chore(conductor): Archive track 'Add new metrics to track ui performance'

conductor/archive/ui_performance_20260223/spec.md

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+# Specification: UI Performance Metrics and AI Diagnostics
+
+## Overview
+This track aims to resolve subpar UI performance (currently perceived below 60 FPS) by implementing a robust performance monitoring system. This system will collect high-resolution telemetry (Frame Time, Input Lag, Thread Usage) and expose it to both the user (via a Diagnostics Panel) and the AI (via API hooks). This ensures that performance degradation is caught early during development and testing.
+
+## Functional Requirements
+- **Metric Collection Engine:**
+    - Track **Frame Time** (ms) for every frame rendered by Dear PyGui.
+    - Measure **Input Lag** (estimated delay between input events and UI state updates).
+    - Monitor **CPU/Thread Usage**, specifically identifying blocks in the main UI thread.
+- **Diagnostics Panel:**
+    - A new dedicated panel in the GUI to display real-time performance graphs and stats.
+    - Historical trend visualization for frame times to identify spikes.
+- **AI API Hooks:**
+    - **Polling Tool:** A tool (e.g., `get_ui_performance`) that allows the AI to request a snapshot of current telemetry.
+    - **Event-Driven Alerts:** A mechanism to notify the AI (or append to history) when performance metrics cross a "degradation" threshold (e.g., frame time > 33ms).
+- **Performance Optimization:**
+    - Identify the "heavy" process currently running in the main UI thread loop.
+    - Refactor identified bottlenecks to utilize background workers or optimized logic.
+
+## Non-Functional Requirements
+- **Low Overhead:** The monitoring system itself must not significantly impact UI performance (target <1% CPU overhead).
+- **Accuracy:** Frame timings must be accurate to sub-millisecond resolution.
+
+## Acceptance Criteria
+- [ ] UI consistently maintains "Smooth Frame Timing" (minimized spikes) under normal load.
+- [ ] Main thread load is reduced, evidenced by metrics showing less than 50% busy time during idle/light use.
+- [ ] AI can successfully retrieve performance data using the `get_ui_performance` tool.
+- [ ] AI is alerted when a simulated performance drop occurs.
+- [ ] The Diagnostics Panel displays live, accurate data.
+
+## Out of Scope
+- GPU-specific profiling (e.g., VRAM usage, shader timings).
+- Remote telemetry/analytics (data stays local).