# Track Specification: MMA Pipeline Fix & Worker Stream Verification

## Overview
The MMA pipeline has a verified code path from `run_worker_lifecycle` → `_queue_put("response", ...)` → `_process_event_queue` → `_pending_gui_tasks("handle_ai_response")` → `mma_streams[stream_id] = text`. However, the robust_live_simulation track's session compression (2026-02-28) documented that Tier 3 worker output never appears in `mma_streams` during actual GUI operation. The simulation only ever sees `'Tier 1'` in `mma_streams` keys.

This track diagnoses and fixes the pipeline break, then verifies end-to-end that worker output flows from `ai_client.send()` through to the GUI's `mma_streams` dict.

## Root Cause Candidates (from code analysis)

1. **`run_in_executor` positional arg ordering**: `run_worker_lifecycle` has 7 parameters. The call at `multi_agent_conductor.py:118-127` passes them positionally. If the order is wrong, `loop` could be `None` and `_queue_put` would silently fail (the `if loop:` branch is skipped, falling to `event_queue._queue.put_nowait()` which may not work from a thread-pool thread because `asyncio.Queue.put_nowait` is not thread-safe when called from outside the event loop).

2. **`asyncio.Queue` thread safety**: `_queue_put` uses `asyncio.run_coroutine_threadsafe()` which IS thread-safe. But the `else` branch (`event_queue._queue.put_nowait(...)`) is NOT — `asyncio.Queue` is NOT thread-safe for cross-thread access. If `loop` is `None`, this branch silently corrupts or drops the event.

3. **`ai_client.reset_session()` side effects**: Called at the start of `run_worker_lifecycle`, this resets the global `_gemini_cli_adapter.session_id = None`. If the adapter is shared state and the GUI's Tier 2 call is still in-flight, this could corrupt the provider state.

4. **Token stats stub**: `engine.tier_usage` update uses `stats = {}` (empty dict, commented "ai_client.get_token_stats() is not available"), so `prompt_tokens` and `candidates_tokens` are always 0. Not a stream bug but a data bug.

## Goals
1. Fix Tier 3 worker responses reaching `mma_streams` in the GUI.
2. Fix token usage tracking for Tier 3 workers.
3. Verify via `ApiHookClient.get_mma_status()` that `mma_streams` contains Tier 3 output after a mock MMA run.

## Architecture Reference
- Threading model: [docs/guide_architecture.md](../../docs/guide_architecture.md) — see "Cross-Thread Data Structures" and "Pattern A: AsyncEventQueue"
- Worker lifecycle: [docs/guide_mma.md](../../docs/guide_mma.md) — see "Tier 3: Worker Lifecycle"
- Frame-sync: [docs/guide_architecture.md](../../docs/guide_architecture.md) — see "Frame-Sync Mechanism" action catalog (`handle_ai_response` with `stream_id`)