docs+skills: add main UI/UX visual-truth PRD and skill links

.agents/skills/tradelab-backtest-interpretation/SKILL.md

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+---
+name: tradelab-backtest-interpretation
+description: Use when reviewing TradeLab backtest output so recommendations are grounded in getBacktestResults data and mapped to concrete strategy changes.
+---
+
+# TradeLab Backtest Interpretation
+
+## Overview
+Use `getBacktestResults` output as the source of truth for strategy feedback. Interpret risk and return metrics first, then propose specific code-level changes through the strategy workflow.
+
+## When to Use
+- User asks why strategy performance is good or bad.
+- User asks how to improve a strategy after a backtest.
+- A new `currentBacktestId` is available in context.
+
+## Non-Optional Rules
+1. Retrieve metrics via `getBacktestResults` before proposing optimizations.
+2. Anchor every recommendation to returned fields, not guesses.
+3. Separate analysis into: performance, risk, and action plan.
+4. If code changes are needed, route them through full-class `saveStrategy` flow.
+
+## Metric Interpretation Baselines
+- `sharpeRatio`: `< 1.0` weak, `1.5-2.0` good, `> 2.0` elite.
+- `profitFactor`: `< 1.2` fragile, `1.5-2.5` robust, `> 3.0` possible overfit.
+- `maxDrawdown`: flag if `> 15%`; suggest volatility controls or regime filters.
+- `winRate < 40%`: verify payoff ratio; add entry-quality filters.
+
+## Tool Usage Pattern
+```json
+{
+  "backtestId": "optional-explicit-id",
+  "strategyId": "optional-fallback-id",
+  "includeTrades": false,
+  "metricFilter": ["performance", "risk", "ratios"]
+}
+```
+
+## Output Pattern
+1. State key facts from tool output.
+2. Explain likely failure mode (entries, exits, regime mismatch, risk sizing).
+3. Propose 2-3 prioritized improvements tied to those facts.
+4. If user approves changes, produce full updated class through `saveStrategy`.
+
+## Common Mistakes
+- Recommending changes without calling `getBacktestResults`.
+- Giving generic advice not tied to metric values.
+- Treating high `profitFactor` without checking overfit risk.