diff --git a/conductor/tracks/cost_token_analytics_20260306/spec.md b/conductor/tracks/cost_token_analytics_20260306/spec.md
index ae5cc66..2f56dc0 100644
--- a/conductor/tracks/cost_token_analytics_20260306/spec.md
+++ b/conductor/tracks/cost_token_analytics_20260306/spec.md
@@ -8,59 +8,48 @@ Real-time cost tracking panel displaying cost per model, session totals, and bre
 ### Already Implemented (DO NOT re-implement)
 
 #### cost_tracker.py (src/cost_tracker.py)
-- **`MODEL_PRICING` dict**: Pricing per 1M tokens for all supported models
+- **`MODEL_PRICING` list**: List of (regex_pattern, rates_dict) tuples
   ```python
-  MODEL_PRICING: dict[str, dict[str, float]] = {
-   "gemini-2.5-flash-lite": {"input": 0.075, "output": 0.30},
-   "gemini-2.5-flash": {"input": 0.15, "output": 0.60},
-   "gemini-3.1-pro-preview": {"input": 1.25, "output": 5.00},
-   "claude-3-5-sonnet": {"input": 3.00, "output": 15.00},
-   "deepseek-v3": {"input": 0.27, "output": 1.10},
-   # ... more models
-  }
+  MODEL_PRICING = [
+      (r"gemini-2\.5-flash-lite", {"input_per_mtok": 0.075, "output_per_mtok": 0.30}),
+      (r"gemini-2\.5-flash", {"input_per_mtok": 0.15, "output_per_mtok": 0.60}),
+      (r"gemini-3-flash-preview", {"input_per_mtok": 0.15, "output_per_mtok": 0.60}),
+      (r"gemini-3\.1-pro-preview", {"input_per_mtok": 3.50, "output_per_mtok": 10.50}),
+      (r"claude-.*-sonnet", {"input_per_mtok": 3.0, "output_per_mtok": 15.0}),
+      (r"deepseek-v3", {"input_per_mtok": 0.27, "output_per_mtok": 1.10}),
+  ]
   ```
-- **`estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float`**: Calculate cost in USD
-- **Returns 0.0 for unknown models** - safe default
+- **`estimate_cost(model: str, input_tokens: int, output_tokens: int) -> float`**: Uses regex match, returns 0.0 for unknown models
 
-#### Token Tracking in ai_client.py
-- **`_add_bleed_derived()`** (ai_client.py): Adds derived token counts to comms entries
-- **`get_history_bleed_stats()`**: Returns token statistics from history
-- **Gemini**: Token counts from API response (`usage_metadata`)
-- **Anthropic**: Token counts from API response (`usage`)
-- **DeepSeek**: Token counts from API response (`usage`)
-
-#### MMA Tier Usage Tracking
-- **`ConductorEngine.tier_usage`** (multi_agent_conductor.py): Tracks per-tier token usage
+#### MMA Tier Usage Tracking (multi_agent_conductor.py)
+- **`ConductorEngine.tier_usage`** already tracks per-tier token counts AND model:
   ```python
   self.tier_usage = {
-   "Tier 1": {"input": 0, "output": 0},
-   "Tier 2": {"input": 0, "output": 0},
-   "Tier 3": {"input": 0, "output": 0},
-   "Tier 4": {"input": 0, "output": 0},
+   "Tier 1": {"input": 0, "output": 0, "model": "gemini-3.1-pro-preview"},
+   "Tier 2": {"input": 0, "output": 0, "model": "gemini-3-flash-preview"},
+   "Tier 3": {"input": 0, "output": 0, "model": "gemini-2.5-flash-lite"},
+   "Tier 4": {"input": 0, "output": 0, "model": "gemini-2.5-flash-lite"},
   }
   ```
+- **Key insight**: The model name is already tracked per tier in `tier_usage[tier]["model"]`
+- Updated in `run_worker_lifecycle()` from comms_log token counts
 
 ### Gaps to Fill (This Track's Scope)
 - No GUI panel to display cost information
 - No session-level cost accumulation
-- No per-model breakdown visualization
-- No tier breakdown visualization
+- No per-tier cost breakdown in UI
 
 ## Architectural Constraints
 
 ### Non-Blocking Updates
 - Cost calculations MUST NOT block UI thread
-- Token counts are read from existing tracking - no new API calls
+- Token counts are read from existing tier_usage - no new tracking needed
 - Use cached values, update on state change events
 
 ### Cross-Thread Data Access
-- `tier_usage` is updated on asyncio worker thread
-- GUI reads via `_process_pending_gui_tasks` pattern
-- Already synchronized through MMA state updates
-
-### Memory Efficiency
-- Session cost is a simple float - no history array needed
-- Per-model costs can be dict: `{model_name: float}`
+- `tier_usage` is updated on worker threads
+- GUI reads via MMA state updates through `_pending_gui_tasks` pattern
+- Already synchronized through existing state update mechanism
 
 ## Architecture Reference
 
@@ -69,38 +58,72 @@ Real-time cost tracking panel displaying cost per model, session totals, and bre
 | File | Lines | Purpose |
 |------|-------|---------|
 | `src/cost_tracker.py` | 10-40 | `MODEL_PRICING`, `estimate_cost()` |
-| `src/ai_client.py` | ~500-550 | `_add_bleed_derived()`, `get_history_bleed_stats()` |
-| `src/multi_agent_conductor.py` | ~50-60 | `tier_usage` dict |
+| `src/multi_agent_conductor.py` | ~50-60 | `tier_usage` dict with input/output/model |
 | `src/gui_2.py` | ~2700-2800 | `_render_mma_dashboard()` - existing tier usage display |
-| `src/gui_2.py` | ~1800-1900 | `_render_token_budget_panel()` - potential location |
 
-### Existing MMA Dashboard Pattern
-The `_render_mma_dashboard()` method already displays tier usage in a table. Extend this pattern for cost display.
+### Cost Calculation Pattern
+```python
+from src import cost_tracker
+usage = engine.tier_usage["Tier 3"]
+cost = cost_tracker.estimate_cost(
+    usage["model"],      # Already tracked!
+    usage["input"],
+    usage["output"]
+)
+```
 
 ## Functional Requirements
 
 ### FR1: Session Cost Accumulation
-- Track total cost for the current session
+- Track total cost for the current session in App/AppController state
 - Reset on session reset
-- Store in `App` or `AppController` state
+- Sum of all tier costs
 
-### FR2: Per-Model Cost Display
-- Show cost broken down by model name
-- Group by provider (Gemini, Anthropic, DeepSeek)
-- Show token counts alongside costs
+### FR2: Per-Tier Cost Display
+- Show cost per MMA tier using existing `tier_usage[tier]["model"]` for model
+- Show input/output tokens alongside cost
+- Calculate using `cost_tracker.estimate_cost()`
 
-### FR3: Tier Breakdown Display
-- Show cost per MMA tier (Tier 1-4)
-- Use existing `tier_usage` data
-- Calculate cost using `cost_tracker.estimate_cost()`
-
-### FR4: Real-Time Updates
+### FR3: Real-Time Updates
 - Update cost display when MMA state changes
 - Hook into existing `mma_state_update` event handling
 - No polling - event-driven
 
 ## Non-Functional Requirements
 
+| Requirement | Constraint |
+|-------------|------------|
+| Frame Time Impact | <1ms when panel visible |
+| Memory Overhead | <1KB for session cost state |
+
+## Testing Requirements
+
+### Unit Tests
+- Test `estimate_cost()` with known model/token combinations
+- Test unknown model returns 0.0
+- Test session cost accumulation
+
+### Integration Tests (via `live_gui` fixture)
+- Verify cost panel displays after MMA execution
+- Verify session reset clears costs
+
+## Out of Scope
+- Historical cost tracking across sessions
+- Cost budgeting/alerts
+- Per-model aggregation (model already per-tier)
+
+## Acceptance Criteria
+- [ ] Cost panel displays in GUI
+- [ ] Per-tier cost shown with token counts
+- [ ] Tier breakdown uses existing tier_usage model field
+- [ ] Total session cost accumulates correctly
+- [ ] Panel updates on MMA state changes
+- [ ] Uses existing `cost_tracker.estimate_cost()`
+- [ ] Session reset clears costs
+- [ ] 1-space indentation maintained
+
+## Non-Functional Requirements
+
 | Requirement | Constraint |
 |-------------|------------|
 | Frame Time Impact | <1ms when panel visible |
diff --git a/conductor/tracks/kill_abort_workers_20260306/spec.md b/conductor/tracks/kill_abort_workers_20260306/spec.md
index d77576a..59c947e 100644
--- a/conductor/tracks/kill_abort_workers_20260306/spec.md
+++ b/conductor/tracks/kill_abort_workers_20260306/spec.md
@@ -1,49 +1,40 @@
 # Track Specification: Kill/Abort Running Workers (kill_abort_workers_20260306)
 
 ## Overview
-Add ability to kill/abort a running Tier 3 worker mid-execution. Currently workers run to completion in `run_in_executor()`; add cancel button with forced termination option.
+Add ability to kill/abort a running Tier 3 worker mid-execution. Currently workers run to completion; add cancel button with forced termination option.
 
 ## Current State Audit
 
 ### Already Implemented (DO NOT re-implement)
 
 #### Worker Execution (multi_agent_conductor.py)
-- **`run_worker_lifecycle()`**: Executes ticket via `loop.run_in_executor(None, ...)`
-- **`ConductorEngine.run()`**: Main loop that spawns workers
-- **No cancellation mechanism exists**
+- **`run_worker_lifecycle()`**: Executes ticket via `threading.Thread(daemon=True)`
+- **`ConductorEngine.run()`**: Spawns parallel workers:
+- **No thread references stored** - threads launched and joined() but no tracking
+- **No abort mechanism** - no way to stop a running worker
 
-#### Thread Pool Pattern (app_controller.py / gui_2.py)
-- Uses `threading.Thread(daemon=True)` for background work
-- `asyncio.run_in_executor()` for blocking AI calls
-- No thread references stored for later cancellation
+#### Threading (multi_agent_conductor.py)
+- **`threading.Thread`**: Used for workers
+- **`threading.Event`**: Available for signaling
+- **No abort event per worker**
 
-#### GUI State (gui_2.py)
-- **`mma_streams`**: Dict of worker output streams by tier
-- **`active_tickets`**: List of currently active tickets
-- **No per-worker thread tracking**
-
-### Gaps to Fill (This Track's Scope)
-- No way to track individual worker threads
-- No cancellation signal mechanism
-- No UI for kill/abort
+### Gaps to Fill (This Track's scope)
+- No worker thread tracking
+- No abort signal mechanism
+- No kill button UI
 - No cleanup on termination
 
 ## Architectural Constraints
 
-### Thread Safety
-- Worker tracking MUST use thread-safe data structures
-- Kill signal MUST be atomic (threading.Event)
-- Status updates MUST be atomic
-
 ### Clean Termination
 - Resources (file handles, network connections) MUST be released
 - Partial results SHOULD be preserved
 - No zombie processes
 
-### AI Client Cancellation
-- `ai_client.send()` is blocking - cannot be interrupted mid-call
-- Kill can only happen between API calls or during tool execution
-- Use `threading.Event` to signal abort between operations
+### Abort Timing
+- **AI API calls cannot mid-call interruption** (API limitation)
+- Abort only between API calls or during tool execution
+- Check abort flag between operations
 
 ## Architecture Reference
 
@@ -51,56 +42,85 @@ Add ability to kill/abort a running Tier 3 worker mid-execution. Currently worke
 
 | File | Lines | Purpose |
 |------|-------|---------|
-| `src/multi_agent_conductor.py` | 150-250 | `run_worker_lifecycle()` - add abort check |
-| `src/multi_agent_conductor.py` | 80-120 | `ConductorEngine.run()` - track workers |
-| `src/dag_engine.py` | 50-80 | `ExecutionEngine` - add kill method |
-| `src/models.py` | 30-50 | `Ticket` - add abort_event field |
-| `src/gui_2.py` | 2700-2800 | `_render_mma_dashboard()` - add kill buttons |
-
-### Proposed Worker Tracking Pattern
+| `src/multi_agent_conductor.py` | ~80-150 | `ConductorEngine.run()` - thread spawning |
+| `src/multi_agent_conductor.py` | ~250-320 | `run_worker_lifecycle()` - add abort check |
+| `src/gui_2.py` | ~2650-2750 | `_render_mma_dashboard()` - add kill buttons |
 
+### Current Thread Pattern
 ```python
-# In ConductorEngine:
-self._active_workers: dict[str, dict] = {}  # ticket_id -> {thread, event, status}
+# In ConductorEngine.run():
+threads = []
+for ticket in to_run:
+    t = threading.Thread(
+        target=run_worker_lifecycle,
+        args=(ticket, context, context_files, self.event_queue, self, md_content),
+        daemon=True
+    )
+    threads.append(t)
+    t.start()
 
-# In Ticket:
-self._abort_event: threading.Event = threading.Event()
-
-# In run_worker_lifecycle:
-if ticket._abort_event.is_set():
- return  # Exit early
+for t in threads:
+    t.join()
 ```
 
 ## Functional Requirements
 
 ### FR1: Worker Thread Tracking
-- Store reference to each worker's thread
-- Store abort Event per worker
-- Track status: running, killing, killed
+- Store thread reference in `_active_workers: dict[ticket_id, Thread]`
+- Track thread state: running, completed, killed
+- Clean up on completion
 
-### FR2: Kill Button UI
-- Button per active worker in MMA dashboard
+### FR2: Abort Event Mechan
+- Add `threading.Event()` per ticket: `_abort_events[ticket_id]`
+- Worker checks event between operations:
+- API call cannot be interrupted (limitation documented)
+
+### FR3: Kill Button UI
+- Button per running worker in MMA dashboard
 - Confirmation dialog before kill
 - Disabled if no workers running
 
-### FR3: Abort Signal Mechanism
-- `threading.Event` per ticket for abort signaling
-- Worker checks event between operations
-- AI client call cannot be interrupted (document limitation)
-
-### FR4: Clean Cleanup
-- Mark ticket as "killed" status
+### FR4: Clean Termination
+- On kill: set `abort_event.set()`
+- Wait for thread to finish (with timeout)
+- Remove from `_active_workers`
 - Preserve partial output in stream
-- Remove from active workers dict
 
 ## Non-Functional Requirements
-
 | Requirement | Constraint |
 |-------------|------------|
 | Response Time | Kill takes effect within 1s of button press |
 | No Deadlocks | Kill cannot cause system hang |
 | Memory Safety | Worker resources freed after kill |
 
+## Testing Requirements
+### Unit Tests
+- Test abort event stops worker at check point
+- Test worker tracking dict updates correctly
+- Test kill button enables/disables based on workers
+
+### Integration Tests (via `live_gui` fixture)
+- Start worker, click kill, verify termination
+- Verify partial output preserved
+- Verify no zombie threads
+
+## Out of Scope
+- Force-killing AI API calls (API limitation)
+- Kill and restart (separate track)
+- Kill during PowerShell execution (separate concern)
+
+## Acceptance Criteria
+- [ ] Kill button visible per running worker
+- [ ] Confirmation dialog appears
+- [ ] Worker terminates within 1s of kill
+- [ ] Partial output preserved in stream
+- [ ] Resources cleaned up
+- [ ] Status reflects "killed"
+- [ ] No zombie threads after kill
+- [ ] 1-space indentation maintained
+| No Deadlocks | Kill cannot cause system hang |
+| Memory Safety | Worker resources freed after kill |
+
 ## Testing Requirements
 
 ### Unit Tests