Extract three to five plain-language trading rules from profitable trades, then test them across Chinese A-shares, Hong Kong stocks, US stocks, and crypto. Produce a report comparing simulated and actual results, with a breakdown of differences.
Shadow Account — 从用户交割单提炼盈利模式（3-5 条人话规则）→ 跨 A股/港股/美股/crypto 多市场回测 → 差值归因 → 8-section PDF 报告。叙事：你的影子，没有情绪噪音。
Review the instructions the agent will receive before you install.
当用户说 "提炼我的策略" / "训练影子" / "我的打法回测一下" / "我能多赚多少" / "我的盈利模式" 时，加载此 skill。
前提：用户已上传交割单且 analyze_trade_journal 已跑过。若没有，先跑 Phase 4a 工具。
extract_shadow_strategy(journal_path=...)
shadow_id + 3-5 条人话规则min_support 重跑run_shadow_backtest(shadow_id=..., journal_path=...)
delta_pnl + attribution breakdownrender_shadow_report(shadow_id=...)
html_path / pdf_path / delta_pnlscan_shadow_signals(shadow_id=...) — 今日落在影子入场窗口的标的列表（研究用）每条规则含：rule_id、human_text（≤30 字）、support_count、coverage_rate、holding_days_range。规则不是"必赚公式"，而是"用户盈利时的共性画像"。
per_market：四市场的 Sharpe/年化/最大回撤combined：合并池表现equity_curve：净值时序（进入 PDF Section 3）所有数值 signed，正值=影子相对赚更多：
noise_trades_pnl：不命中任何规则的真实交易累计 PnL（用户的情绪单）early_exit_pnl：赢单但持仓 < 规则下限，按不足比例折算的机会成本late_exit_pnl：亏单但持仓 > 规则上限，按超额比例折算的放大损失overtrading_pnl：超出规则频率的真实交易 PnLmissed_signals_pnl：残差（shadow_pnl − real_pnl − 上面四项之和）按 |impact| 排序，列出 5 条"最该做没做 / 最不该做却做了"的交易，带具体日期、原因。
确认规则：
从你 {profitable_roundtrips} 笔盈利回合中提炼出这些规则：{rules}。这些看起来像你本人的打法吗？
展示差值（Section 5）：
影子 PnL {shadow_pnl:+.0f} / 你真实 {real_pnl:+.0f} / 差值 {delta_pnl:+.0f}。其中 {noise_trades_pnl:+.0f} 来自不符合你任何盈利规则的"情绪单"。
今日扫描（强制附带免责）：
今日落在你影子入场节奏的标的：{symbols}。仅研究用，不是买入建议。
当 extract_shadow_strategy 被调用时，可以注入一个 llm_translator callable 以把结构化 entry_condition 翻译成中文自然语言：
[上下文] 一位散户的盈利回合中，{N} 笔满足同一组条件：
market = {market}
entry_hour ∈ [{hour_min}, {hour_max}]
持有 {hold_lo}-{hold_hi} 天
[任务] 用 ≤30 字的中文写一条规则，口吻像用户自述的交易习惯，不要堆术语。
[输出] 只返回一行规则文本，不要解释。
不注入时走 f-string 模板（见 extractor._translate_rule）。
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