diff --git a/plugins/member_roast/config.toml b/plugins/member_roast/config.toml
new file mode 100644
index 0000000..8831afe
--- /dev/null
+++ b/plugins/member_roast/config.toml
@@ -0,0 +1,38 @@
+[MemberRoast]
+enable = true
+command = ["锐评一下", "锐评", "吐槽一下", "锐评我", "吐槽我"]
+command_format = """
+锐评插件指令：
+@机器人 锐评一下 @某人
+@机器人 锐评一下我
+@机器人 锐评一下 张三
+"""
+
+[llm]
+# 这里使用通用聊天场景，而不是成员画像提炼场景：
+# 1. 成员画像场景更偏结构化抽取；
+# 2. “锐评”更需要创意表达、梗感和自然语言发挥；
+# 3. 因此优先复用 chat.main，既稳定又方便后续单独切换模型。
+scene = "chat.main"
+temperature = 0.9
+max_tokens = 700
+timeout_seconds = 120
+max_retries = 2
+retry_delay_seconds = 1.5
+
+[profile]
+# 最近消息窗口：尽量贴近用户提出的“最近 50 条发言”。
+sample_days = 30
+message_limit = 50
+min_message_count = 8
+context_stale_hours = 24
+name_match_min_chars = 2
+
+[style]
+# 文案风格参数：
+# 1. 默认允许“犀利但有分寸”的群聊吐槽；
+# 2. 输出长度控制在群里容易传播的一屏左右；
+# 3. 若后续你想改成更狠/更柔和，只需要调这里。
+max_output_chars = 320
+min_output_chars = 140
+sharpness_level = "high"
diff --git a/plugins/member_roast/main.py b/plugins/member_roast/main.py
new file mode 100644
index 0000000..05f4b1c
--- /dev/null
+++ b/plugins/member_roast/main.py
@@ -0,0 +1,633 @@
+# -*- coding: utf-8 -*-
+import json
+import re
+import xml.etree.ElementTree as ET
+from datetime import datetime, timedelta
+from typing import Any, Dict, List, Optional, Tuple
+
+from loguru import logger
+
+from base.plugin_common.message_plugin_interface import MessagePluginInterface
+from base.plugin_common.plugin_interface import PluginStatus
+from db.connection import DBConnectionManager
+from db.contacts_db import ContactsDBOperator
+from db.member_context_db import MemberContextDBOperator
+from db.message_storage import MessageStorageDB
+from plugins.ai_auto_response.memory.group_memory_profile import GroupMemoryService
+from plugins.member_context.service import MemberContextService
+from utils.ai.unified_llm import UnifiedLLMClient
+from utils.decorator.plugin_decorators import plugin_stats_decorator
+from utils.decorator.points_decorator import plugin_points_cost
+from utils.decorator.rate_limit_decorator import group_feature_rate_limit, user_feature_rate_limit
+from utils.revoke.message_auto_revoke import MessageAutoRevoke
+from utils.robot_cmd.robot_command import GroupBotManager, PermissionStatus
+from utils.wechat.contact_manager import ContactManager
+from wechat_ipad import WechatAPIClient
+from wechat_ipad.models.message import WxMessage
+
+
+class MemberRoastService:
+    """成员锐评服务。
+
+    设计目标：
+    1. 尽量复用现有“成员画像 + 群画像 + 最近消息”能力，避免再做一套平行画像系统；
+    2. 锐评时优先吃稳定画像，再辅以最近 50 条发言做“当期状态”补充；
+    3. 这样生成出来的内容既不像随机骂人，也不会完全被旧画像绑死。
+    """
+
+    def __init__(self, db_manager: DBConnectionManager, plugin_config: Optional[Dict[str, Any]] = None):
+        self.db_manager = db_manager
+        self.plugin_config = plugin_config or {}
+        self.contacts_db = ContactsDBOperator(db_manager)
+        self.member_context_db = MemberContextDBOperator(db_manager)
+        self.message_db = MessageStorageDB(db_manager)
+        self.member_context_service = MemberContextService(db_manager, plugin_config or {})
+        # 群画像服务本身已经带“按天/按总结刷新”的快照逻辑，直接复用即可。
+        self.group_memory_service = GroupMemoryService(db_manager, {})
+        self.LOG = logger
+
+        profile_cfg = self.plugin_config.get("profile", {}) or {}
+        self.sample_days = max(int(profile_cfg.get("sample_days", 30) or 30), 1)
+        self.message_limit = max(int(profile_cfg.get("message_limit", 50) or 50), 1)
+        self.min_message_count = max(int(profile_cfg.get("min_message_count", 8) or 8), 1)
+        self.context_stale_hours = max(int(profile_cfg.get("context_stale_hours", 24) or 24), 1)
+
+    def build_roast_payload(self, group_id: str, target_wxid: str) -> Tuple[bool, Dict[str, Any]]:
+        """构建锐评所需的完整画像载荷。"""
+        member_info = self.contacts_db.get_chatroom_member_info(group_id, target_wxid) or {}
+        display_name = (
+            member_info.get("display_name")
+            or member_info.get("nick_name")
+            or ContactManager.get_instance().get_group_name(group_id, target_wxid)
+            or target_wxid
+        )
+        group_profile = self.contacts_db.get_chatroom_profile(group_id) or {}
+        group_name = str(group_profile.get("nick_name") or "").strip()
+
+        recent_messages = self.message_db.get_member_recent_messages(
+            group_id,
+            target_wxid,
+            days=self.sample_days,
+            limit=self.message_limit,
+            include_today=True,
+        ) or []
+
+        if len(recent_messages) < self.min_message_count:
+            return False, {
+                "error": (
+                    f"素材不够，最近只找到 {len(recent_messages)} 条有效发言，"
+                    f"至少需要 {self.min_message_count} 条才能锐评得像样。"
+                )
+            }
+
+        member_context = self._load_or_refresh_member_context(group_id, target_wxid)
+        group_memory_profile = self.group_memory_service.build_group_memory_profile(group_id, group_name=group_name)
+        active_dates = self.message_db.get_member_active_dates(group_id, target_wxid, days=min(self.sample_days, 180)) or []
+
+        payload = {
+            "group_id": group_id,
+            "group_name": group_name,
+            "target_wxid": target_wxid,
+            "display_name": display_name,
+            "member_context": member_context or {},
+            "group_memory_profile": group_memory_profile or {},
+            "recent_messages": recent_messages,
+            "message_count": len(recent_messages),
+            "active_days": len(active_dates),
+            "last_active_at": recent_messages[-1].get("timestamp") if recent_messages else "",
+        }
+        return True, payload
+
+    def _load_or_refresh_member_context(self, group_id: str, target_wxid: str) -> Dict[str, Any]:
+        """读取成员画像，必要时做一次轻刷新。
+
+        这里不强制每次都实时重建：
+        1. 优先使用已有画像，保证调用速度；
+        2. 只有画像不存在，或者已明显过期时，才重新构建；
+        3. 这样既兼顾体验，也能让锐评尽量吃到比较新的“人设信息”。
+        """
+        member_context = self.member_context_db.get_member_context(group_id, target_wxid) or {}
+        if not member_context:
+            refreshed = self.member_context_service.build_member_context(
+                group_id,
+                target_wxid,
+                days=self.sample_days,
+                limit=self.message_limit,
+                ensure_group_daily=True,
+                enable_weekly_digest=True,
+                enable_monthly_digest=True,
+            )
+            self.member_context_db.save_member_context(refreshed)
+            return refreshed
+
+        last_profiled_at = self._safe_parse_datetime(str(member_context.get("last_profiled_at", "") or ""))
+        if not last_profiled_at:
+            return member_context
+
+        if datetime.now() - last_profiled_at <= timedelta(hours=self.context_stale_hours):
+            return member_context
+
+        try:
+            refreshed = self.member_context_service.build_member_context(
+                group_id,
+                target_wxid,
+                days=self.sample_days,
+                limit=self.message_limit,
+                ensure_group_daily=False,
+                enable_weekly_digest=True,
+                enable_monthly_digest=True,
+            )
+            self.member_context_db.save_member_context(refreshed)
+            return refreshed
+        except Exception as e:
+            # 画像刷新失败时回退旧画像：
+            # 1. 锐评功能本身不应因为画像补刷新失败而整体不可用；
+            # 2. 旧画像 + 最近消息 仍然足够支撑一版可用输出。
+            self.LOG.warning(f"[成员锐评] 画像过期后刷新失败，回退旧画像: group={group_id}, wxid={target_wxid}, error={e}")
+            return member_context
+
+    @staticmethod
+    def _safe_parse_datetime(value: str) -> Optional[datetime]:
+        """安全解析时间字符串。"""
+        text = str(value or "").strip()
+        if not text:
+            return None
+        for fmt in ("%Y-%m-%d %H:%M:%S", "%Y-%m-%d"):
+            try:
+                return datetime.strptime(text, fmt)
+            except ValueError:
+                continue
+        return None
+
+
+class MemberRoastPlugin(MessagePluginInterface):
+    """成员锐评插件。
+
+    用户场景：
+    1. @机器人 锐评一下 @某人
+    2. @机器人 锐评一下我
+    3. @机器人 锐评一下 张三
+
+    玩法目标：
+    1. 利用现有成员画像和群画像，让模型“骂得像认识这个人”；
+    2. 保持群聊传播性，输出足够犀利，但不要跨到恶意辱骂；
+    3. 尽量做到一句命令就能引爆围观，而不需要复杂多轮交互。
+    """
+
+    FEATURE_KEY = "MEMBER_ROAST"
+    FEATURE_DESCRIPTION = "🗡️ 成员锐评 [@机器人 锐评一下 @某人]"
+
+    @property
+    def name(self) -> str:
+        return "成员锐评"
+
+    @property
+    def version(self) -> str:
+        return "1.0.0"
+
+    @property
+    def description(self) -> str:
+        return "结合成员画像与最近发言，对指定群成员进行幽默锐评。"
+
+    @property
+    def author(self) -> str:
+        return "ABOT Team"
+
+    @property
+    def command_prefix(self) -> Optional[str]:
+        return ""
+
+    @property
+    def commands(self) -> List[str]:
+        return self._commands
+
+    @property
+    def feature_key(self) -> Optional[str]:
+        return self.FEATURE_KEY
+
+    @property
+    def feature_description(self) -> Optional[str]:
+        return self.FEATURE_DESCRIPTION
+
+    def __init__(self):
+        super().__init__()
+        self.feature = self.register_feature()
+        self.service: Optional[MemberRoastService] = None
+        self.llm_client: Optional[UnifiedLLMClient] = None
+        self.bot: Optional[WechatAPIClient] = None
+        self.revoke: Optional[MessageAutoRevoke] = None
+        self.contacts_db: Optional[ContactsDBOperator] = None
+        self.enable = True
+        self.command_format = ""
+        self.max_output_chars = 320
+        self.min_output_chars = 140
+        self.sharpness_level = "high"
+        self.name_match_min_chars = 2
+
+    def initialize(self, context: Dict[str, Any]) -> bool:
+        """初始化插件。"""
+        self.LOG = logger
+        self.LOG.debug(f"正在初始化 {self.name} 插件...")
+        cfg = self._config.get("MemberRoast", {}) or {}
+        self.enable = bool(cfg.get("enable", True))
+        self._commands = cfg.get("command", ["锐评一下", "锐评", "吐槽一下", "锐评我", "吐槽我"])
+        self.command_format = str(
+            cfg.get(
+                "command_format",
+                "锐评插件指令：\n@机器人 锐评一下 @某人\n@机器人 锐评一下我",
+            )
+        )
+
+        style_cfg = self._config.get("style", {}) or {}
+        self.max_output_chars = max(int(style_cfg.get("max_output_chars", 320) or 320), 80)
+        self.min_output_chars = max(int(style_cfg.get("min_output_chars", 140) or 140), 40)
+        self.sharpness_level = str(style_cfg.get("sharpness_level", "high") or "high").strip().lower()
+
+        profile_cfg = self._config.get("profile", {}) or {}
+        self.name_match_min_chars = max(int(profile_cfg.get("name_match_min_chars", 2) or 2), 1)
+
+        db_manager = context.get("db_manager")
+        if not db_manager:
+            self.LOG.error(f"[{self.name}] 缺少 db_manager，初始化失败")
+            return False
+
+        self.contacts_db = ContactsDBOperator(db_manager)
+        self.service = MemberRoastService(db_manager, self._config)
+        self.llm_client = UnifiedLLMClient(self._config.get("llm", {}) or {"scene": "chat.main"})
+        self.LOG.debug(f"[{self.name}] 插件初始化完成，指令：{self._commands}")
+        return True
+
+    def start(self) -> bool:
+        self.LOG.debug(f"[{self.name}] 插件已启动")
+        self.status = PluginStatus.RUNNING
+        return True
+
+    def stop(self) -> bool:
+        self.LOG.info(f"[{self.name}] 插件已停止")
+        self.status = PluginStatus.STOPPED
+        return True
+
+    def can_process(self, message: Dict[str, Any]) -> bool:
+        """判断消息是否可能触发锐评。
+
+        这里不只看首词：
+        1. 用户实际会说“@机器人 锐评一下 @张三”；
+        2. 这时首词往往是 @机器人，而不是“锐评一下”；
+        3. 因此需要做关键字级别的宽匹配。
+        """
+        if not self.enable:
+            return False
+
+        roomid = str(message.get("roomid", "") or "").strip()
+        if not roomid:
+            return False
+
+        content = self._normalize_text(message.get("content", ""))
+        if not content:
+            return False
+
+        return bool(re.search(r"(锐评(?:一下)?|吐槽一下|锐评我|吐槽我)", content))
+
+    @plugin_stats_decorator(plugin_name="成员锐评")
+    @plugin_points_cost(10, "成员锐评消耗积分", FEATURE_KEY)
+    @group_feature_rate_limit(max_per_minute=12, feature_key=FEATURE_KEY)
+    @user_feature_rate_limit(max_per_minute=4, feature_key=FEATURE_KEY)
+    async def process_message(self, message: Dict[str, Any]) -> Tuple[bool, Optional[str]]:
+        """处理锐评请求。"""
+        content = self._normalize_text(message.get("content", ""))
+        sender = str(message.get("sender", "") or "").strip()
+        roomid = str(message.get("roomid", "") or "").strip()
+        self.bot = message.get("bot")
+        self.revoke = message.get("revoke")
+        gbm: GroupBotManager = message.get("gbm")
+
+        if not roomid:
+            return False, "仅支持群聊"
+        if not self.bot:
+            return False, "bot 未初始化"
+        if not self.service or not self.llm_client or not self.contacts_db:
+            return False, "服务未初始化"
+        if gbm and roomid and gbm.get_group_permission(roomid, self.feature) == PermissionStatus.DISABLED:
+            return False, "没有权限"
+
+        # 群里更推荐 @机器人 触发，避免普通聊天里出现“锐评”二字时误打到插件。
+        if not bool(message.get("is_at", False)) and not content.startswith(("锐评", "吐槽")):
+            return False, None
+
+        target_ok, target_payload = self._resolve_target_member(message, content)
+        if not target_ok:
+            await self._send_fail_message(roomid, sender, target_payload.get("error", "目标解析失败"))
+            return False, target_payload.get("error", "目标解析失败")
+
+        target_wxid = str(target_payload.get("target_wxid") or "").strip()
+        target_name = str(target_payload.get("target_name") or target_wxid).strip()
+        if not target_wxid:
+            await self._send_fail_message(roomid, sender, "没找到要锐评的人。")
+            return False, "未找到目标"
+
+        wait_msg = f"🧐 正在翻 {target_name} 的群聊黑历史，稍等我组织一下语言…"
+        client_msg_id, create_time, new_msg_id = await self.bot.send_text_message(roomid, wait_msg, sender)
+        if self.revoke:
+            self.revoke.add_message_to_revoke(roomid, client_msg_id, create_time, new_msg_id, 5)
+
+        ok, roast_payload = self.service.build_roast_payload(roomid, target_wxid)
+        if not ok:
+            await self._send_fail_message(roomid, sender, roast_payload.get("error", "素材不足，今天先放他一马。"))
+            return False, roast_payload.get("error", "素材不足")
+
+        requester_name = ContactManager.get_instance().get_group_name(roomid, sender) or sender
+        roast_text = self._generate_roast_text(roast_payload, requester_name=requester_name)
+        if not roast_text:
+            await self._send_fail_message(roomid, sender, "模型今天嘴有点钝，稍后再来试试。")
+            return False, "模型输出为空"
+
+        final_text = self._post_process_roast_text(roast_text, target_name)
+        client_msg_id, create_time, new_msg_id = await self.bot.send_at_message(roomid, final_text, [sender])
+        if self.revoke:
+            self.revoke.add_message_to_revoke(roomid, client_msg_id, create_time, new_msg_id, 120)
+        return True, "锐评成功"
+
+    def _resolve_target_member(self, message: Dict[str, Any], content: str) -> Tuple[bool, Dict[str, Any]]:
+        """解析本次要被锐评的目标成员。"""
+        sender = str(message.get("sender", "") or "").strip()
+        roomid = str(message.get("roomid", "") or "").strip()
+        wx_msg: WxMessage = message.get("full_wx_msg")
+        raw_xml = wx_msg.msg_source if wx_msg else ""
+        at_users = self._parse_at_users(raw_xml)
+        bot_wxid = str(getattr(self.bot, "wxid", "") or "").strip()
+
+        # @列表里如果带机器人自己，需要先排除掉，再决定是否还有真正的目标成员。
+        target_at_users = [uid for uid in at_users if uid and uid != bot_wxid]
+        if len(target_at_users) > 1:
+            return False, {"error": "一次只能锐评一个人，别让我开群体AOE。"}
+        if len(target_at_users) == 1:
+            target_wxid = target_at_users[0]
+            target_name = self._get_member_display_name(roomid, target_wxid)
+            return True, {"target_wxid": target_wxid, "target_name": target_name}
+
+        # 没有真正的 @目标时，优先支持“锐评一下我”。
+        normalized = content.replace(" ", "").replace("\u2005", "")
+        if any(keyword in normalized for keyword in ("锐评一下我", "锐评我", "吐槽我", "吐槽一下我")):
+            return True, {"target_wxid": sender, "target_name": self._get_member_display_name(roomid, sender)}
+
+        candidate_name = self._extract_name_candidate(content)
+        if not candidate_name:
+            return False, {"error": "请 @一个人，或者直接说“锐评一下我”。"}
+
+        matched = self._match_member_by_name(roomid, candidate_name)
+        if not matched:
+            return False, {"error": f"没在群里找到“{candidate_name}”这个人。"}
+        if len(matched) > 1:
+            names = "、".join([item["target_name"] for item in matched[:3]])
+            return False, {"error": f"“{candidate_name}”对应了多个人：{names}，建议直接 @TA。"}
+        return True, matched[0]
+
+    def _extract_name_candidate(self, content: str) -> str:
+        """从文本里提取未 @ 时的目标名称候选。"""
+        text = self._normalize_text(content)
+        # 先去掉常见的 @机器人文案残留，尽量只保留命令后面真正的目标名。
+        text = re.sub(r"^@\S+\s*", "", text)
+        text = re.sub(r"(锐评(?:一下)?|吐槽一下|吐槽我|锐评我)", " ", text, count=1)
+        text = re.sub(r"[@#：:，,。.!！?？\[\]\(\)]", " ", text)
+        text = re.sub(r"\s+", " ", text).strip()
+        if len(text) < self.name_match_min_chars:
+            return ""
+        return text
+
+    def _match_member_by_name(self, roomid: str, candidate_name: str) -> List[Dict[str, str]]:
+        """按群昵称/微信昵称模糊匹配成员。
+
+        匹配优先级：
+        1. 完全匹配；
+        2. 去空格后完全匹配；
+        3. 包含匹配。
+        """
+        if not self.contacts_db:
+            return []
+
+        candidate = self._normalize_name(candidate_name)
+        if not candidate:
+            return []
+
+        members = self.contacts_db.get_chatroom_member_list(roomid) or []
+        exact_matches: List[Dict[str, str]] = []
+        contains_matches: List[Dict[str, str]] = []
+        for member in members:
+            wxid = str(member.get("wxid") or "").strip()
+            if not wxid:
+                continue
+            display_name = str(member.get("display_name") or "").strip()
+            nick_name = str(member.get("nick_name") or "").strip()
+            for raw_name in [display_name, nick_name]:
+                normalized = self._normalize_name(raw_name)
+                if not normalized:
+                    continue
+                payload = {"target_wxid": wxid, "target_name": display_name or nick_name or wxid}
+                if normalized == candidate:
+                    exact_matches.append(payload)
+                    break
+                if candidate in normalized:
+                    contains_matches.append(payload)
+                    break
+
+        if exact_matches:
+            return self._dedup_target_list(exact_matches)
+        return self._dedup_target_list(contains_matches)
+
+    @staticmethod
+    def _dedup_target_list(items: List[Dict[str, str]]) -> List[Dict[str, str]]:
+        """按 wxid 去重。"""
+        result: List[Dict[str, str]] = []
+        seen = set()
+        for item in items:
+            wxid = str(item.get("target_wxid") or "").strip()
+            if not wxid or wxid in seen:
+                continue
+            seen.add(wxid)
+            result.append(item)
+        return result
+
+    def _generate_roast_text(self, payload: Dict[str, Any], requester_name: str = "") -> str:
+        """调用大模型生成锐评文案。"""
+        system_prompt = self._build_system_prompt()
+        user_prompt = self._build_user_prompt(payload, requester_name=requester_name)
+        text = self.llm_client.chat(
+            system_prompt=system_prompt,
+            user_prompt=user_prompt,
+            user_id=f"member_roast::{payload.get('group_id', '')}::{payload.get('target_wxid', '')}",
+        )
+        return str(text or "").strip()
+
+    def _build_system_prompt(self) -> str:
+        """构建系统提示词。
+
+        这份提示词重点控制三件事：
+        1. 输出要像群友毒舌，而不是客服分析；
+        2. 必须建立在已有素材上，不能瞎编私货；
+        3. 锐评要有梗，但不能跨到恶意羞辱。
+        """
+        sharpness_hint = "允许明显犀利、能扎心，但必须像熟人调侃，不能恶毒。"
+        if self.sharpness_level == "medium":
+            sharpness_hint = "允许轻到中度犀利，以调侃为主，不要真伤人。"
+        elif self.sharpness_level == "low":
+            sharpness_hint = "以幽默吐槽为主，别太重。"
+
+        return f"""
+你是微信群里的“人设观察员”，擅长用幽默、犀利、带梗的口吻总结一个人的群聊人设。
+
+你的任务不是分析报告，而是写一段会让群友围观、会心一笑、觉得“这人还真就是这样”的锐评。
+
+核心要求：
+1. 只能基于给定的成员画像、群画像和最近发言素材输出，不要编造未出现过的经历、人设、职业、家庭、隐私。
+2. {sharpness_hint}
+3. 可以用捧杀、阴阳、轻微毒舌、反转、梗化总结，但不能出现脏话、恶意辱骂、羞辱外貌、攻击疾病、地域、性别、民族、宗教等受保护属性。
+4. 不要写成正经心理测评，不要出现“根据数据分析”“从画像看”这种机器味句式。
+5. 优先抓：群聊人设、常见话术、反复出现的行为模式、擅长点、翻车点、群内角色。
+6. 如果素材不够扎实，就收一点，写成“轻评版”，不要硬编大招。
+
+输出格式要求：
+1. 第一行固定为：`【锐评 目标昵称】`
+2. 正文写 4 到 6 行，每行一句，适合直接发群里。
+3. 最后一行必须是“一句话绝杀”式收尾。
+4. 总长度控制在 {self.min_output_chars} 到 {self.max_output_chars} 字之间，宁可短狠，不要注水。
+""".strip()
+
+    def _build_user_prompt(self, payload: Dict[str, Any], requester_name: str = "") -> str:
+        """拼装用户提示词。"""
+        member_context = payload.get("member_context", {}) or {}
+        group_memory_profile = payload.get("group_memory_profile", {}) or {}
+        recent_messages = payload.get("recent_messages", []) or []
+        meta = member_context.get("meta", {}) or {}
+        group_style = group_memory_profile.get("style_profile", {}) or {}
+
+        # 最近 50 条发言是这次锐评最关键的“即时素材”：
+        # 1. 画像决定“这个人长期像谁”；
+        # 2. 最近发言决定“这阵子他又在发什么病”；
+        # 3. 两者结合，模型才更容易产出既稳定又有当期节目效果的锐评。
+        recent_lines = []
+        for idx, item in enumerate(recent_messages, start=1):
+            ts = item.get("timestamp")
+            if isinstance(ts, datetime):
+                ts_text = ts.strftime("%m-%d %H:%M")
+            else:
+                ts_text = str(ts or "")[5:16] if str(ts or "") else ""
+            content = str(item.get("content", "") or "").replace("\n", " ").strip()
+            if not content:
+                continue
+            recent_lines.append(f"{idx}. [{ts_text}] {content}")
+
+        prompt_payload = {
+            "任务说明": "请基于以下真实素材，为目标成员写一段有传播性的群聊锐评。",
+            "目标成员": {
+                "昵称": payload.get("display_name", ""),
+                "最近样本消息数": payload.get("message_count", 0),
+                "活跃天数": payload.get("active_days", 0),
+                "最后活跃时间": payload.get("last_active_at", ""),
+            },
+            "成员长期画像": {
+                "摘要": member_context.get("summary_text", ""),
+                "活跃等级": member_context.get("activity_level", ""),
+                "发言模式": member_context.get("message_pattern", ""),
+                "互动风格": member_context.get("interaction_style", ""),
+                "回复建议": member_context.get("response_style_hint", ""),
+                "长期主题": member_context.get("topics_of_interest", []),
+                "近期关注": member_context.get("recent_focus", []),
+                "稳定特征": meta.get("stable_traits", []),
+                "习惯模式": meta.get("habit_patterns", []),
+                "表达标记": meta.get("expression_profile", []),
+                "技能侧重点": meta.get("skill_profile", []),
+                "群内角色": meta.get("group_role", ""),
+                "气质倾向": meta.get("temperament_tendency", ""),
+                "近期状态": meta.get("recent_state", []),
+            },
+            "群聊背景": {
+                "群名": payload.get("group_name", ""),
+                "长期主题": group_memory_profile.get("focus_topics", []),
+                "群风格": group_style,
+                "群摘要": group_memory_profile.get("summary_text", ""),
+            },
+            "最近发言样本": recent_lines,
+            "额外要求": [
+                "要像熟人看破不说破，不要像机器写分析。",
+                "可以先抬后杀，也可以连续抓几个典型症状。",
+                "如果这人明显偏技术、答疑、摸鱼、抽象、嘴硬、复读机、群气氛组，请点出来。",
+                f"发起请求的人是：{requester_name}" if requester_name else "",
+            ],
+        }
+        return json.dumps(prompt_payload, ensure_ascii=False, indent=2)
+
+    def _post_process_roast_text(self, roast_text: str, target_name: str) -> str:
+        """清洗模型输出，统一成更适合直接发群的格式。"""
+        text = str(roast_text or "").strip()
+        text = re.sub(r"^```(?:json|markdown|text)?", "", text, flags=re.IGNORECASE).strip()
+        text = re.sub(r"```$", "", text).strip()
+        text = re.sub(r"\n{3,}", "\n\n", text)
+
+        # 如果模型忘了带头标题，这里兜底补上，保证最终输出辨识度稳定。
+        if not text.startswith("【锐评"):
+            text = f"【锐评 {target_name}】\n{text}"
+
+        # 模型有时会过度铺陈，这里做一次保底裁切，优先保持群聊传播性。
+        if len(text) > self.max_output_chars + 80:
+            text = text[: self.max_output_chars + 80].rstrip("，,、；; ").rstrip() + "。"
+        return text
+
+    async def _send_fail_message(self, roomid: str, sender: str, fail_text: str) -> None:
+        """统一发送失败提示。"""
+        client_msg_id, create_time, new_msg_id = await self.bot.send_at_message(roomid, f"❌ {fail_text}", [sender])
+        if self.revoke:
+            self.revoke.add_message_to_revoke(roomid, client_msg_id, create_time, new_msg_id, 8)
+
+    def _get_member_display_name(self, roomid: str, wxid: str) -> str:
+        """获取群内成员展示名。"""
+        if self.contacts_db:
+            member = self.contacts_db.get_chatroom_member_info(roomid, wxid) or {}
+            display_name = str(member.get("display_name") or member.get("nick_name") or "").strip()
+            if display_name:
+                return display_name
+        return ContactManager.get_instance().get_group_name(roomid, wxid) or wxid
+
+    @staticmethod
+    def _parse_at_users(raw_xml: str) -> List[str]:
+        """解析消息 XML 里的 @用户列表。"""
+        raw_xml = str(raw_xml or "").strip()
+        if not raw_xml:
+            return []
+
+        at_user_list_text = ""
+        try:
+            root = ET.fromstring(raw_xml)
+            node = root.find(".//atuserlist")
+            if node is not None and node.text:
+                at_user_list_text = str(node.text).strip()
+        except Exception:
+            match = re.search(r"<atuserlist><!\[CDATA\[(.*?)\]\]></atuserlist>", raw_xml, flags=re.IGNORECASE | re.DOTALL)
+            if match:
+                at_user_list_text = str(match.group(1) or "").strip()
+
+        if not at_user_list_text:
+            return []
+
+        seen = set()
+        result: List[str] = []
+        for user_id in re.split(r"[,\s;]+", at_user_list_text):
+            normalized = str(user_id or "").strip()
+            if not normalized or normalized in seen:
+                continue
+            seen.add(normalized)
+            result.append(normalized)
+        return result
+
+    @staticmethod
+    def _normalize_text(value: Any) -> str:
+        """清洗文本中的多余空白。"""
+        text = str(value or "").replace("\u2005", " ").replace("\xa0", " ")
+        text = re.sub(r"\s+", " ", text)
+        return text.strip()
+
+    @staticmethod
+    def _normalize_name(value: str) -> str:
+        """规范化昵称用于模糊匹配。"""
+        text = str(value or "").strip().lower()
+        text = re.sub(r"\s+", "", text)
+        return text