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

conductor/tracks.md

@@ -12,3 +12,8 @@ This file tracks all major tracks for the project. Each track has its own detail
 - [x] **Track: Review vendor api usage in regards to conservative context handling**
   *Link: [./tracks/api_metrics_20260223/](./tracks/api_metrics_20260223/)*
 
+---
+
+- [ ] **Track: Add new metrics to track ui performance (frametimings, fps, input lag, etc). And api hooks so that ai may engage with them.**
+  *Link: [./tracks/ui_performance_20260223/](./tracks/ui_performance_20260223/)*
+

conductor/tracks/ui_performance_20260223/index.md

@@ -0,0 +1,5 @@
+# Track ui_performance_20260223 Context
+
+- [Specification](./spec.md)
+- [Implementation Plan](./plan.md)
+- [Metadata](./metadata.json)

conductor/tracks/ui_performance_20260223/metadata.json

@@ -0,0 +1,8 @@
+{
+  "track_id": "ui_performance_20260223",
+  "type": "feature",
+  "status": "new",
+  "created_at": "2026-02-23T14:45:00Z",
+  "updated_at": "2026-02-23T14:45:00Z",
+  "description": "Add new metrics to track ui performance (frametimings, fps, input lag, etc). And api hooks so that ai may engage with them."
+}

conductor/tracks/ui_performance_20260223/plan.md

@@ -0,0 +1,31 @@
+# Implementation Plan: UI Performance Metrics and AI Diagnostics
+
+## Phase 1: High-Resolution Telemetry Engine
+- [ ] Task: Implement core performance collector (FrameTime, CPU usage)
+    - [ ] Sub-task: Write Tests (validate metric collection accuracy)
+    - [ ] Sub-task: Implement Feature (create `PerformanceMonitor` class)
+- [ ] Task: Integrate collector with Dear PyGui main loop
+    - [ ] Sub-task: Write Tests (verify integration doesn't crash loop)
+    - [ ] Sub-task: Implement Feature (hooks in `gui.py` or `gui_2.py`)
+- [ ] Task: Implement Input Lag estimation logic
+    - [ ] Sub-task: Write Tests (simulated input vs. response timing)
+    - [ ] Sub-task: Implement Feature (event-based timing in GUI)
+- [ ] Task: Conductor - User Manual Verification 'Phase 1: High-Resolution Telemetry Engine' (Protocol in workflow.md)
+
+## Phase 2: AI Tooling and Alert System
+- [ ] Task: Create `get_ui_performance` AI tool
+    - [ ] Sub-task: Write Tests (verify tool returns correct JSON schema)
+    - [ ] Sub-task: Implement Feature (add tool to `mcp_client.py`)
+- [ ] Task: Implement performance threshold alert system
+    - [ ] Sub-task: Write Tests (verify alerts trigger at correct thresholds)
+    - [ ] Sub-task: Implement Feature (logic to inject messages into `ai_client.py` context)
+- [ ] Task: Conductor - User Manual Verification 'Phase 2: AI Tooling and Alert System' (Protocol in workflow.md)
+
+## Phase 3: Diagnostics UI and Optimization
+- [ ] Task: Build the Diagnostics Panel in Dear PyGui
+    - [ ] Sub-task: Write Tests (verify panel components render)
+    - [ ] Sub-task: Implement Feature (plots, stat readouts in `gui.py`)
+- [ ] Task: Identify and fix main thread performance bottlenecks
+    - [ ] Sub-task: Write Tests (reproducible "heavy" load test)
+    - [ ] Sub-task: Implement Feature (refactor heavy logic to workers)
+- [ ] Task: Conductor - User Manual Verification 'Phase 3: Diagnostics UI and Optimization' (Protocol in workflow.md)

conductor/tracks/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).