refinement of upcoming tracks
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# Track Specification: Tool Usage Analytics (tool_usage_analytics_20260306)
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## Overview
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Analytics panel showing most-used tools, average execution time, and failure rates. Uses existing tool_log_callback data.
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Analytics panel showing most-used tools, average execution time, failure rates.
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## Architectural Constraints
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- **Efficient Aggregation**: Analytics MUST use efficient data structures.
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- **Memory Bounds**: History MUST be bounded to prevent growth.
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## Current State Audit
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### Already Implemented
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- **`ai_client.tool_log_callback`**: Called when tool executes
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- **`mcp_client.dispatch()`**: Routes tool calls
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- **No aggregation or storage**
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### Gaps to Fill
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- No tool usage tracking
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- No execution time tracking
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- No failure rate tracking
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## Functional Requirements
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- **Usage Ranking**: Show most-used tools ranked by count.
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- **Avg Time**: Display average execution time per tool.
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- **Failure Rate**: Track and display failure percentage per tool.
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- **Time Series**: Show usage over time.
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- Track tool name, execution time, success/failure
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- Aggregate by tool name
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- Display ranking by usage count
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- Show average time per tool
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- Show failure percentage
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## Key Integration Points
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| File | Purpose |
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|-----|---------|
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| `src/ai_client.py` | Hook into tool_log_callback |
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| `src/gui_2.py` | Analytics panel rendering |
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## Acceptance Criteria
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- [ ] Tool ranking displayed.
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- [ ] Average times accurate.
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- [ ] Failure rates tracked.
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- [ ] Time series visualization works.
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- [ ] Uses existing tool_log_callback.
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- [ ] Tool ranking displayed
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- [ ] Average times accurate
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- [ ] Failure rates tracked
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- [ ] 1-space indentation
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