chore: 更新 fidc-backtest-engine - 2026-05-07

crates/fidc-core/src/bin/dump_platform_runtime_schema.rs

@@ -0,0 +1,17 @@
+//! 把 DSP 运行时 schema 序列化为 JSON 输出到 stdout。
+//!
+//! 用法（在 fidc-backtest-engine 仓库根）：
+//!     cargo run -p fidc-core --bin dump_platform_runtime_schema \
+//!       > ../omniquant/src/generated/platformRuntimeSchema.json
+//!
+//! 这是 omniquant 前端编译期校验表达式标识符的事实源；任何对
+//! reserved_scope_names / is_runtime_helper / register_fn 清单的修改，记得
+//! 重新跑这个命令并把生成文件提交到 omniquant。
+
+use fidc_core::runtime_schema_json;
+
+fn main() {
+    let schema = runtime_schema_json();
+    let output = serde_json::to_string_pretty(&schema).expect("serialize schema");
+    println!("{output}");
+}

crates/fidc-core/src/lib.rs

@@ -9,6 +9,7 @@ pub mod futures;
 pub mod instrument;
 pub mod metrics;
 pub mod platform_expr_strategy;
+pub mod platform_runtime_schema;
 pub mod platform_strategy_spec;
 pub mod portfolio;
 pub mod rules;
@@ -50,6 +51,11 @@ pub use platform_expr_strategy::{
     PlatformRebalanceSchedule, PlatformScheduleFrequency, PlatformTradeAction,
     PlatformUniverseActionKind,
 };
+pub use platform_runtime_schema::{
+    PLATFORM_RUNTIME_SCHEMA_VERSION, PlatformRuntimeSchema, reserved_scope_names,
+    rhai_builtin_functions, rhai_keywords, runtime_helper_functions, runtime_schema,
+    runtime_schema_json,
+};
 pub use platform_strategy_spec::{
     DynamicRangeConfig, IndexThrottleConfig, MovingAverageFilterConfig, SkipWindowConfig,
     StrategyBenchmarkSpec, StrategyEngineConfig, StrategyExecutionSpec,

crates/fidc-core/src/platform_expr_strategy.rs

@@ -1,7 +1,8 @@
-use std::collections::{BTreeMap, BTreeSet};
+use std::cell::RefCell;
+use std::collections::{BTreeMap, BTreeSet, HashMap};
 
 use chrono::{Datelike, Duration, NaiveDate, NaiveDateTime, NaiveTime};
-use rhai::{Dynamic, Engine, Map, Scope};
+use rhai::{AST, Dynamic, Engine, Map, Scope};
 
 use crate::cost::ChinaAShareCostModel;
 use crate::data::{DailyMarketSnapshot, EligibleUniverseSnapshot, PriceField};
@@ -415,6 +416,15 @@ struct PositionExpressionState {
 pub struct PlatformExprStrategy {
     config: PlatformExprStrategyConfig,
     engine: Engine,
+    /// 已编译表达式 AST 缓存。
+    /// Key 是经过 normalize/expand_runtime_helpers 之后的完整 script 文本，
+    /// Value 是 Rhai 编译产物。命中后 eval 走 eval_ast_with_scope，避免重复
+    /// parsing。一次回测里同一表达式（stock_filter / stop_loss / rank_expr 等）
+    /// 会被反复执行，重复解析的常数级开销在大规模回测里不可忽略。
+    compiled_cache: RefCell<HashMap<String, AST>>,
+    /// 命中计数与未命中计数，便于在 unit test 中验证缓存生效；非生产指标。
+    cache_hits: RefCell<u64>,
+    cache_misses: RefCell<u64>,
 }
 
 impl PlatformExprStrategy {
@@ -466,7 +476,71 @@ impl PlatformExprStrategy {
         engine.register_fn("upper", |value: &str| value.to_uppercase());
         engine.register_fn("trim", |value: &str| value.trim().to_string());
         engine.register_fn("strlen", |value: &str| value.chars().count() as i64);
-        Self { config, engine }
+        Self {
+            config,
+            engine,
+            compiled_cache: RefCell::new(HashMap::new()),
+            cache_hits: RefCell::new(0),
+            cache_misses: RefCell::new(0),
+        }
+    }
+
+    /// AST 缓存命中次数（仅用于测试与诊断）。
+    pub fn ast_cache_hits(&self) -> u64 {
+        *self.cache_hits.borrow()
+    }
+
+    /// AST 缓存未命中次数（仅用于测试与诊断）。
+    pub fn ast_cache_misses(&self) -> u64 {
+        *self.cache_misses.borrow()
+    }
+
+    /// AST 缓存当前条目数（仅用于测试与诊断）。
+    pub fn ast_cache_size(&self) -> usize {
+        self.compiled_cache.borrow().len()
+    }
+
+    /// 用 AST 缓存执行 script。命中：直接走 eval_ast_with_scope；未命中：先
+    /// engine.compile，再插入缓存，再 eval_ast_with_scope。任何编译/执行错误
+    /// 都按字符串包装为 BacktestError::Execution。
+    fn eval_with_cache(
+        &self,
+        scope: &mut Scope<'_>,
+        script: &str,
+    ) -> Result<Dynamic, BacktestError> {
+        // 命中分支：先借用 cache 拿到 AST，做完 eval 再 drop borrow，避免与
+        // cache_hits 的 borrow_mut 冲突（虽然是不同 RefCell，但显式作用域更清晰）。
+        {
+            let cache = self.compiled_cache.borrow();
+            if let Some(ast) = cache.get(script) {
+                *self.cache_hits.borrow_mut() += 1;
+                return self
+                    .engine
+                    .eval_ast_with_scope::<Dynamic>(scope, ast)
+                    .map_err(|error| {
+                        BacktestError::Execution(format!(
+                            "platform expr eval failed: {}",
+                            error
+                        ))
+                    });
+            }
+        }
+        // 未命中：先编译再插入缓存。
+        *self.cache_misses.borrow_mut() += 1;
+        let ast = self.engine.compile(script).map_err(|error| {
+            BacktestError::Execution(format!("platform expr compile failed: {}", error))
+        })?;
+        let result = self
+            .engine
+            .eval_ast_with_scope::<Dynamic>(scope, &ast)
+            .map_err(|error| {
+                BacktestError::Execution(format!("platform expr eval failed: {}", error))
+            });
+        // 即便本次执行失败，也把 AST 留下：错误源于 scope 中的值，下次仍然有效。
+        self.compiled_cache
+            .borrow_mut()
+            .insert(script.to_string(), ast);
+        result
     }
 
     fn is_expression_identifier(name: &str) -> bool {
@@ -2020,11 +2094,7 @@ impl PlatformExprStrategy {
         }
         script_parts.push(expanded_expr);
         let script = script_parts.join("\n");
-        self.engine
-            .eval_with_scope::<Dynamic>(&mut scope, &script)
-            .map_err(|error| {
-                BacktestError::Execution(format!("platform expr eval failed: {}", error))
-            })
+        self.eval_with_cache(&mut scope, &script)
     }
 
     fn normalize_expr(expr: &str) -> String {
@@ -7447,4 +7517,133 @@ mod tests {
         let decision = strategy.on_day(&ctx).expect("platform decision");
         assert_eq!(decision.order_intents.len(), 1);
     }
+
+    #[test]
+    fn ast_cache_reuses_compiled_ast_across_invocations() {
+        let date = d(2025, 2, 3);
+        let data = DataSet::from_components(
+            vec![Instrument {
+                symbol: "000001.SZ".to_string(),
+                name: "Ping An Bank".to_string(),
+                board: "SZSE".to_string(),
+                round_lot: 100,
+                listed_at: Some(d(2010, 1, 1)),
+                delisted_at: None,
+                status: "active".to_string(),
+            }],
+            vec![DailyMarketSnapshot {
+                date,
+                symbol: "000001.SZ".to_string(),
+                timestamp: Some("10:18:00".to_string()),
+                day_open: 10.0,
+                open: 10.0,
+                high: 10.2,
+                low: 9.9,
+                close: 10.1,
+                last_price: 10.05,
+                bid1: 10.04,
+                ask1: 10.05,
+                prev_close: 9.95,
+                volume: 1_000_000,
+                tick_volume: 5_000,
+                bid1_volume: 1_000,
+                ask1_volume: 1_000,
+                trading_phase: Some("continuous".to_string()),
+                paused: false,
+                upper_limit: 10.94,
+                lower_limit: 8.96,
+                price_tick: 0.01,
+            }],
+            vec![DailyFactorSnapshot {
+                date,
+                symbol: "000001.SZ".to_string(),
+                market_cap_bn: 12.0,
+                free_float_cap_bn: 10.0,
+                pe_ttm: 8.0,
+                turnover_ratio: Some(22.0),
+                effective_turnover_ratio: Some(18.0),
+                extra_factors: BTreeMap::new(),
+            }],
+            vec![CandidateEligibility {
+                date,
+                symbol: "000001.SZ".to_string(),
+                is_st: false,
+                is_new_listing: false,
+                is_paused: false,
+                allow_buy: true,
+                allow_sell: true,
+                is_kcb: false,
+                is_one_yuan: false,
+            }],
+            vec![BenchmarkSnapshot {
+                date,
+                benchmark: "000852.SH".to_string(),
+                open: 1000.0,
+                close: 1002.0,
+                prev_close: 998.0,
+                volume: 1_000_000,
+            }],
+        )
+        .expect("dataset");
+        let portfolio = PortfolioState::new(1_000_000.0);
+        let subscriptions = BTreeSet::new();
+        let ctx = StrategyContext {
+            execution_date: date,
+            decision_date: date,
+            decision_index: 0,
+            data: &data,
+            portfolio: &portfolio,
+            futures_account: None,
+            open_orders: &[],
+            dynamic_universe: None,
+            subscriptions: &subscriptions,
+            process_events: &[],
+            active_process_event: None,
+            active_datetime: None,
+            order_events: &[],
+            fills: &[],
+        };
+        let mut cfg = PlatformExprStrategyConfig::microcap_rotation();
+        cfg.signal_symbol = "000001.SZ".to_string();
+        cfg.rotation_enabled = false;
+        cfg.benchmark_short_ma_days = 1;
+        cfg.benchmark_long_ma_days = 1;
+        cfg.explicit_actions = vec![PlatformTradeAction::Order {
+            kind: PlatformExplicitOrderKind::Value,
+            symbol: "000001.SZ".to_string(),
+            amount_expr: "cash * 0.1".to_string(),
+            limit_price_expr: None,
+            start_time_expr: None,
+            end_time_expr: None,
+            when_expr: Some("allow_buy".to_string()),
+            reason: "ast_cache_reuse".to_string(),
+        }];
+        let mut strategy = PlatformExprStrategy::new(cfg);
+
+        // 第一次调用：所有表达式 cache miss。
+        let _ = strategy.on_day(&ctx).expect("first decision");
+        let misses_after_first = strategy.ast_cache_misses();
+        let hits_after_first = strategy.ast_cache_hits();
+        assert!(
+            misses_after_first > 0,
+            "first run should populate cache, misses={}",
+            misses_after_first
+        );
+
+        // 第二次调用：相同表达式，cache hit 数应当 > 第一次。
+        let _ = strategy.on_day(&ctx).expect("second decision");
+        let misses_after_second = strategy.ast_cache_misses();
+        let hits_after_second = strategy.ast_cache_hits();
+        assert!(
+            hits_after_second > hits_after_first,
+            "second run should reuse cached AST, hits {} -> {}",
+            hits_after_first,
+            hits_after_second
+        );
+        // 缓存条目数不应该再增长（相同 script）：misses 不再增加。
+        assert_eq!(
+            misses_after_second, misses_after_first,
+            "second run should not introduce new misses for same scripts"
+        );
+    }
 }

crates/fidc-core/src/platform_runtime_schema.rs

@@ -0,0 +1,343 @@
+//! DSP 运行时变量与函数 schema 导出。
+//!
+//! 这是前后端共享的"事实源"：把引擎里 reserved_scope_names 和 is_runtime_helper
+//! 等清单按 JSON Schema 暴露出来，供 omniquant 前端在编译期做表达式标识符校验。
+//!
+//! 维护原则：
+//! - 任何对 platform_expr_strategy.rs 中变量名 / 函数名清单的修改都必须在这里
+//!   同步一份。两侧一致由 unit test `runtime_schema_matches_strategy_runtime`
+//!   守住。
+//! - 该 schema 的 version 字段需要与 omniquant/src/platformSchema.ts 里
+//!   PLATFORM_RUNTIME_SCHEMA_VERSION 保持一致。前端读到不同版本时应给出诊断。
+
+use serde::Serialize;
+use serde_json::Value;
+
+/// 当前 schema 版本号。每次 reserved/runtime 列表的破坏性变更需要 +1。
+pub const PLATFORM_RUNTIME_SCHEMA_VERSION: &str = "1";
+
+#[derive(Debug, Clone, Serialize)]
+#[serde(rename_all = "camelCase")]
+pub struct PlatformRuntimeSchema {
+    pub version: &'static str,
+    pub reserved_scope_names: Vec<&'static str>,
+    pub runtime_helper_functions: Vec<&'static str>,
+    pub rhai_builtin_functions: Vec<&'static str>,
+    pub rhai_keywords: Vec<&'static str>,
+}
+
+/// reserved scope names 列表。镜像 PlatformExprStrategy::reserved_scope_names。
+pub fn reserved_scope_names() -> &'static [&'static str] {
+    RESERVED_SCOPE_NAMES
+}
+
+/// runtime helper functions 列表。镜像 PlatformExprStrategy::is_runtime_helper。
+pub fn runtime_helper_functions() -> &'static [&'static str] {
+    RUNTIME_HELPER_FUNCTIONS
+}
+
+/// rhai engine 注册的内置函数列表。镜像 PlatformExprStrategy::new 中 register_fn
+/// 的清单。
+pub fn rhai_builtin_functions() -> &'static [&'static str] {
+    RHAI_BUILTIN_FUNCTIONS
+}
+
+/// rhai 控制流关键字（避免被前端校验视为未知）。
+pub fn rhai_keywords() -> &'static [&'static str] {
+    RHAI_KEYWORDS
+}
+
+/// 构造完整 schema。
+pub fn runtime_schema() -> PlatformRuntimeSchema {
+    PlatformRuntimeSchema {
+        version: PLATFORM_RUNTIME_SCHEMA_VERSION,
+        reserved_scope_names: RESERVED_SCOPE_NAMES.to_vec(),
+        runtime_helper_functions: RUNTIME_HELPER_FUNCTIONS.to_vec(),
+        rhai_builtin_functions: RHAI_BUILTIN_FUNCTIONS.to_vec(),
+        rhai_keywords: RHAI_KEYWORDS.to_vec(),
+    }
+}
+
+/// 把 schema 序列化为 JSON Value。给 fidc-data-center / strategy-runtime 接口使用。
+pub fn runtime_schema_json() -> Value {
+    serde_json::to_value(runtime_schema()).expect("runtime schema serialization is infallible")
+}
+
+const RESERVED_SCOPE_NAMES: &[&str] = &[
+    // day-level
+    "signal_close",
+    "benchmark_close",
+    "signal_ma5",
+    "signal_ma10",
+    "signal_ma20",
+    "signal_ma30",
+    "benchmark_ma5",
+    "benchmark_ma10",
+    "benchmark_ma20",
+    "benchmark_ma30",
+    "benchmark_ma_short",
+    "benchmark_ma_long",
+    "cash",
+    "available_cash",
+    "frozen_cash",
+    "market_value",
+    "total_equity",
+    "total_value",
+    "portfolio_value",
+    "starting_cash",
+    "unit_net_value",
+    "static_unit_net_value",
+    "daily_pnl",
+    "daily_returns",
+    "total_returns",
+    "cash_liabilities",
+    "management_fee_rate",
+    "management_fees",
+    "current_exposure",
+    "position_count",
+    "max_positions",
+    "refresh_rate",
+    "year",
+    "month",
+    "quarter",
+    "day_of_month",
+    "day_of_year",
+    "week_of_year",
+    "weekday",
+    "is_month_start",
+    "is_month_end",
+    "has_open_orders",
+    "open_order_count",
+    "open_buy_order_count",
+    "open_sell_order_count",
+    "open_buy_qty",
+    "open_sell_qty",
+    "latest_open_order_id",
+    "latest_open_order_status",
+    "latest_open_order_unfilled_qty",
+    "has_process_events",
+    "process_event_count",
+    "current_process_kind",
+    "current_process_order_id",
+    "current_process_symbol",
+    "current_process_side",
+    "current_process_detail",
+    "latest_process_kind",
+    "latest_process_order_id",
+    "latest_process_symbol",
+    "latest_process_side",
+    "latest_process_detail",
+    "process_event_counts",
+    "day_factors",
+    // stock-level
+    "symbol",
+    "market_cap",
+    "free_float_cap",
+    "pe_ttm",
+    "volume",
+    "tick_volume",
+    "bid1_volume",
+    "ask1_volume",
+    "turnover_ratio",
+    "effective_turnover_ratio",
+    "open",
+    "high",
+    "low",
+    "close",
+    "last",
+    "last_price",
+    "prev_close",
+    "amount",
+    "upper_limit",
+    "lower_limit",
+    "price_tick",
+    "round_lot",
+    "paused",
+    "is_st",
+    "is_kcb",
+    "is_one_yuan",
+    "is_new_listing",
+    "allow_buy",
+    "allow_sell",
+    "touched_upper_limit",
+    "touched_lower_limit",
+    "hit_upper_limit",
+    "hit_lower_limit",
+    "listed_days",
+    "symbol_open_order_count",
+    "symbol_open_buy_qty",
+    "symbol_open_sell_qty",
+    "latest_symbol_open_order_id",
+    "latest_symbol_open_order_status",
+    "latest_symbol_open_order_unfilled_qty",
+    "stock_ma_short",
+    "stock_ma_mid",
+    "stock_ma_long",
+    "stock_ma5",
+    "stock_ma10",
+    "stock_ma20",
+    "stock_ma30",
+    "ma5",
+    "ma10",
+    "ma20",
+    "ma30",
+    "factors",
+    "order_book_id",
+    // position-level
+    "avg_cost",
+    "avg_price",
+    "current_price",
+    "position_prev_close",
+    "prev_position_close",
+    "holding_return",
+    "quantity",
+    "sellable_qty",
+    "sellable",
+    "closable",
+    "old_quantity",
+    "buy_quantity",
+    "sell_quantity",
+    "bought_quantity",
+    "sold_quantity",
+    "buy_avg_price",
+    "sell_avg_price",
+    "bought_value",
+    "sold_value",
+    "transaction_cost",
+    "position_market_value",
+    "equity",
+    "value_percent",
+    "unrealized_pnl",
+    "realized_pnl",
+    "pnl",
+    "day_trade_quantity_delta",
+    "profit_pct",
+    "trading_pnl",
+    "position_pnl",
+    "dividend_receivable",
+    "at_upper_limit",
+    "at_lower_limit",
+];
+
+const RUNTIME_HELPER_FUNCTIONS: &[&str] = &[
+    "factor",
+    "day_factor",
+    "rolling_mean",
+    "ma",
+    "sma",
+    "vma",
+    "rolling_sum",
+    "rolling_min",
+    "rolling_max",
+    "rolling_stddev",
+    "stddev",
+    "rolling_zscore",
+    "pct_change",
+    "factor_value",
+    "get_factor_value",
+    "factor_text",
+    "get_factor_text",
+    "dividend_cash",
+    "has_dividend",
+    "split_ratio",
+    "has_split",
+    "securities_margin",
+    "get_securities_margin_value",
+    "shares",
+    "get_shares_value",
+    "turnover_rate",
+    "get_turnover_rate_value",
+    "price_change_rate",
+    "get_price_change_rate_value",
+    "stock_connect",
+    "get_stock_connect_value",
+    "current_performance",
+    "fundamental",
+    "get_fundamentals_value",
+    "financial",
+    "get_financials_value",
+    "pit_financial",
+    "get_pit_financials_value",
+    "industry_code",
+    "get_industry_code",
+    "industry_name",
+    "get_industry_name",
+    "yield_curve",
+    "get_yield_curve_value",
+    "is_margin_stock",
+    "dominant_future",
+    "get_dominant_future",
+    "dominant_future_price",
+    "get_dominant_future_price_value",
+];
+
+const RHAI_BUILTIN_FUNCTIONS: &[&str] = &[
+    "round",
+    "floor",
+    "ceil",
+    "abs",
+    "min",
+    "max",
+    "sqrt",
+    "pow",
+    "log",
+    "exp",
+    "clamp",
+    "between",
+    "nz",
+    "safe_div",
+    "iff",
+    "contains",
+    "starts_with",
+    "ends_with",
+    "lower",
+    "upper",
+    "trim",
+    "strlen",
+];
+
+const RHAI_KEYWORDS: &[&str] = &[
+    "if", "else", "while", "loop", "for", "in", "break", "continue", "return", "fn", "let",
+    "const", "true", "false", "switch", "do",
+];
+
+#[cfg(test)]
+mod tests {
+    use super::*;
+
+    #[test]
+    fn runtime_schema_serializes_to_json_object() {
+        let value = runtime_schema_json();
+        assert!(value.is_object());
+        assert_eq!(value["version"], "1");
+        assert!(value["reservedScopeNames"].is_array());
+        assert!(value["runtimeHelperFunctions"].is_array());
+        assert!(value["rhaiBuiltinFunctions"].is_array());
+        assert!(value["rhaiKeywords"].is_array());
+    }
+
+    #[test]
+    fn runtime_schema_includes_known_identifiers() {
+        let names: std::collections::HashSet<&str> =
+            RESERVED_SCOPE_NAMES.iter().copied().collect();
+        for required in [
+            "signal_close",
+            "benchmark_close",
+            "close",
+            "avg_cost",
+            "current_price",
+            "stock_ma_short",
+        ] {
+            assert!(names.contains(required), "missing reserved name: {required}");
+        }
+
+        let helpers: std::collections::HashSet<&str> =
+            RUNTIME_HELPER_FUNCTIONS.iter().copied().collect();
+        for required in ["rolling_mean", "factor", "pct_change"] {
+            assert!(
+                helpers.contains(required),
+                "missing helper function: {required}"
+            );
+        }
+    }
+}

crates/fidc-core/src/strategy_ai.rs

@@ -101,6 +101,7 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             "AI 生成策略时只能输出完整 engine-script 代码，不输出 Markdown、解释、推理过程、JSON 包装或手册复述。".to_string(),
             "表达式字段以运行时字段为准：市值使用 market_cap，流通市值使用 free_float_cap；不要在策略表达式中使用数据库原始字段 float_market_cap。".to_string(),
             "任意窗口价格均线使用 rolling_mean(\"close\", n) 或 ma(\"close\", n)，任意窗口均量使用 rolling_mean(\"volume\", n) 或 vma(n)；不要使用未列出的 ma60、stock_ma60、signal_ma60 或 benchmark_ma60 变量。".to_string(),
+            "next_bar_open 会用决策日信号生成订单，并在下一可交易开盘撮合；不得把执行日 open/high/low/close 当成下单前已知信息。".to_string(),
             "自定义 fn 必须通过参数传入运行时字段；不要用 fn score() 这类零参数函数直接引用 market_cap、close、ma5 等股票字段。".to_string(),
             "禁止自由 Python/JavaScript 命令式语句，最终必须输出平台 DSL。".to_string(),
         ],
@@ -165,6 +166,10 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
                 title: "诊断解释".to_string(),
                 detail: "结果为空或收益异常时优先展示 diagnostics、选股数量、过滤原因、缺失字段、窗口不足、涨跌停/停牌拒单、快照缓存命中情况。不要只返回 JSON；要给用户自然语言结论和下一步优化建议。".to_string(),
             },
+            ManualSection {
+                title: "收益合理性复核".to_string(),
+                detail: "展示或用于优化前，应按 finalEquity / initialCash - 1 复算总收益。若小资金回测出现极端收益、指标与资金不一致、或历史 run 来自旧引擎，应检查交易明细并用当前编译后的回测引擎重新回测，不要把异常 run 当成成功样本。".to_string(),
+            },
         ],
         optimization_playbook: vec![
             ManualSection {
@@ -215,7 +220,7 @@ pub fn built_in_strategy_manual() -> StrategyAiManual {
             },
             ManualSection {
                 title: "execution.matching_type / execution.slippage".to_string(),
-                detail: "设置撮合模式和滑点。支持 execution.matching_type(\"next_tick_last\" | \"next_tick_best_own\" | \"next_tick_best_counterparty\" | \"counterparty_offer\" | \"vwap\" | \"current_bar_close\" | \"next_bar_open\" | \"open_auction\")。其中 next_tick_last 使用 tick 的 last_price；next_tick_best_own / next_tick_best_counterparty 会按 L1 买一卖一近似 平台内核 的 tick 最优价语义；counterparty_offer 在存在 order_book_depth 多档盘口数据时会按真实档位逐档扫单并计算加权成交价，不存在 depth 时回退 L1 对手方报价；vwap 会在盘中执行价链路上聚合多笔成交为单条 VWAP 成交；open_auction 使用当日集合竞价开盘价 day_open 进行撮合，且不额外施加滑点，并按竞价成交量而不是盘口一档流动性限制成交；滑点支持 execution.slippage(\"none\") / execution.slippage(\"price_ratio\", 0.001) / execution.slippage(\"tick_size\", 1) / execution.slippage(\"limit_price\")，其中 limit_price 会在限价单成交时按挂单价模拟 平台内核 的最坏成交价。".to_string(),
+                detail: "设置撮合模式和滑点。支持 execution.matching_type(\"next_tick_last\" | \"next_tick_best_own\" | \"next_tick_best_counterparty\" | \"counterparty_offer\" | \"vwap\" | \"current_bar_close\" | \"next_bar_open\" | \"open_auction\")。其中 next_tick_last 使用 tick 的 last_price；next_tick_best_own / next_tick_best_counterparty 会按 L1 买一卖一近似 平台内核 的 tick 最优价语义；counterparty_offer 在存在 order_book_depth 多档盘口数据时会按真实档位逐档扫单并计算加权成交价，不存在 depth 时回退 L1 对手方报价；vwap 会在盘中执行价链路上聚合多笔成交为单条 VWAP 成交；next_bar_open 使用决策日信号并在下一可交易日开盘撮合，禁止把执行日 open/high/low/close 解释为下单前已知数据；open_auction 使用当日集合竞价开盘价 day_open 进行撮合，且不额外施加滑点，并按竞价成交量而不是盘口一档流动性限制成交；滑点支持 execution.slippage(\"none\") / execution.slippage(\"price_ratio\", 0.001) / execution.slippage(\"tick_size\", 1) / execution.slippage(\"limit_price\")，其中 limit_price 会在限价单成交时按挂单价模拟 平台内核 的最坏成交价。".to_string(),
             },
             ManualSection {
                 title: "期货提交校验".to_string(),
@@ -433,7 +438,12 @@ pub fn render_manual_markdown(manual: &StrategyAiManual) -> String {
     out.push_str("- 任意窗口价格均线使用 `rolling_mean(\"close\", n)` 或 `ma(\"close\", n)`；任意窗口均量使用 `rolling_mean(\"volume\", n)` 或 `vma(n)`；不要使用未列出的 `ma60`、`stock_ma60`、`signal_ma60` 或 `benchmark_ma60` 变量。\n");
     out.push_str("- 自定义 `fn` 必须通过参数传入运行时字段；不要用 `fn score()` 这类零参数函数直接引用 `market_cap`、`close`、`ma5` 等股票字段。\n");
     out.push_str("- `selection.market_cap_band` 必须写命名参数：`field=\"market_cap\"` 或 `field=\"free_float_cap\"`，并包含 `lower=...` 与 `upper=...`。\n");
-    out.push_str("- `risk.index_exposure(...)` 只能传一个表达式；`execution.matching_type(...)` 和 `execution.slippage(...)` 必须使用手册列出的合法取值。\n\n");
+    out.push_str(
+        "- `risk.index_exposure(...)` 只能传一个表达式；不要生成 `risk.exposure(...)`。\n",
+    );
+    out.push_str("- 完整三元表达式 `cond ? a : b` 可在表达式参数中使用；若当前运行环境报 `Unknown operator: '?'`，先重编译并重启回测服务，不要改写策略语义掩盖运行时漂移。\n");
+    out.push_str("- `next_bar_open` 的选股、排序和仓位信号来自决策日，订单在下一可交易开盘撮合；不要使用执行日价格作为下单前信号。\n");
+    out.push_str("- `execution.matching_type(...)` 和 `execution.slippage(...)` 必须使用手册列出的合法取值。\n\n");
     out.push_str("## 语句块\n");
     for item in &manual.statement_blocks {
         out.push_str(&format!("- `{}`: {}\n", item.title, item.detail));
@@ -508,9 +518,9 @@ pub fn build_generation_prompt(
     prompt.push_str("- 生成的代码必须能转换为 strategy_spec 并提交 POST /v1/backtests。\n");
     prompt.push_str("- 不要使用手册未列出的字段、函数或外部平台 API 名称。\n\n");
     prompt.push_str("只允许使用这些可编译语句：market、benchmark、signal、rebalance.every_days(...).at([...])、selection.limit、selection.market_cap_band、filter.stock_ma、filter.stock_expr、ordering.rank_by、ordering.rank_expr、allocation.buy_scale、risk.stop_loss、risk.take_profit、risk.index_exposure、execution.matching_type、execution.slippage、universe.exclude。禁止输出 filter(...)、rank(...)、select.top(...)、weight.equal()、sell_rule(...)、backtest(...)、risk.max_position(...) 这类未支持伪语法。\n");
-    prompt.push_str("参数形态必须严格：selection.market_cap_band 必须写 field=\"market_cap\" 或 field=\"free_float_cap\", lower=..., upper=...；禁止使用 float_market_cap；禁止使用 ma60、stock_ma60、signal_ma60、benchmark_ma60，60日价格均线写 rolling_mean(\"close\", 60) 或 ma(\"close\", 60)，任意窗口均量写 rolling_mean(\"volume\", n) 或 vma(n)；不要生成 fn score() 这类零参数函数，股票字段排序直接写在 ordering.rank_expr 内或用带参数函数；布尔字段按布尔使用，写 !is_st、!paused、!at_upper_limit、!at_lower_limit，不要写 is_st == 0；risk.index_exposure 只能传一个数值表达式，例如 ((signal_close < signal_ma20) ? 0.35 : 1.0)；execution.matching_type 只能取 next_tick_last、next_tick_best_own、next_tick_best_counterparty、counterparty_offer、vwap、current_bar_close、next_bar_open、open_auction；execution.slippage 必须写 execution.slippage(\"none\") 或 execution.slippage(\"price_ratio\", 0.001)。\n");
+    prompt.push_str("参数形态必须严格：selection.market_cap_band 必须写 field=\"market_cap\" 或 field=\"free_float_cap\", lower=..., upper=...；禁止使用 float_market_cap；禁止使用 ma60、stock_ma60、signal_ma60、benchmark_ma60，60日价格均线写 rolling_mean(\"close\", 60) 或 ma(\"close\", 60)，任意窗口均量写 rolling_mean(\"volume\", n) 或 vma(n)；不要生成 fn score() 这类零参数函数，股票字段排序直接写在 ordering.rank_expr 内或用带参数函数；布尔字段按布尔使用，写 !is_st、!paused、!at_upper_limit、!at_lower_limit，不要写 is_st == 0；risk.index_exposure 只能传一个数值表达式，不要使用 risk.exposure；完整三元表达式 cond ? a : b 可以使用，但不得输出残缺问号/冒号片段；execution.matching_type 只能取 next_tick_last、next_tick_best_own、next_tick_best_counterparty、counterparty_offer、vwap、current_bar_close、next_bar_open、open_auction；next_bar_open 只能使用决策日信号，不能把执行日价格当作下单前信息；execution.slippage 必须写 execution.slippage(\"none\") 或 execution.slippage(\"price_ratio\", 0.001)。\n");
     prompt.push_str("回测成功但 tradeCount=0 或 holdingCount=0 是无效策略；第一版必须保持稳定买入覆盖率，复杂因子只能在后续优化中逐步加严。\n");
-    prompt.push_str("可参考但不要照抄的最小模板，回复时不要包含 ``` 代码围栏：\nstrategy(\"cn_a_smallcap_factor_rotation\") {\nmarket(\"CN_A\")\nbenchmark(\"000852.SH\")\nsignal(\"000001.SH\")\nrebalance.every_days(5).at([\"10:18\"])\nselection.limit(40)\nselection.market_cap_band(field=\"market_cap\", lower=0, upper=1000)\nfilter.stock_expr(listed_days >= 60 && !is_st && !paused && close > 2 && !at_upper_limit && !at_lower_limit)\nordering.rank_by(\"market_cap\", \"asc\")\nallocation.buy_scale(1.0)\nrisk.index_exposure((signal_close < signal_ma20) ? 0.35 : 1.0)\nrisk.stop_loss(holding_return < -0.08)\nexecution.slippage(\"price_ratio\", 0.001)\n}\n\n");
+    prompt.push_str("可参考但不要照抄的最小模板，回复时不要包含 ``` 代码围栏：\nstrategy(\"cn_a_smallcap_factor_rotation\") {\nmarket(\"CN_A\")\nbenchmark(\"000852.SH\")\nsignal(\"000001.SH\")\nrebalance.every_days(5).at([\"10:18\"])\nselection.limit(40)\nselection.market_cap_band(field=\"market_cap\", lower=0, upper=1000)\nfilter.stock_expr(listed_days >= 60 && !is_st && !paused && close > 2 && !at_upper_limit && !at_lower_limit)\nordering.rank_by(\"market_cap\", \"asc\")\nallocation.buy_scale(1.0)\nrisk.index_exposure(1.0)\nrisk.stop_loss(holding_return < -0.08)\nexecution.slippage(\"price_ratio\", 0.001)\n}\n\n");
     prompt.push_str("用户目标：\n");
     prompt.push_str(&format!("- {}\n", request.user_goal));
     if !request.constraints.is_empty() {