diff --git a/README.md b/README.md
index 3c62e90f..ee282da2 100644
--- a/README.md
+++ b/README.md
@@ -19,7 +19,7 @@ py -3.11 run.py
 python3 run.py
 ```
 
-_Note: The system is currently in **Weather Query Mode**. Active market monitoring and automated trading modules are suspended._
+_Note: The system is currently in **Weather Query Mode**. Legacy active market monitoring and automated trading modules are suspended._
 
 ---
 
@@ -31,92 +31,76 @@ _Note: The system is currently in **Weather Query Mode**. Active market monitori
 | `/id`          | **Get Chat ID**        | Retrieve your current Telegram Chat ID         |
 | `/help`        | **Help**               | Display all available commands                 |
 
-### /city Command Example
-
-```
-/city Chicago
-```
-
-**Real-time Output:**
-
-> 📍 **Chicago 天气详情**  
-> ⏱️ 生成时间: 12:45:30  
-> ════════════════════  
-> 🕐 当地时间: 12:45
->
-> 📊 **Open-Meteo 7天预测**  
-> 👉 今天: 最高 22.4°F (NWS: 23°F)  
->  02-08: 最高 26.2°F  
->  02-09: 最高 37.2°F
->
-> ✈️ **机场实测 (KORD)**  
->  🌡️ 21.0°F (今日最高: 23.0°F)  
->  💨 风速: 4kt  
->  🕐 观测: 12:00 (当地)
->
-> 💡 **态势分析**  
-> ⏱️ **预计峰值时刻**：今天 14:00 - 16:00 之间。  
-> 🎯 **博弈建议**：关注该时段实测能否站稳 22.4°F。  
-> 📈 **升温进程中**：距离峰值还有约 1.4° 空间，正向高点冲击。
-
 ---
 
 ## ✨ Key Features
 
-### 1. 🏛️ Multi-Source Data Fusion
+### 1. 🏛️ Multi-Source Data Fusion (High-Fidelity)
 
-The bot aggregates data from multiple authoritative sources:
+The bot aggregates data from multiple authoritative sources, layered by reliability:
 
-| Source         | Data Type                      | Coverage          |
-| -------------- | ------------------------------ | ----------------- |
-| **Open-Meteo** | 7-day forecast                 | Global            |
-| **NWS**        | Official US forecast           | US cities only ⚠️ |
-| **METAR**      | Real-time airport observations | Global airports   |
+| Source             | Role                    | Coverage        | Strength                                                                           |
+| :----------------- | :---------------------- | :-------------- | :--------------------------------------------------------------------------------- |
+| **Open-Meteo**     | Base Forecast           | Global          | Provides detailed 72-hour temperature curves for all cities.                       |
+| **Meteoblue (MB)** | **Precision Consensus** | Global          | **Traders' choice**. Aggregates multiple models; excellent for microclimates.      |
+| **METAR**          | **Settlement Standard** | Global Airports | The absolute truth for Polymarket settlement; real-time station data.              |
+| **NWS**            | Official (US)           | US Only         | High-fidelity forecasts for US cities, critical for extreme weather events.        |
+| **MGM**            | Official (Turkey)       | Ankara          | Direct access to Turkish State Meteorological Service for local official accuracy. |
 
-- **⚠️ Divergence Alerts**: When Open-Meteo and NWS disagree by >1°F, the bot flags it for your attention.
+### 2. ⚡ Ultra-Fresh Data (Cache-Busting)
 
-### 2. ⏱️ Peak Timing Prediction
+To counter second-by-second variations in weather betting, we implemented **Zero-Cache Technology**:
 
-For each city, the bot analyzes the hourly forecast curve to identify:
+- **Micro-timestamp Tokens**: Every request includes a dynamic token to force servers to bypass CDN caches.
+- **MGM Real-time Sync**: Specialized header camouflaging to bypass local Turkish API anti-crawling for Ankara.
 
-- **Exact peak window**: e.g., "14:00 - 16:00"
-- **Betting recommendation**: Monitor real-time data during this window
+### 3. ⏱️ Automated Trend Analysis
 
-### 3. 📊 Today's High Tracking
+The bot doesn't just fetch data; it interprets it:
 
-METAR data is filtered by **local calendar day** using UTC offset:
+- **Peak Window Prediction**: Automatically identifies the timeframe when today's record is most likely to be hit.
+- **Risk Profiling**: Assigns risk levels based on geographic traits (e.g., Ankara high-altitude swings, London coastal microclimates).
+- **Source Attribution**: Every data point is clearly labeled ([MGM], [METAR], [MB]) to help you weigh the data.
 
-- Only observations from **local midnight onwards** are counted
-- Ensures "Today's High" is accurate, not polluted by yesterday's warm afternoon
+### 4. 📊 Smart Max-Temp Tracking
 
-### 4. ✈️ High-Fidelity Airport Data (METAR)
+Optimized for Polymarket settlement logic:
 
-Directly connected to **NOAA Aviation Weather**, the bot fetches raw METAR data from major international airports.
+- **Local Day Filtering**: Uses city UTC offsets to strictly count observations after 00:00 local time.
+- **Multi-dimension Monitoring**: Includes "Feels Like" temperatures and 24h precipitation to assist in nuanced trade decisions.
 
-- Automatic conversion from UTC to **City Local Time**.
-- Real-time station observations (Temperature, Wind, Dew Point).
+---
 
-### 5. ⚡ Ultra-Fresh Data (Cache Busting)
+## 🏗️ System Architecture
 
-Engineered to bypass ISP and proxy caches:
+PolyWeather uses a **Lightweight, Plugin-based** architecture for millisecond responses.
 
-- Every request includes a **micro-timestamp token**.
-- Forces weather servers (Open-Meteo/NOAA/NWS) to deliver fresh results instead of stale cached snapshots.
+```mermaid
+graph TD
+    User[/Telegram User/] --> Bot[bot_listener.py]
+    Bot --> Collector[WeatherDataCollector]
+
+    subgraph "Data Engine"
+        Collector --> OM[Open-Meteo API]
+        Collector --> MB[Meteoblue Scraper]
+        Collector --> NOAA[METAR Data Center]
+        Collector --> MGM[Turkish MGM API]
+        Collector --> NWS[US NWS API]
+    end
+
+    Collector --> Processing[Smart Analysis & Formatting]
+    Processing --> Bot
+    Bot --> Reponse[/Compact Betting Snapshot/]
+```
+
+- **Logic Decoupling**: `weather_sources.py` handles parsing; `bot_listener.py` handles rendering.
+- **Legacy Modules**: `main.py` contains the old automated trading engine. Focus has shifted to "assisted manual decision-making."
 
 ---
 
 ## 🎯 Betting Strategy Tips
 
-1. **Check model consensus**: If Open-Meteo and NWS agree, confidence is high.
-2. **Watch the peak window**: Monitor METAR during predicted peak hours.
-3. **Use "Today's High"**: Track the actual recorded maximum vs forecast.
-4. **Interpret ⚠️ warnings**: Divergence means uncertainty—proceed with caution.
-
----
-
-## 🏗️ Architecture Note
-
-The project contains a legacy **Monitoring Engine** and **Paper Trading System** (located in `main.py`). These features are currently **deactivated** to prioritize high-speed on-demand weather reporting.
-
-- To re-enable monitoring: Uncomment `monitor_thread.start()` in `run.py`.
-- Documentation for inactive features: See [MARKET_DISCOVERY.md](./MARKET_DISCOVERY.md) and [PAPER_TRADING_GUIDE.md](./PAPER_TRADING_GUIDE.md).
+1. **Check Consensus**: Compare Open-Meteo and Meteoblue (MB). Consensus usually implies higher probability.
+2. **Watch the Peak**: Use `/city` frequently during predicted peak windows to catch momentum.
+3. **Weighting Hierarchy**: Settlement is **METAR**; high-accuracy trend is **MB**; Official (NWS/MGM) is the "anchor."
+4. **Geographic Risk**: Pay close attention to cities where "Bias will significantly amplify."
diff --git a/README_ZH.md b/README_ZH.md
index a0a0a5c4..392999ef 100644
--- a/README_ZH.md
+++ b/README_ZH.md
@@ -34,89 +34,79 @@ _注意：系统当前处于 **天气查询模式**。主动市场监控和自
 ### /city 指令示例
 
 ```
-/city 芝加哥
+/city 伦敦
 ```
 
-**实时输出：**
-
-> 📍 **Chicago 天气详情**  
-> ⏱️ 生成时间: 12:45:30  
-> ════════════════════  
-> 🕐 当地时间: 12:45
->
-> 📊 **Open-Meteo 7天预测**  
-> 👉 今天: 最高 22.4°F (NWS: 23°F)  
->  02-08: 最高 26.2°F  
->  02-09: 最高 37.2°F
->
-> ✈️ **机场实测 (KORD)**  
->  🌡️ 21.0°F (今日最高: 23.0°F)  
->  💨 风速: 4kt  
->  🕐 观测: 12:00 (当地)
->
-> 💡 **态势分析**  
-> ⏱️ **预计峰值时刻**：今天 14:00 - 16:00 之间。  
-> � **博弈建议**：关注该时段实测能否站稳 22.4°F。  
-> 📈 **升温进程中**：距离峰值还有约 1.4° 空间，正向高点冲击。
-
 ---
 
 ## ✨ 核心功能
 
-### 1. 🏛️ 多源数据融合
+### 1. 🏛️ 多源数据融合 (Multi-Source Fusion)
 
-机器人聚合多个权威数据源：
+机器人聚合了全球最权威的几个数据源，并按权重进行分层：
 
-| 数据源         | 数据类型     | 覆盖范围      |
-| -------------- | ------------ | ------------- |
-| **Open-Meteo** | 7天预报      | 全球          |
-| **NWS**        | 美国官方预报 | 仅美国城市 ⚠️ |
-| **METAR**      | 机场实时观测 | 全球主要机场  |
+| 数据源             | 数据角色       | 覆盖范围   | 优势                                             |
+| :----------------- | :------------- | :--------- | :----------------------------------------------- |
+| **Open-Meteo**     | 基础预测       | 全球       | 提供所有城市的 72 小时精细化温度曲线             |
+| **Meteoblue (MB)** | **高精度共识** | 全球       | **交易员首选**。聚合多家模型，对微气候处理极佳   |
+| **METAR**          | **结算标准**   | 全球机场   | Polymarket 结算参考的绝对真理，实时机场观测      |
+| **NWS**            | 官方预测(美)   | 仅限美国   | 美国国家气象局，对美国城市的极端天气预判准确     |
+| **MGM**            | 官方预测(土)   | 仅限安卡拉 | 土耳其气象局，提供安卡拉 Esenboğa 机场的官方数据 |
 
-- **⚠️ 分歧预警**：当 Open-Meteo 和 NWS 预测差异超过 1°F 时，机器人会标注提醒。
+### 2. ⚡ 超新鲜数据 (Cache-Busting)
 
-### 2. ⏱️ 峰值时刻预测
+为了应对气象博弈中秒级的变化，我们实现了 **0 缓存技术**：
 
-机器人分析每个城市的逐小时预报曲线，识别：
+- **微秒级令牌**：每个 API 请求都附带动态时间戳，强制气象服务器绕过 CDN 缓存返回最新值。
+- **MGM 实时同步**：针对土耳其 MGM API 做了专门的 Header 伪装和时区校正。
 
-- **精确峰值窗口**：如 "14:00 - 16:00"
-- **博弈建议**：在此窗口期关注实测数据变化
+### 3. ⏱️ 自动态势分析
 
-### 3. 📊 今日最高温追踪
+机器人不仅仅搬运数据，它还会进行逻辑加工：
 
-METAR 数据按**当地日历日**过滤（使用 UTC 偏移）：
+- **峰值时刻预测**：自动计算今天气温最高点出现的概率窗口（如：14:00 - 15:00）。
+- **风险等级 (Risk-Profile)**：根据地理特征（如安卡拉的高原温差、伦敦的近海微气候）自动分配风险等级。
+- **数据溯源**：报表明确标注每个数字的来源（[MGM], [METAR], [MB]）。
 
-- 只统计**当地零点之后**的观测记录
-- 确保"今日最高"准确，不受昨天下午高温干扰
+### 4. 📊 智能最高温追踪
 
-### 4. ✈️ 高保真机场数据 (METAR)
+针对 Polymarket 的结算逻辑进行优化：
 
-直连 **NOAA 航空气象中心**，获取原始 METAR 数据：
+- **当地日历日过滤**：基于城市 UTC 偏移，严格统计当地时间 00:00 之后的实测最高温。
+- **多维度监测**：集成体感温度 (`feels_like`) 和 24h 累计降雨量，辅助多维度判断。
 
-- 自动将 UTC 时间转换为**城市当地时间**
-- 实时观测（温度、风速、露点）
+---
 
-### 5. ⚡ 超新鲜数据（缓存穿透）
+## 🏗️ 系统架构
 
-专门设计以绕过 ISP 和代理缓存：
+本项目采用 **“轻量化、插件式”** 架构，旨在实现毫秒级响应。
 
-- 每次请求附带**微秒时间戳令牌**
-- 强制 Open-Meteo/NOAA/NWS 返回最新数据
+```mermaid
+graph TD
+    User[/Telegram User/] --> Bot[bot_listener.py]
+    Bot --> Collector[WeatherDataCollector]
+
+    subgraph "Data Engine"
+        Collector --> OM[Open-Meteo API]
+        Collector --> MB[Meteoblue Scraper]
+        Collector --> NOAA[METAR Data Center]
+        Collector --> MGM[Turkish MGM API]
+        Collector --> NWS[US NWS API]
+    end
+
+    Collector --> Processing[智能分析 & 格式化]
+    Processing --> Bot
+    Bot --> Reponse[/精简版博弈快照/]
+```
+
+- **逻辑解耦**：`weather_sources.py` 负责外部数据的解析；`bot_listener.py` 负责消息模板渲染。
+- **遗留模块说明**：项目根目录下的 `main.py` 包含旧版本的自动交易引擎。目前重心在“手动辅助决策”，如需开启请查阅 [MARKET_DISCOVERY_ZH.md](./MARKET_DISCOVERY_ZH.md)。
 
 ---
 
 ## 🎯 博弈策略提示
 
-1. **检查模型共识**：如果 Open-Meteo 和 NWS 一致，置信度高。
-2. **关注峰值窗口**：在预测的峰值时段多次刷新 METAR。
-3. **使用"今日最高"**：对比实测峰值与预报值。
-4. **解读 ⚠️ 警告**：分歧意味着不确定性——谨慎操作。
-
----
-
-## 🏗️ 架构说明
-
-项目包含一个遗留的**监控引擎**和**模拟交易系统**（位于 `main.py`）。这些功能目前**已停用**，以优先保障高速按需天气查询。
-
-- 重新启用监控：取消 `run.py` 中 `monitor_thread.start()` 的注释。
-- 已停用功能的文档：参见 [MARKET_DISCOVERY_ZH.md](./MARKET_DISCOVERY_ZH.md) 和 [PAPER_TRADING_GUIDE.md](./PAPER_TRADING_GUIDE.md)。
+1. **检查模型共识**：查看 Open-Meteo 和 Meteoblue (MB) 是否达成共识。
+2. **关注峰值窗口**：在预测的峰值时段多次使用 `/city` 刷新。
+3. **数据权重优先级**：结算以 **METAR** 为准，趋势预测以 **MB** 为准。
+4. **地理风险评估**：重点关注提示中的“偏差会显著放大”警告（如安卡拉、伦敦）。
diff --git a/bot_listener.py b/bot_listener.py
index 60b68308..54114665 100644
--- a/bot_listener.py
+++ b/bot_listener.py
@@ -274,16 +274,22 @@ def start_bot():
             # 今天对比
             today_t = max_temps[0] if max_temps else "N/A"
             comp_parts = []
+            sources = ["Open-Meteo"]
+            
+            if mb_high is not None:
+                sources.append("MB")
+                comp_parts.append(f"MB: {mb_high}")
             if nws_high is not None:
+                sources.append("NWS")
                 comp_parts.append(f"NWS: {nws_high}")
             if mgm_high is not None:
+                sources.append("MGM")
                 comp_parts.append(f"MGM: {mgm_high}")
-            if mb_high is not None:
-                comp_parts.append(f"MB: {mb_high}")
             
             comp_str = f" ({' | '.join(comp_parts)})" if comp_parts else ""
+            sources_str = " | ".join(sources)
             
-            msg_lines.append(f"\n📊 <b>预报 (Open-Meteo)</b>")
+            msg_lines.append(f"\n📊 <b>预报 ({sources_str})</b>")
             msg_lines.append(f"👉 <b>今天: {today_t}{temp_symbol}{comp_str}</b>")
             
             # 明后天