x3AEC3498
         DockNode      ID=0x00000001 Parent=0x0000000B SizeRef=1029,775 Selected=0x8B4EBFA6
       DockNode        ID=0x0000000D Parent=0x00000003 SizeRef=435,1186 Selected=0x363E93D6

mma-orchestrator/SKILL.md

@@ -15,11 +15,13 @@ To ensure proper environment handling and logging, you MUST NOT call the `gemini
 
 ## 1. The Tier 3 Worker (Execution)
 When performing code modifications or implementing specific requirements:
-1. **DO NOT** perform large code writes yourself.
+1. **Pre-Delegation Checkpoint:** For dangerous or non-trivial changes, ALWAYS stage your changes (`git add .`) or commit before delegating to a Tier 3 Worker. If the worker fails or runs `git restore`, you will lose all prior AI iterations for that file if it wasn't staged/committed.
-2. **DO** construct a single, highly specific prompt with a clear objective.
+2. **DO NOT** perform large code writes yourself.
-3. **DO** spawn a Tier 3 Worker.
+3. **DO** construct a single, highly specific prompt with a clear objective.
+4. **DO** spawn a Tier 3 Worker.
    *Command:* `uv run python scripts/mma_exec.py --role tier3-worker "Implement [SPECIFIC_INSTRUCTION] in [FILE_PATH]. Follow TDD and return success status or code changes."`
-4. The Tier 3 Worker is stateless and has tool access for file I/O. 
+5. **Handling Repeated Failures:** If a Tier 3 Worker fails multiple times on the same task, it may lack the necessary capability. You must track failures and retry with `--failure-count <N>` (e.g., `--failure-count 2`). This tells `mma_exec.py` to escalate the sub-agent to a more powerful reasoning model (like `gemini-3-flash`).
+6. The Tier 3 Worker is stateless and has tool access for file I/O. 
 
 ## 2. The Tier 4 QA Agent (Diagnostics)
 If you run a test or command that fails with a significant error or large traceback:

scripts/mma_exec.py

@@ -57,13 +57,15 @@ def generate_skeleton(code: str) -> str:
  except Exception as e:
   return f"# Error generating skeleton: {e}\n{code}"
 
-def get_model_for_role(role: str) -> str:
+def get_model_for_role(role: str, failure_count: int = 0) -> str:
  """Returns the specific model to use for a given tier role."""
  if role == 'tier1-orchestrator' or role == 'tier1':
   return 'gemini-3.1-pro-preview'
  elif role == 'tier2-tech-lead' or role == 'tier2':
   return 'gemini-3-flash-preview'
  elif role == 'tier3-worker' or role == 'tier3':
+  if failure_count > 1:
+   return 'gemini-3-flash'
   return 'gemini-2.5-flash-lite'
  elif role == 'tier4-qa' or role == 'tier4':
   return 'gemini-2.5-flash-lite'
@@ -124,8 +126,8 @@ def get_dependencies(filepath: str) -> list[str]:
   print(f"Error getting dependencies for {filepath}: {e}")
   return []
 
-def execute_agent(role: str, prompt: str, docs: list[str], debug: bool = False) -> str:
+def execute_agent(role: str, prompt: str, docs: list[str], debug: bool = False, failure_count: int = 0) -> str:
- model = get_model_for_role(role)
+ model = get_model_for_role(role, failure_count)
  # Advanced Context: Dependency skeletons for Tier 3
  injected_context = ""
  # Whitelist of modules that sub-agents have "unfettered" (full) access to.
@@ -249,6 +251,12 @@ def create_parser() -> argparse.ArgumentParser:
   action="store_true",
   help="Enable debug logging"
  )
+ parser.add_argument(
+  "--failure-count",
+  type=int,
+  default=0,
+  help="Number of times this task has failed previously"
+ )
  parser.add_argument(
   "prompt", 
   type=str, 
@@ -263,6 +271,7 @@ def main() -> None:
  role = args.role
  prompt = args.prompt
  debug = args.debug
+ failure_count = args.failure_count
  docs = []
  if args.task_file and os.path.exists(args.task_file):
   with open(args.task_file, "rb") as f:
@@ -272,6 +281,7 @@ def main() -> None:
    docs = task_data.get("docs", [])
    # Only override debug if it's explicitly set in the task file (optional)
    debug = task_data.get("debug", debug)
+   failure_count = task_data.get("failure_count", failure_count)
  if not role or not prompt:
   parser.print_help()
   return
@@ -283,8 +293,8 @@ def main() -> None:
  for ref in file_refs:
   if os.path.exists(ref) and ref not in docs:
    docs.append(ref)
- print(f"Executing role: {role} with docs: {docs} (debug={debug})")
+ print(f"Executing role: {role} with docs: {docs} (debug={debug}, failure_count={failure_count})")
- result = execute_agent(role, prompt, docs, debug=debug)
+ result = execute_agent(role, prompt, docs, debug=debug, failure_count=failure_count)
  print(result)
 
 if __name__ == "__main__":

tests/temp_project.toml

@@ -37,6 +37,6 @@ web_search = true
 fetch_url = true
 
 [mma]
-epic = ""
+epic = "Develop a new feature"
 active_track_id = ""
 tracks = []

tests/temp_project_history.toml

@@ -10,5 +10,5 @@ auto_add = true
 
 [discussions.main]
 git_commit = ""
-last_updated = "2026-02-28T20:50:25"
+last_updated = "2026-02-28T21:27:02"
 history = []

tests/visual_sim_mma_v2.py

@@ -9,31 +9,71 @@ sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
 from api_hook_client import ApiHookClient
 
 @pytest.mark.integration
-def test_mma_epic_simulation(live_gui) -> None:
+def test_mma_complete_lifecycle(live_gui) -> None:
  """
-    Integration test for MMA epic simulation.
+    Tests the entire MMA lifecycle from epic planning to track loading and ticket verification
-    Red Phase: asserts False.
+    in a single test case to avoid state dependency issues between separate test functions.
     """
  client = ApiHookClient()
  assert client.wait_for_server(timeout=10)
- # Try selecting MMA Dashboard tab if applicable (using typical naming convention)
+
- try:
+ # 1. Set model to 'mock'.
-  client.select_tab('main_tab_bar', 'tab_mma')
- except Exception:
-  pass
-  # Set model to mock to avoid real API calls and timeouts
  try:
   client.set_value('current_model', 'mock')
- except Exception:
+ except Exception as e:
-  pass
+  pytest.fail(f"Failed to set model to 'mock': {e}")
- client.set_value('mma_epic_input', 'Build a simple calculator')
+
+ # 2. Enter epic and click 'Plan Epic'.
+ client.set_value('mma_epic_input', 'Develop a new feature')
  client.click('btn_mma_plan_epic')
- # Poll client.get_mma_status() every 1 second (up to 30 seconds)
+
- success = False
+ # 3. Wait for 'proposed_tracks'.
- for i in range(30):
+ proposed_tracks_found = False
+ for _ in range(60): # Poll for up to 60 seconds
   status = client.get_mma_status()
-  if status and status.get('tracks') and len(status['tracks']) > 0:
+  print(f"Polling status: {status}")
-   success = True
+  # Assuming 'ai_status' might be a key within the status dictionary. If not, this needs adjustment.
+  print(f"Polling ai_status: {status.get('ai_status', 'N/A')}")
+  if status and status.get('proposed_tracks') and len(status['proposed_tracks']) > 0:
+   proposed_tracks_found = True
    break
   time.sleep(1)
- assert success, "Failed to generate at least one track."
+ assert proposed_tracks_found, "Failed to find proposed tracks after planning epic."
+
+ # 4. Click 'Accept' to start tracks.
+ client.click('btn_mma_accept_tracks')
+
+ # 5. Wait for 'tracks' list to populate.
+ tracks_populated = False
+ for _ in range(30): # Poll for up to 30 seconds
+  status = client.get_mma_status()
+  if status and status.get('tracks') and len(status['tracks']) > 0:
+   tracks_populated = True
+   break
+  time.sleep(1)
+ assert tracks_populated, "Failed to populate tracks list after accepting proposed tracks."
+
+ # 6. Verify that one of the new tracks can be loaded and its tickets appear in 'active_tickets'.
+ status_after_tracks = client.get_mma_status()
+ assert status_after_tracks is not None, "Failed to get MMA status after tracks populated."
+ tracks_list = status_after_tracks.get('tracks')
+ assert tracks_list is not None and len(tracks_list) > 0, "Tracks list is empty or not found."
+
+ track_id_to_load = tracks_list[0]['id']
+ print(f"Attempting to load track with ID: {track_id_to_load}")
+
+ # Load the first track
+ client.click('btn_mma_load_track', user_data=track_id_to_load)
+
+ # Poll until 'active_track' is not None and 'active_tickets' are present
+ active_track_and_tickets_found = False
+ for _ in range(60): # Poll for up to 60 seconds
+  status = client.get_mma_status()
+  if status and status.get('active_track') == track_id_to_load and \
+     'active_tickets' in status and len(status['active_tickets']) > 0:
+   active_track_and_tickets_found = True
+   break
+  time.sleep(1)
+ assert active_track_and_tickets_found, f"Timed out waiting for track {track_id_to_load} to load and populate active tickets."
+
+ print(f"Successfully loaded and verified track ID: {track_id_to_load} with active tickets.")