archiving tracks
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conductor/archive/tool_usage_analytics_20260306/plan.md
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conductor/archive/tool_usage_analytics_20260306/plan.md
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# Implementation Plan: Tool Usage Analytics (tool_usage_analytics_20260306)
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> **Reference:** [Spec](./spec.md) | [Architecture Guide](../../../docs/guide_architecture.md)
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## Phase 1: Data Collection
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Focus: Add tool execution tracking
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- [ ] Task 1.1: Initialize MMA Environment
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- Run `activate_skill mma-orchestrator` before starting
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- [ ] Task 1.2: Add tool stats state
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- WHERE: `src/app_controller.py` or `src/gui_2.py`
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- WHAT: Add `_tool_stats: dict[str, dict]` state
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- HOW:
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```python
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self._tool_stats: dict[str, dict] = {}
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# Structure: {tool_name: {"count": 0, "total_time_ms": 0, "failures": 0}}
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```
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- CODE STYLE: 1-space indentation
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- [ ] Task 1.3: Hook into tool execution
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- WHERE: `src/ai_client.py` in tool execution path
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- WHAT: Track tool name, time, success/failure
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- HOW:
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```python
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start_time = time.time()
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try:
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result = mcp_client.dispatch(name, args)
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success = True
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except Exception:
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success = False
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finally:
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elapsed_ms = (time.time() - start_time) * 1000
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# Update stats via callback or direct update
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```
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- SAFETY: Don't impact tool execution performance
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## Phase 2: Aggregation Logic
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Focus: Calculate derived metrics
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- [ ] Task 2.1: Implement stats update function
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- WHERE: `src/app_controller.py`
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- WHAT: Function to update tool stats
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- HOW:
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```python
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def _update_tool_stats(self, tool_name: str, elapsed_ms: float, success: bool) -> None:
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if tool_name not in self._tool_stats:
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self._tool_stats[tool_name] = {"count": 0, "total_time_ms": 0.0, "failures": 0}
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self._tool_stats[tool_name]["count"] += 1
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self._tool_stats[tool_name]["total_time_ms"] += elapsed_ms
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if not success:
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self._tool_stats[tool_name]["failures"] += 1
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```
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- [ ] Task 2.2: Calculate average time and failure rate
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- WHERE: `src/gui_2.py` in render function
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- WHAT: Derive avg_time and failure_rate from stats
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- HOW:
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```python
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for tool, stats in self._tool_stats.items():
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count = stats["count"]
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avg_time = stats["total_time_ms"] / count if count > 0 else 0
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failure_rate = (stats["failures"] / count * 100) if count > 0 else 0
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```
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## Phase 3: Visualization
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Focus: Display analytics in GUI
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- [ ] Task 3.1: Add analytics panel
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- WHERE: `src/gui_2.py` in MMA Dashboard or Operations
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- WHAT: Table showing tool stats
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- HOW:
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```python
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if imgui.collapsing_header("Tool Usage Analytics"):
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if imgui.begin_table("tool_stats", 4):
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imgui.table_setup_column("Tool")
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imgui.table_setup_column("Count")
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imgui.table_setup_column("Avg Time (ms)")
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imgui.table_setup_column("Failure %")
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imgui.table_headers_row()
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for tool, stats in sorted(self._tool_stats.items(), key=lambda x: -x[1]["count"]):
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imgui.table_next_row()
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imgui.table_set_column_index(0)
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imgui.text(tool)
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# ... other columns
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imgui.end_table()
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```
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## Phase 4: Reset on Session Clear
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Focus: Clear stats on new session
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- [ ] Task 4.1: Clear stats on session reset
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- WHERE: `src/gui_2.py` or `src/app_controller.py` reset handler
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- WHAT: Clear `_tool_stats` dict
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- HOW: `self._tool_stats.clear()`
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## Phase 5: Testing
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Focus: Verify all functionality
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- [ ] Task 5.1: Write unit tests
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- WHERE: `tests/test_tool_analytics.py` (new file)
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- WHAT: Test stats accumulation, avg calculation
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- HOW: Mock tool execution, verify stats update
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- [ ] Task 5.2: Conductor - Phase Verification
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- Run: `uv run pytest tests/test_tool_analytics.py -v`
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- Manual: Verify analytics panel displays in GUI
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