conductor(plan): Mark task 2.1 complete, begin 2.2
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## Phase 2: Fix Token Usage Tracking
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- [~] Task 2.1: In `run_worker_lifecycle` (multi_agent_conductor.py:295-298), the `stats = {}` stub produces zero token counts. Replace with `stats = ai_client.get_history_bleed_stats()` which returns a dict containing `"total_input_tokens"` and `"total_output_tokens"` (see ai_client.py:1657-1796). Extract the relevant fields and update `engine.tier_usage["Tier 3"]`. If `get_history_bleed_stats` is too heavy, use the simpler approach: after `ai_client.send()`, read the last comms log entry from `ai_client.get_comms_log()[-1]` which contains `payload.usage` with token counts.
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- [ ] Task 2.2: Similarly fix Tier 1 and Tier 2 token tracking. In `_cb_plan_epic` (gui_2.py:1985-2010) and wherever Tier 2 calls happen, ensure `mma_tier_usage` is updated with actual token counts from comms log entries.
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- [x] Task 2.1: In `run_worker_lifecycle` (multi_agent_conductor.py:295-298), the `stats = {}` stub produces zero token counts. Replace with `stats = ai_client.get_history_bleed_stats()` which returns a dict containing `"total_input_tokens"` and `"total_output_tokens"` (see ai_client.py:1657-1796). Extract the relevant fields and update `engine.tier_usage["Tier 3"]`. If `get_history_bleed_stats` is too heavy, use the simpler approach: after `ai_client.send()`, read the last comms log entry from `ai_client.get_comms_log()[-1]` which contains `payload.usage` with token counts. Used comms-log baseline approach. 3eefdfd
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- [~] Task 2.2: Similarly fix Tier 1 and Tier 2 token tracking. In `_cb_plan_epic` (gui_2.py:1985-2010) and wherever Tier 2 calls happen, ensure `mma_tier_usage` is updated with actual token counts from comms log entries.
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## Phase 3: End-to-End Verification
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