diff --git a/src/llm/prompts.ts b/src/llm/prompts.ts
index 4ad8919..a91074e 100644
--- a/src/llm/prompts.ts
+++ b/src/llm/prompts.ts
@@ -90,3 +90,66 @@ export function generateMindMapPrompt(
     },
   ];
 }
+
+/**
+ * 回忆对比：将用户凭记忆写的导图与标准导图语义对比。
+ *
+ * 输出要求：严格 JSON（不要包含 markdown 代码块标记），结构如下：
+ * {
+ *   "matchedTree": { "title": "标准根标题", "children": [...], "notes": "MATCHED|备注" },
+ *   "extraNodes": [{ "title": "额外节点标题", "path": "路径" }],
+ *   "recallRatio": 0.75,
+ *   "matchedCount": 6,
+ *   "missedCount": 2,
+ *   "extraCount": 3,
+ *   "evaluation": "评价文字"
+ * }
+ *
+ * 要点：
+ * - 标准导图的每个节点在 matchedTree 中标注 MATCHED| 或 MISSED| 前缀，
+ *   匹配时保留原始标题，不要改变标准导图的标题文字
+ * - 匹配应基于语义而非字面，同义表达（如"锁升级"≈"锁膨胀"）算匹配
+ * - 考虑层级上下文：节点逻辑上归属正确即可匹配，不要求层级路径完全一致
+ * - 用户额外回忆到的节点放入 extraNodes
+ * - 评价用中文写，2-5 句话，指出回忆完整度、遗漏的关键概念、
+ *   额外回忆的知识点是否有价值
+ */
+export function compareRecallPrompt(
+  taskName: string,
+  standardOutline: string,
+  recallOutline: string,
+): ChatMessage[] {
+  return [
+    {
+      role: "system",
+      content: [
+        "你是一名学习评估专家。请对比两份思维导图大纲：",
+        "1. 标准导图（系统从学习报告中提炼的知识结构）",
+        "2. 用户导图（用户凭记忆回忆的知识结构）",
+        "",
+        "你的任务：",
+        "- 对标准导图的每个非根节点，判断用户在回忆中是否覆盖了它；",
+        "- 匹配应基于语义理解：即使表达的用词、角度不同，概念相同就算匹配；",
+        "- 考虑层级上下文：一个节点在用户导图中归属到正确的逻辑分组下才算匹配；",
+        "- 找出用户额外回忆到的、标准导图中没有的知识点（extraNodes）；",
+        "- 统计覆盖率、命中/遗漏/额外数量；",
+        "- 用中文写一段评价（2-5 句话），包括：回忆完整度评价、遗漏了哪些关键概念、额外回忆的内容是否有价值。",
+        "",
+        "输出必须是有效 JSON，不要包含 ```json 之类的标记，直接输出 JSON 对象。",
+        "标准导图中需要标注的节点，在 notes 字段中用 MATCHED| 或 MISSED| 标记。",
+      ].join("\n"),
+    },
+    {
+      role: "user",
+      content: [
+        `学习任务：${taskName}`,
+        "",
+        "===== 标准导图（知识结构）=====",
+        standardOutline,
+        "",
+        "===== 用户回忆导图 =====",
+        recallOutline,
+      ].join("\n"),
+    },
+  ];
+}
diff --git a/src/routes/ai.ts b/src/routes/ai.ts
index 7d8f0af..fb191b7 100644
--- a/src/routes/ai.ts
+++ b/src/routes/ai.ts
@@ -4,7 +4,7 @@
 
 import type { FastifyInstance } from "fastify";
 import { chat, isAvailable, loadConfig, LlmError } from "../llm/client.js";
-import { aggregateReportPrompt, generateMindMapPrompt, type FragmentInput } from "../llm/prompts.js";
+import { aggregateReportPrompt, compareRecallPrompt, generateMindMapPrompt, type FragmentInput } from "../llm/prompts.js";
 import { logStore } from "../admin/store.js";
 
 interface AggregateReportBody {
@@ -20,6 +20,12 @@ interface GenerateMindMapBody {
   fragments: string[];
 }
 
+interface CompareRecallBody {
+  taskName: string;
+  standardOutline: string;
+  recallOutline: string;
+}
+
 export async function aiRoutes(app: FastifyInstance): Promise<void> {
   const config = loadConfig();
 
@@ -120,4 +126,51 @@ export async function aiRoutes(app: FastifyInstance): Promise<void> {
       throw err;
     }
   });
+
+  /**
+   * 回忆对比：将用户凭记忆写的导图大纲与标准导图语义对比。
+   */
+  app.post<{ Body: CompareRecallBody }>("/ai/compare-recall", async (request, reply) => {
+    const { taskName, standardOutline, recallOutline } = request.body ?? ({} as CompareRecallBody);
+    const t0 = Date.now();
+    const params = { temperature: 0.2, max_tokens: 4096 };
+
+    if (!taskName || !standardOutline?.trim() || !recallOutline?.trim()) {
+      logStore.add({
+        timestamp: new Date().toISOString(), endpoint: "/ai/compare-recall",
+        model: config.model, durationMs: Date.now() - t0, status: 400,
+        requestBody: request.body ?? {}, params,
+        responseBody: { error: "taskName、standardOutline、recallOutline 均不可为空" },
+      });
+      return reply.status(400).send({ error: "taskName、standardOutline、recallOutline 均不可为空" });
+    }
+
+    try {
+      const messages = compareRecallPrompt(taskName, standardOutline, recallOutline);
+      const raw = await chat(config, messages, { temperature: 0.2, maxTokens: 4096 });
+      // LLM 可能把 JSON 包在 ```json ... ``` 里，做一次清理
+      const clean = raw.trim().replace(/^```(?:json)?\s*/, "").replace(/\s*```$/, "");
+      const result = JSON.parse(clean);
+      logStore.add({
+        timestamp: new Date().toISOString(), endpoint: "/ai/compare-recall",
+        model: config.model, durationMs: Date.now() - t0, status: 200,
+        requestBody: request.body ?? {}, messages, params,
+        responseBody: result,
+      });
+      return result;
+    } catch (err) {
+      const status = err instanceof LlmError ? err.statusCode
+                   : err instanceof SyntaxError ? 502 : 500;
+      const errMsg = err instanceof Error ? err.message : String(err);
+      logStore.add({
+        timestamp: new Date().toISOString(), endpoint: "/ai/compare-recall",
+        model: config.model, durationMs: Date.now() - t0, status,
+        requestBody: request.body ?? {}, params, responseBody: {}, error: errMsg,
+      });
+      if (err instanceof LlmError) {
+        return reply.status(err.statusCode).send({ error: err.message });
+      }
+      throw err;
+    }
+  });
 }