hopefully done refining

conductor/tracks/tool_usage_analytics_20260306/spec.md

@@ -1,35 +1,99 @@
 # Track Specification: Tool Usage Analytics (tool_usage_analytics_20260306)
 
 ## Overview
-Analytics panel showing most-used tools, average execution time, failure rates.
+Analytics panel showing most-used tools, average execution time, and failure rates. Uses existing tool execution data from ai_client.
 
 ## Current State Audit
 
-### Already Implemented
-- **`ai_client.tool_log_callback`**: Called when tool executes
-- **`mcp_client.dispatch()`**: Routes tool calls
-- **No aggregation or storage**
+### Already Implemented (DO NOT re-implement)
 
-### Gaps to Fill
-- No tool usage tracking
-- No execution time tracking
+#### Tool Execution (src/ai_client.py)
+- **Tool dispatch in `_execute_tool_calls_concurrently()`**: Executes tools via `mcp_client.dispatch()`
+- **`pre_tool_callback`**: Optional callback before tool execution
+- **No built-in tracking or aggregation**
+
+#### MCP Client (src/mcp_client.py)
+- **`dispatch(name, args)`**: Routes tool calls to implementations
+- **26 tools available** (run_powershell, read_file, py_get_skeleton, etc.)
+- **`MUTATING_TOOLS`**: Set of tools that modify files
+
+### Gaps to Fill (This Track's Scope)
+- No tool usage tracking (count per tool)
+- No execution time tracking per tool
 - No failure rate tracking
+- No analytics display in GUI
+
+## Architectural Constraints
+
+### Efficient Aggregation
+- Track tool stats in lightweight data structure
+- Don't impact tool execution performance
+- Use dict: `{tool_name: {count, total_time, failures}}`
+
+### Memory Bounds
+- Only track stats, not full history
+- Reset on session reset
+
+## Architecture Reference
+
+### Key Integration Points
+
+| File | Lines | Purpose |
+|------|-------|---------|
+| `src/ai_client.py` | ~500-550 | Tool execution - add tracking |
+| `src/gui_2.py` | ~2700-2800 | Analytics panel |
+
+### Proposed Tracking Structure
+```python
+# In AppController or App:
+self._tool_stats: dict[str, dict] = {}
+# Structure: {"read_file": {"count": 10, "total_time_ms": 150, "failures": 0}, ...}
+```
 
 ## Functional Requirements
-- Track tool name, execution time, success/failure
-- Aggregate by tool name
-- Display ranking by usage count
-- Show average time per tool
-- Show failure percentage
 
-## Key Integration Points
-| File | Purpose |
-|-----|---------|
-| `src/ai_client.py` | Hook into tool_log_callback |
-| `src/gui_2.py` | Analytics panel rendering |
+### FR1: Tool Usage Tracking
+- Track tool name, execution time, success/failure
+- Store in `_tool_stats` dict
+- Update on each tool execution
+
+### FR2: Aggregation by Tool
+- Count total calls per tool
+- Calculate average execution time
+- Track failure count and rate
+
+### FR3: Analytics Display
+- Table showing tool name, count, avg time, failure rate
+- Sort by usage count (most used first)
+- Show in MMA Dashboard or Operations panel
+
+## Non-Functional Requirements
+
+| Requirement | Constraint |
+|-------------|------------|
+| Tracking Overhead | <1ms per tool call |
+| Memory | <1KB for stats dict |
+
+## Testing Requirements
+
+### Unit Tests
+- Test tracking updates correctly
+- Test failure rate calculation
+
+### Integration Tests
+- Execute tools, verify stats accumulate
+- Reset session, verify stats cleared
+
+## Out of Scope
+- Historical analytics across sessions
+- Export to file
+- Per-ticket tool breakdown
 
 ## Acceptance Criteria
-- [ ] Tool ranking displayed
-- [ ] Average times accurate
-- [ ] Failure rates tracked
-- [ ] 1-space indentation
+- [ ] Tool execution tracked
+- [ ] Count per tool accurate
+- [ ] Average time calculated
+- [ ] Failure rate shown
+- [ ] Display in GUI panel
+- [ ] Reset on session clear
+- [ ] 1-space indentation maintained