claude_evening daily review

Analyze today's trading result and write reports/daily/YYYY-MM-DD.md.

Steps

Collect data:
```
python app/ai/evening.py --print
```
Review:
- total trades, win rate, net PnL, fees
- exit reason distribution: TP1 / TP2 / SL / TIME / FORCE
- overtrading: daily entry count, repeated stop losses, TIME/FORCE concentration
- AI filter quality: boosted tickers and blacklists
- execution quality: missing prices, zero-price rows, inconsistent open positions
Strategy changes:
- Do not edit app/config.py directly.
- If a change looks justified, create reports/proposals/YYYY-MM-DD_strategy_proposal.md.
- Include exact proposed values, evidence, sample size, expected benefit, and risk.
- If fewer than 30 closed trades support the change, clearly mark the evidence as insufficient.
- FORCE_EXIT = "14:50" is not changeable.
Live readiness:
- at least 30 closed trades
- recent win rate > 48%
- MDD better than -10%
- Sharpe > 1.0
- stop/kill risk events <= 2
- If all pass, create reports/live_ready/YYYY-MM-DD_READY.md.
Discord: Send a concise result summary. If a proposal file was created, include that manual approval is required.