新增: 跨会话召回四层架构与脉络卡

- 会话终态提炼: 删除前+停靠双挂点,快照与清水位同临界区
- 目标快照: 恢复引导按最终有效意图生成,旧目标不复活
- 知识检索项目维度软排序,WorkingContext 持久化迁移
- 脉络卡: published 知识按项目聚合纯读侧,带入上下文经输入框显式注入
- 压缩与缓存能力在主循环/子代理/提示词三面接线
- 两份专项设计文档与看板销账

crates/df-storage/src/migrations.rs

@@ -65,7 +65,9 @@ pub fn run(conn: &Connection) -> Result<()> {
     // V51 = 待发箱 ai_outbox 表(定时消息与待发箱持久化 P0 地基):队列/定时统一实体,
     //       调度器按 status+due_at 索引到点派发。纯新增表,可逆=DROP TABLE ai_outbox。
     // V52 = ai_messages.source 列(#958 消息溯源:外部渠道原始消息 ID JSON,NULL=桌面本端)。
-    let steps: [(i32, fn(&Connection) -> Result<()>); 52] = [
+    // V53 = WorkingContext 持久化(ai_conversations.working_context_json TEXT,跨会话召回 L4
+    //       重启不失忆:save 随行写,会话载入与 parked 恢复读还原,NULL=无上下文行为同旧)。
+    let steps: [(i32, fn(&Connection) -> Result<()>); 53] = [
         (1, migrate_v1),
         (2, migrate_v2),
         (3, migrate_v3),
@@ -125,6 +127,8 @@ pub fn run(conn: &Connection) -> Result<()> {
         (51, migrate_v51),
         // V52 = ai_messages 加 source 列(#958 消息溯源:飞书等外部渠道原始消息 ID)。
         (52, migrate_v52),
+        // V53 = WorkingContext 持久化(ai_conversations.working_context_json,跨会话召回 L4)。
+        (53, migrate_v53),
     ];
 
     for (version, migrate_fn) in steps {
@@ -1532,7 +1536,7 @@ fn migrate_v50(conn: &Connection) -> Result<()> {
 ///   调度器启动时 reset_stale_sending 复位为 pending。
 /// 迁移链顶点版本(单一真值来源)：**新增迁移时必须同步 +1**,否则下方迁移测试会失败
 /// (测试用它断言「全量迁移后 schema_version == 顶点」「重跑仍到顶点」——既防链中断,也免多处写死)。
-pub const LATEST_SCHEMA_VERSION: i32 = 52;
+pub const LATEST_SCHEMA_VERSION: i32 = 53;
 
 fn migrate_v51(conn: &Connection) -> Result<()> {
     if !table_exists(conn, "ai_outbox") {
@@ -1584,6 +1588,27 @@ fn migrate_v52(conn: &Connection) -> Result<()> {
     Ok(())
 }
 
+/// V53: WorkingContext 持久化 — ai_conversations 加 working_context_json TEXT 列。
+///
+/// 跨会话召回 L4(重启不失忆):WorkingContext(自动目标/决策/未解项/当前步骤/脏标记版本)
+/// 此前纯内存,重启后压缩重锚定回填的决策与未解项全丢,恢复的会话半失忆续跑。本列随 save
+/// 每轮随行写、会话载入与 parked 恢复读还原;NULL=无上下文(老会话/全空),行为同旧。
+/// 目标快照裁决语义另批,本列只做存储载体。
+/// - **幂等**:column_exists 守卫(同 V44/V45/V49 模式),崩溃重跑/全链两遍不炸;
+/// - **可逆**:`ALTER TABLE ai_conversations DROP COLUMN working_context_json`(SQLite 3.35+)。
+fn migrate_v53(conn: &Connection) -> Result<()> {
+    if !column_exists(conn, "ai_conversations", "working_context_json") {
+        conn.execute(
+            "ALTER TABLE ai_conversations ADD COLUMN working_context_json TEXT",
+            [],
+        )?;
+        tracing::info!("v53: 补建 ai_conversations.working_context_json 列(WorkingContext 持久化)");
+    }
+    conn.execute("INSERT OR IGNORE INTO schema_version (version) VALUES (?)", [53])?;
+    tracing::info!("迁移 v53 完成: ai_conversations 加 working_context_json 列");
+    Ok(())
+}
+
 /// 回填 conversation_checkpoints.token_total:按 snapshot JSON 内逐条消息的
 /// prompt_tokens+completion_tokens 求真实总量。
 ///
@@ -2951,4 +2976,51 @@ mod tests {
             "逐条相加,缺字段按 0"
         );
     }
+
+    /// V53 幂等:最小老库补建 working_context_json 列;重跑(含版本号回退模拟崩溃断点)
+    /// 不炸不报 duplicate column;列可写可读(NULL 语义=无 WorkingContext)。
+    #[test]
+    fn v53_working_context_json_idempotent() {
+        let conn = setup_legacy_db();
+        assert!(
+            !column_exists(&conn, "ai_conversations", "working_context_json"),
+            "迁移前应无 working_context_json 列"
+        );
+
+        migrate_v53(&conn).expect("v53 首次迁移应成功");
+        assert!(column_exists(&conn, "ai_conversations", "working_context_json"), "应有 working_context_json 列");
+        let v: i64 = conn
+            .query_row("SELECT MAX(version) FROM schema_version", [], |r| r.get(0))
+            .unwrap();
+        assert_eq!(v, 53, "应写入版本号 53");
+
+        // 模拟崩溃断点:版本号回退但列已建 → 重跑走 column_exists 短路
+        conn.execute("DELETE FROM schema_version WHERE version = 53", []).unwrap();
+        migrate_v53(&conn).expect("列已存在时重跑应幂等跳过 ALTER 不报错");
+        let v2: i64 = conn
+            .query_row("SELECT MAX(version) FROM schema_version", [], |r| r.get(0))
+            .unwrap();
+        assert_eq!(v2, 53, "重跑后版本号恢复 53");
+
+        // 列可写可读;老会话行(不带该列插入)读回 NULL
+        conn.execute(
+            "INSERT INTO ai_conversations (id, messages, created_at, updated_at, working_context_json) \
+             VALUES ('c1', '[]', '0', '0', '{\"goals\":[],\"decisions\":[]}')",
+            [],
+        )
+        .unwrap();
+        conn.execute(
+            "INSERT INTO ai_conversations (id, messages, created_at, updated_at) VALUES ('c2', '[]', '0', '0')",
+            [],
+        )
+        .unwrap();
+        let got: Option<String> = conn
+            .query_row("SELECT working_context_json FROM ai_conversations WHERE id = 'c1'", [], |r| r.get(0))
+            .unwrap();
+        assert!(got.is_some(), "working_context_json 应可写可读");
+        let legacy: Option<String> = conn
+            .query_row("SELECT working_context_json FROM ai_conversations WHERE id = 'c2'", [], |r| r.get(0))
+            .unwrap();
+        assert!(legacy.is_none(), "老会话行应为 NULL(无 WorkingContext)");
+    }
 }