diff --git a/config.py b/config.py
index 4ac176e..dcbfa42 100644
--- a/config.py
+++ b/config.py
@@ -402,7 +402,7 @@ YOUTUBE_API_KEY = os.getenv('YOUTUBE_API_KEY', '')
 # ==========================================
 # 系統版本與路徑
 # ==========================================
-SYSTEM_VERSION = "V10.605"
+SYSTEM_VERSION = "V10.606"
 LOG_FILE_PATH = os.path.join(BASE_DIR, 'logs/system.log')
 public_url = PUBLIC_URL  # 用於模板顯示
 
diff --git a/docs/AI_INTELLIGENCE_MODULE_SOT.md b/docs/AI_INTELLIGENCE_MODULE_SOT.md
index 5775590..c226173 100644
--- a/docs/AI_INTELLIGENCE_MODULE_SOT.md
+++ b/docs/AI_INTELLIGENCE_MODULE_SOT.md
@@ -1,8 +1,8 @@
-# MOMO PRO — AI 競價情報模組 Single Source of Truth
+# PChome 業績成長自動化作戰系統 — AI 競價情報模組 Single Source of Truth
 
 > **最後更新**: 2026-06-15 (台北時間)
-> **狀態**: 🟢 四 AI Agent 自動化閉環已落地；LLM 路由紅線升級為 Ollama-first 三主機級聯；PChome 後台業績匯入韌性已補強
-> **適用版本**: V10.605
+> **狀態**: 🟢 四 AI Agent 自動化閉環已落地；LLM 路由紅線升級為 Ollama-first 三主機級聯；PChome 後台業績匯入韌性已補強；產品定位正名為「PChome 業績成長自動化作戰系統」
+> **適用版本**: V10.606
 
 ---
 
@@ -45,6 +45,15 @@
 - 111 的 LAN 入口必須經 `scripts/ops/ollama111_allow_proxy.py` allowlist proxy：真實 Ollama 綁 `127.0.0.1:11434`，proxy 綁 `192.168.0.111:11434`，預設只允許 111 本機與 188 生產宿主；110 / 121 / 其他 LAN client 不能直接打 111，避免跨專案 CI 或 VM 繞過 momo-pro router 載入 7B+ runner。111 上以 `scripts/ops/install_ollama111_allow_proxy.sh` 安裝 user LaunchAgent，安裝器會把 proxy script 複製到 `~/.local/share/momo-pro-system/ollama111_allow_proxy.py`，讓 LaunchAgent 不依賴 iCloud repo 掛載路徑，並讓 proxy 與 `OLLAMA_HOST=127.0.0.1:11434` 在登入/重啟後自動恢復。拒絕日誌以 `OLLAMA111_PROXY_REJECT_LOG_DEDUP_SEC=60` 去重，避免 121 這類旁路探測刷爆 111 磁碟日誌。
 - ElephantAlpha 的 `price_drop_alert` / `market_opportunity` Telegram HITL 告警必須把同款證據獨立呈現，至少包含 `match_type`、`price_basis`、`alert_tier` 與 `match_score`；沒有高信心同款與總價可比證據時，不得把 PChome/MOMO 價差寫成可直接跟價建議。
 
+## 零之零、產品定位正名（2026-06-15）
+
+- 本專案的營運定位正名為「PChome 業績成長自動化作戰系統」。
+- 主要目標是提升 PChome 銷售業績；MOMO 是目前已接入的外部價格參考來源，不再把 PChome 視為附屬競品語意。
+- 使用者可見 UI、Telegram 與報表文案必須白話、可行動，優先使用「商品對應」「可直接比價」「待補對應」「放大價格優勢」「檢查售價與活動」等營運語言，避免把 `identity_v2`、`match_score`、`candidate queue` 等工程詞直接丟給使用者。
+- `services/pchome_revenue_growth_service.py` 是第一版只讀作戰清單：讀 PChome 後台業績與已驗證 MOMO 外部價格參考，輸出 `/api/ai/pchome-growth/opportunities`。此服務不呼叫 LLM、不抓外站、不寫 DB。
+- 2026-06-15 只讀盤點確認：`daily_sales_snapshot."商品ID"` 與 `competitor_prices.competitor_product_id` 在正式資料中直接重疊為 0。因此第一版作戰清單不得硬接兩邊 ID；若沒有可驗證對應，只能輸出「先補商品對應」任務。
+- 蝦皮與酷澎暫停接入，不進作戰清單、不發告警；後續只可透過 official API / provider API / manual CSV 進 `external_offers` 類正規化層，並清楚標示資料品質。
+
 ## 零之一、12 Agent 決策信封（2026-05-24）
 
 - 12 角色分工不作為 12 個常駐模型；在產品層統一收斂成 `decision_envelope`，由 Hermes / NemoTron / OpenClaw / ElephantAlpha 與人工審核、PPT QA、競品 review queue 共用。
diff --git a/docs/memory/current_execution_queue_20260524.md b/docs/memory/current_execution_queue_20260524.md
index a920ad0..5fac5db 100644
--- a/docs/memory/current_execution_queue_20260524.md
+++ b/docs/memory/current_execution_queue_20260524.md
@@ -122,6 +122,7 @@
 - 2026-06-02 起，`V10.568` 將價格類 `decision_envelope` 的 Telegram 直送訊息改為專業 brief：標的、價格證據、比對證據、人工下一步四段式；review queue 信封 subject 同步帶 `momo_price` / `competitor_price`，讓 Telegram、PPT、Webcrumbs 與 AI 摘要共用價格證據。
 - 2026-06-02 起，`V10.569` 將 Webcrumbs host data 串到 `summarize_review_decision_envelopes()`，payload 新增 `reviewDecisionBrief` 與 review queue / HITL / auto-execute-blocked metadata；共用 UI runtime 讀同一份 PChome 覆核信封摘要，仍只讀 DB、不呼叫 LLM、不抓外站、不寫資料。
 - 2026-06-15 起，`V10.605` 修正 PChome 後台業績 Excel 匯入韌性：auto import 會掃所有 worksheet / 表頭列並選擇 `即時業績明細` 類明細 sheet，欄位或日期不合格的檔案會移至 Drive `匯入失敗` 避免 30 分鐘重複告警；同版修復 scheduler 容器缺 `pg_dump` 的備份告警。Production 匯入任務 #54 成功寫入 12,460 筆，`daily_sales_snapshot` 與 `realtime_sales_monthly` 最新日期皆為 2026-06-14；資料新鮮度 probe 降為 `gap=1 / info / notified=false`，daily/growth chart runtime guard 通過。
+- 2026-06-15 起，`V10.606` 正名為「PChome 業績成長自動化作戰系統」並新增只讀 `/api/ai/pchome-growth/opportunities`：作戰清單以 PChome 後台業績為主、MOMO 作為外部價格參考，蝦皮與酷澎先暫停且不進告警。正式只讀盤點確認 `daily_sales_snapshot."商品ID"` 與 `competitor_prices.competitor_product_id` 直接重疊為 0，因此第一版不硬接 ID；無可驗證對應時只輸出「先補商品對應」任務。AI 競情頁同步改成白話營運文案，避免把工程術語直接呈現給使用者。
 
 ## 3. 12 Agent 決策信封整合
 
diff --git a/routes/ai_routes.py b/routes/ai_routes.py
index 59ecb3c..8e62cef 100644
--- a/routes/ai_routes.py
+++ b/routes/ai_routes.py
@@ -56,6 +56,11 @@ _ICAIM_DASHBOARD_TTL_SECONDS = 120
 _ICAIM_DASHBOARD_STALE_TTL_SECONDS = 900
 _ICAIM_MATCH_SCORE_FLOOR = 0.76
 _ICAIM_DB_STATEMENT_TIMEOUT_MS = 5000
+_PCHOME_GROWTH_CACHE = {
+    "expires_at": 0.0,
+    "payload": None,
+}
+_PCHOME_GROWTH_TTL_SECONDS = 120
 
 # 服務實例
 ollama_service = OllamaService()
@@ -1596,6 +1601,59 @@ def _create_icaim_dashboard_engine(database_path):
     return create_engine(database_path, **engine_kwargs)
 
 
+def _get_cached_pchome_growth_payload():
+    now_ts = time.time()
+    cached_payload = _PCHOME_GROWTH_CACHE.get("payload")
+    if cached_payload is not None and now_ts < float(_PCHOME_GROWTH_CACHE.get("expires_at") or 0):
+        payload = json.loads(json.dumps(cached_payload, ensure_ascii=False, default=str))
+        payload["cache_state"] = "fresh"
+        return payload
+    return None
+
+
+def _set_pchome_growth_cache(payload):
+    cached = json.loads(json.dumps(payload, ensure_ascii=False, default=str))
+    cached["cache_state"] = "fresh"
+    _PCHOME_GROWTH_CACHE.update({
+        "expires_at": time.time() + _PCHOME_GROWTH_TTL_SECONDS,
+        "payload": cached,
+    })
+
+
+@ai_bp.route('/api/ai/pchome-growth/opportunities')
+@login_required
+def api_pchome_growth_opportunities():
+    """PChome 業績成長自動化作戰清單，只讀、不呼叫 LLM、不寫 DB。"""
+    try:
+        from config import DATABASE_PATH
+        from services.pchome_revenue_growth_service import build_pchome_growth_opportunities
+
+        force_refresh = str(request.args.get('refresh') or '').strip().lower() in {'1', 'true', 'yes'}
+        limit = request.args.get('limit', 20, type=int)
+        limit = max(5, min(limit, 50))
+
+        if not force_refresh:
+            cached_payload = _get_cached_pchome_growth_payload()
+            if cached_payload:
+                return jsonify(cached_payload)
+
+        engine = _create_icaim_dashboard_engine(DATABASE_PATH)
+        try:
+            payload = build_pchome_growth_opportunities(engine, limit=limit)
+        finally:
+            engine.dispose()
+
+        payload["cache_state"] = "fresh"
+        _set_pchome_growth_cache(payload)
+        return jsonify(payload)
+    except Exception as exc:
+        logger.error("[PChomeGrowth] 作戰清單讀取失敗: %s", exc, exc_info=True)
+        return jsonify({
+            "success": False,
+            "error": "PChome 成長作戰清單暫時無法讀取，請稍後再試。",
+        }), 500
+
+
 @ai_bp.route('/api/ai/icaim/dashboard')
 @login_required
 def api_icaim_dashboard():
diff --git a/services/ai_product_pick_agent.py b/services/ai_product_pick_agent.py
index a60791d..3d35975 100644
--- a/services/ai_product_pick_agent.py
+++ b/services/ai_product_pick_agent.py
@@ -14,6 +14,7 @@ AI 建議挑品 Agent
 
 import json
 import logging
+import os
 from dataclasses import dataclass
 from datetime import datetime
 from typing import Any, Dict, List
@@ -107,6 +108,16 @@ def _identity_match_condition(conn, alias: str = "cp") -> str:
     return f"AND COALESCE({alias}.tags, '') LIKE '%identity_v2%'"
 
 
+def _sales_join_by_momo_sku_enabled() -> bool:
+    """舊 MOMO SKU 直連銷售表的路徑預設關閉，避免把 PChome 業績 ID 誤當 MOMO SKU。"""
+    return os.getenv("PCHOME_SALES_JOIN_BY_MOMO_SKU_ENABLED", "false").strip().lower() in {
+        "1",
+        "true",
+        "yes",
+        "on",
+    }
+
+
 def _fetch_candidates_without_sales(conn, limit: int) -> List[Dict[str, Any]]:
     """DB-portable fallback query used when sales-aware PostgreSQL SQL is unavailable."""
     from sqlalchemy import text
@@ -172,7 +183,7 @@ def _fetch_candidates(conn, limit: int) -> List[Dict[str, Any]]:
     sales_join = ""
     sales_select = "0 AS sales_7d, 0 AS sales_prev_7d, 0 AS qty_7d, 0 AS profit_7d, 0 AS cost_7d"
     sales_cols = {}
-    if _has_daily_sales_snapshot(conn):
+    if _sales_join_by_momo_sku_enabled() and _has_daily_sales_snapshot(conn):
         try:
             sales_cols = _daily_sales_columns(conn)
         except Exception as exc:
diff --git a/services/pchome_revenue_growth_service.py b/services/pchome_revenue_growth_service.py
new file mode 100644
index 0000000..54b104f
--- /dev/null
+++ b/services/pchome_revenue_growth_service.py
@@ -0,0 +1,468 @@
+#!/usr/bin/env python3
+# -*- coding: utf-8 -*-
+"""PChome 業績成長自動化作戰系統的只讀作戰清單。"""
+
+from __future__ import annotations
+
+import json
+import logging
+from datetime import datetime
+from typing import Any
+
+from sqlalchemy import bindparam, inspect, text
+
+logger = logging.getLogger(__name__)
+
+SYSTEM_DISPLAY_NAME = "PChome 業績成長自動化作戰系統"
+PRIMARY_SALES_SOURCE = "PChome 後台業績"
+ACTIVE_EXTERNAL_SOURCES = ("MOMO 外部價格參考",)
+PAUSED_EXTERNAL_SOURCES = ("蝦皮", "酷澎")
+
+
+def _to_float(value: Any, default: float = 0.0) -> float:
+    if value is None:
+        return default
+    try:
+        return float(value)
+    except (TypeError, ValueError):
+        return default
+
+
+def _quote_identifier(identifier: str) -> str:
+    return '"' + identifier.replace('"', '""') + '"'
+
+
+def _first_available(columns: set[str], candidates: list[str]) -> str | None:
+    return next((col for col in candidates if col in columns), None)
+
+
+def _load_json_tags(value: Any) -> list[str]:
+    if not value:
+        return []
+    if isinstance(value, list):
+        return value
+    try:
+        parsed = json.loads(value)
+        return parsed if isinstance(parsed, list) else []
+    except Exception:
+        return []
+
+
+def _table_exists(engine, table_name: str) -> bool:
+    try:
+        return inspect(engine).has_table(table_name)
+    except Exception:
+        logger.warning("[PChomeGrowth] table probe failed: %s", table_name, exc_info=True)
+        return False
+
+
+def _daily_sales_columns(conn) -> dict[str, str | None]:
+    if conn.dialect.name == "postgresql":
+        rows = conn.execute(text("""
+            SELECT column_name
+            FROM information_schema.columns
+            WHERE table_name = 'daily_sales_snapshot'
+        """)).fetchall()
+        columns = {row[0] for row in rows}
+    elif conn.dialect.name == "sqlite":
+        rows = conn.execute(text("PRAGMA table_info(daily_sales_snapshot)")).fetchall()
+        columns = {row[1] for row in rows}
+    else:
+        result = conn.execute(text("SELECT * FROM daily_sales_snapshot LIMIT 0"))
+        columns = set(result.keys())
+
+    return {
+        "sku": _first_available(columns, ["商品ID", "Product ID", "ID", "Item Code"]),
+        "name": _first_available(columns, ["商品名稱", "商品名", "品名", "Product Name", "Name"]),
+        "date": _first_available(columns, ["snapshot_date", "日期", "訂單日期", "交易日期", "Date"]),
+        "revenue": _first_available(columns, ["總業績", "銷售金額", "業績", "金額", "Amount", "Sales", "Total"]),
+        "qty": _first_available(columns, ["數量", "銷售數量", "銷量", "Qty", "Quantity"]),
+        "category": _first_available(columns, ["商品館", "館別", "分類", "Category"]),
+        "vendor": _first_available(columns, ["廠商名稱", "供應商", "Vendor"]),
+    }
+
+
+def _as_text_expr(identifier_or_expr: str, dialect_name: str, *, raw: bool = False) -> str:
+    expr = identifier_or_expr if raw else _quote_identifier(identifier_or_expr)
+    if dialect_name == "postgresql":
+        return f"{expr}::text"
+    return f"CAST({expr} AS TEXT)"
+
+
+def _numeric_expr(identifier: str, dialect_name: str) -> str:
+    quoted = _quote_identifier(identifier)
+    if dialect_name == "postgresql":
+        return f"COALESCE(NULLIF(regexp_replace({quoted}::text, '[^0-9.-]', '', 'g'), '')::numeric, 0)"
+    return f"COALESCE(CAST(REPLACE(CAST({quoted} AS TEXT), ',', '') AS REAL), 0)"
+
+
+def _fetch_sales_rows(conn, limit: int) -> tuple[list[dict[str, Any]], str | None]:
+    cols = _daily_sales_columns(conn)
+    missing = [key for key in ["sku", "name", "date", "revenue"] if not cols.get(key)]
+    if missing:
+        raise RuntimeError("PChome 業績檔缺少必要欄位：" + "、".join(missing))
+
+    dialect = conn.dialect.name
+    sku_col = _quote_identifier(cols["sku"])
+    name_col = _quote_identifier(cols["name"])
+    date_col = _quote_identifier(cols["date"])
+    revenue_expr = _numeric_expr(cols["revenue"], dialect)
+    qty_expr = _numeric_expr(cols["qty"], dialect) if cols.get("qty") else "0"
+    category_text = _as_text_expr(cols["category"], dialect) if cols.get("category") else "NULL"
+    vendor_text = _as_text_expr(cols["vendor"], dialect) if cols.get("vendor") else "NULL"
+    sku_text = _as_text_expr(cols["sku"], dialect)
+    name_text = _as_text_expr(cols["name"], dialect)
+    candidate_limit = max(limit * 4, 80)
+
+    if dialect == "postgresql":
+        sale_date_expr = f"NULLIF({date_col}::text, '')::date"
+        curr_window = "lw.latest_date - INTERVAL '6 days'"
+        prev_window_start = "lw.latest_date - INTERVAL '13 days'"
+        prev_window_end = "lw.latest_date - INTERVAL '6 days'"
+    else:
+        sale_date_expr = f"date({date_col})"
+        curr_window = "date(lw.latest_date, '-6 days')"
+        prev_window_start = "date(lw.latest_date, '-13 days')"
+        prev_window_end = "date(lw.latest_date, '-6 days')"
+
+    order_metric = "CASE WHEN sales_7d >= sales_prev_7d THEN sales_7d ELSE sales_prev_7d END"
+    rows = conn.execute(text(f"""
+        WITH sales_rows AS (
+            SELECT
+                NULLIF(TRIM({sku_text}), '') AS pchome_product_id,
+                NULLIF(TRIM({name_text}), '') AS product_name,
+                NULLIF(TRIM({_as_text_expr(category_text, dialect, raw=True)}), '') AS category,
+                NULLIF(TRIM({_as_text_expr(vendor_text, dialect, raw=True)}), '') AS vendor,
+                {sale_date_expr} AS sale_date,
+                {revenue_expr} AS revenue,
+                {qty_expr} AS qty
+            FROM daily_sales_snapshot
+            WHERE {sku_col} IS NOT NULL
+        ),
+        latest_window AS (
+            SELECT MAX(sale_date) AS latest_date
+            FROM sales_rows
+            WHERE sale_date IS NOT NULL
+        ),
+        sales AS (
+            SELECT
+                sr.pchome_product_id,
+                MAX(sr.product_name) AS product_name,
+                MAX(sr.category) AS category,
+                MAX(sr.vendor) AS vendor,
+                SUM(CASE WHEN sr.sale_date >= {curr_window}
+                         THEN sr.revenue ELSE 0 END) AS sales_7d,
+                SUM(CASE WHEN sr.sale_date >= {prev_window_start}
+                          AND sr.sale_date < {prev_window_end}
+                         THEN sr.revenue ELSE 0 END) AS sales_prev_7d,
+                SUM(CASE WHEN sr.sale_date >= {curr_window}
+                         THEN sr.qty ELSE 0 END) AS qty_7d,
+                MAX(sr.sale_date) AS last_sale_date,
+                MAX(lw.latest_date) AS latest_sales_date
+            FROM sales_rows sr
+            CROSS JOIN latest_window lw
+            WHERE sr.pchome_product_id IS NOT NULL
+            GROUP BY sr.pchome_product_id
+        )
+        SELECT *
+        FROM sales
+        WHERE sales_7d > 0 OR sales_prev_7d > 0
+        ORDER BY {order_metric} DESC, qty_7d DESC
+        LIMIT :limit
+    """), {"limit": candidate_limit}).mappings().all()
+
+    mapped_rows = [dict(row) for row in rows]
+    latest_date = None
+    for row in mapped_rows:
+        value = row.get("latest_sales_date")
+        if value:
+            latest_date = value.isoformat() if hasattr(value, "isoformat") else str(value)
+            break
+    return mapped_rows, latest_date
+
+
+def _fetch_external_price_map(conn, pchome_product_ids: list[str]) -> dict[str, dict[str, Any]]:
+    inspector = inspect(conn)
+    if not all(inspector.has_table(table) for table in {"competitor_prices", "products", "price_records"}):
+        return {}
+    ids = [str(item).strip() for item in pchome_product_ids if str(item or "").strip()]
+    if not ids:
+        return {}
+
+    if conn.dialect.name == "postgresql":
+        sql = """
+            WITH valid_cp AS (
+                SELECT DISTINCT ON (cp.competitor_product_id)
+                    cp.competitor_product_id AS pchome_product_id,
+                    cp.competitor_product_name AS pchome_public_name,
+                    cp.sku AS momo_sku,
+                    cp.price AS pchome_price,
+                    cp.match_score,
+                    cp.tags,
+                    cp.crawled_at
+                FROM competitor_prices cp
+                WHERE cp.source = 'pchome'
+                  AND cp.competitor_product_id IS NOT NULL
+                  AND cp.price IS NOT NULL
+                  AND cp.price > 0
+                  AND COALESCE(cp.match_score, 0) >= 0.76
+                  AND (cp.expires_at IS NULL OR cp.expires_at > CURRENT_TIMESTAMP)
+                  AND COALESCE(cp.tags, '[]'::jsonb) ? 'identity_v2'
+                  AND cp.competitor_product_id IN :ids
+                ORDER BY cp.competitor_product_id, cp.crawled_at DESC NULLS LAST
+            )
+            SELECT vc.*, lm.momo_name, lm.momo_price, lm.momo_price_at
+            FROM valid_cp vc
+            LEFT JOIN LATERAL (
+                SELECT
+                    p.name AS momo_name,
+                    pr.price AS momo_price,
+                    pr.timestamp AS momo_price_at
+                FROM products p
+                JOIN price_records pr ON pr.product_id = p.id
+                WHERE p.i_code = vc.momo_sku
+                  AND p.status = 'ACTIVE'
+                ORDER BY pr.timestamp DESC, pr.id DESC
+                LIMIT 1
+            ) lm ON TRUE
+        """
+    else:
+        sql = """
+            WITH latest_cp AS (
+                SELECT
+                    cp.competitor_product_id AS pchome_product_id,
+                    cp.competitor_product_name AS pchome_public_name,
+                    cp.sku AS momo_sku,
+                    cp.price AS pchome_price,
+                    cp.match_score,
+                    cp.tags,
+                    cp.crawled_at,
+                    ROW_NUMBER() OVER (
+                        PARTITION BY cp.competitor_product_id
+                        ORDER BY cp.crawled_at DESC
+                    ) AS rn
+                FROM competitor_prices cp
+                WHERE cp.source = 'pchome'
+                  AND cp.competitor_product_id IS NOT NULL
+                  AND cp.price IS NOT NULL
+                  AND cp.price > 0
+                  AND COALESCE(cp.match_score, 0) >= 0.76
+                  AND COALESCE(cp.tags, '') LIKE '%identity_v2%'
+                  AND cp.competitor_product_id IN :ids
+            ),
+            latest_momo AS (
+                SELECT
+                    p.i_code AS momo_sku,
+                    p.name AS momo_name,
+                    pr.price AS momo_price,
+                    pr.timestamp AS momo_price_at,
+                    ROW_NUMBER() OVER (
+                        PARTITION BY p.i_code
+                        ORDER BY pr.timestamp DESC, pr.id DESC
+                    ) AS rn
+                FROM products p
+                JOIN price_records pr ON pr.product_id = p.id
+                WHERE p.status = 'ACTIVE'
+                  AND p.i_code IN (SELECT momo_sku FROM latest_cp)
+            )
+            SELECT cp.pchome_product_id, cp.pchome_public_name, cp.momo_sku,
+                   cp.pchome_price, cp.match_score, cp.tags, cp.crawled_at,
+                   lm.momo_name, lm.momo_price, lm.momo_price_at
+            FROM latest_cp cp
+            LEFT JOIN latest_momo lm ON lm.momo_sku = cp.momo_sku AND lm.rn = 1
+            WHERE cp.rn = 1
+        """
+
+    stmt = text(sql).bindparams(bindparam("ids", expanding=True))
+    rows = conn.execute(stmt, {"ids": ids}).mappings().all()
+    result: dict[str, dict[str, Any]] = {}
+    for row in rows:
+        key = str(row.get("pchome_product_id") or "").strip()
+        if key:
+            result[key] = dict(row)
+    return result
+
+
+def _score_opportunity(sales_row: dict[str, Any], external_row: dict[str, Any] | None) -> dict[str, Any]:
+    sales_7d = _to_float(sales_row.get("sales_7d"))
+    sales_prev_7d = _to_float(sales_row.get("sales_prev_7d"))
+    qty_7d = _to_float(sales_row.get("qty_7d"))
+    sales_delta_pct = None
+    if sales_prev_7d > 0:
+        sales_delta_pct = (sales_7d - sales_prev_7d) / sales_prev_7d * 100
+
+    volume_score = min(34, max(sales_7d, sales_prev_7d) / 80000 * 34)
+    qty_score = min(10, qty_7d / 25 * 10)
+    decline_score = min(24, abs(sales_delta_pct) / 45 * 24) if sales_delta_pct is not None and sales_delta_pct < 0 else 0
+    data_quality_score = 54
+    external_payload = None
+    action_code = "map_external_product"
+    action_label = "先補商品對應"
+    action_message = "這項商品已有業績訊號，但還沒有可確認的 MOMO 對照商品。先補對應，後續才能判斷價格壓力。"
+    reason_lines = []
+
+    if external_row:
+        pchome_price = _to_float(external_row.get("pchome_price"))
+        momo_price = _to_float(external_row.get("momo_price"))
+        gap_pct = ((momo_price - pchome_price) / pchome_price * 100) if pchome_price else None
+        tags = _load_json_tags(external_row.get("tags"))
+        data_quality_score = 78 + min(12, _to_float(external_row.get("match_score")) * 12)
+        external_payload = {
+            "source": "MOMO",
+            "momo_sku": external_row.get("momo_sku"),
+            "momo_name": external_row.get("momo_name"),
+            "momo_price": round(momo_price, 2) if momo_price else None,
+            "pchome_price": round(pchome_price, 2) if pchome_price else None,
+            "gap_pct": round(gap_pct, 1) if gap_pct is not None else None,
+            "match_score": round(_to_float(external_row.get("match_score")), 3),
+            "tags": tags,
+            "updated_at": str(external_row.get("crawled_at") or ""),
+        }
+
+        if gap_pct is not None and gap_pct < -5:
+            action_code = "review_price_or_promo"
+            action_label = "檢查售價與活動"
+            action_message = "MOMO 外部參考價比較低，建議檢查 PChome 售價、活動組合或曝光策略。"
+        elif gap_pct is not None and gap_pct > 5:
+            action_code = "amplify_price_advantage"
+            action_label = "放大價格優勢"
+            action_message = "PChome 目前有價格優勢，適合檢查曝光、文案與活動位置。"
+        elif sales_delta_pct is not None and sales_delta_pct < -10:
+            action_code = "recover_sales_momentum"
+            action_label = "找回銷售動能"
+            action_message = "價格差距不大，但近 7 天業績轉弱，建議檢查曝光、庫存與商品頁內容。"
+        else:
+            action_code = "monitor"
+            action_label = "持續觀察"
+            action_message = "業績與外部價格暫無明顯異常，先保留在觀察清單。"
+
+        if gap_pct is not None:
+            if gap_pct > 0:
+                reason_lines.append(f"PChome 目前比 MOMO 低約 {abs(gap_pct):.1f}%。")
+            elif gap_pct < 0:
+                reason_lines.append(f"MOMO 目前比 PChome 低約 {abs(gap_pct):.1f}%。")
+            else:
+                reason_lines.append("PChome 與 MOMO 價格幾乎相同。")
+    else:
+        data_quality_score -= 12
+        reason_lines.append("尚未找到可確認的 MOMO 對照商品。")
+
+    if sales_delta_pct is None:
+        reason_lines.append("前 7 天沒有可比基準，先看近 7 天表現。")
+    elif sales_delta_pct < 0:
+        reason_lines.append(f"近 7 天業績比前 7 天少約 {abs(sales_delta_pct):.1f}%。")
+    elif sales_delta_pct > 0:
+        reason_lines.append(f"近 7 天業績比前 7 天多約 {sales_delta_pct:.1f}%。")
+    else:
+        reason_lines.append("近 7 天業績與前 7 天大致持平。")
+
+    if sales_7d > 0:
+        reason_lines.append(f"近 7 天業績約 NT$ {sales_7d:,.0f}，銷量 {qty_7d:,.0f}。")
+
+    mapping_gap_score = 18 if not external_row and max(sales_7d, sales_prev_7d) > 0 else 0
+    priority_score = min(100, volume_score + qty_score + decline_score + mapping_gap_score + data_quality_score * 0.18)
+    if external_payload and external_payload.get("gap_pct") is not None:
+        gap = float(external_payload["gap_pct"])
+        if gap < -5:
+            priority_score = min(100, priority_score + min(18, abs(gap) / 20 * 18))
+        elif gap > 5:
+            priority_score = min(100, priority_score + min(10, gap / 25 * 10))
+
+    issues = []
+    if not external_row:
+        issues.append("需要補商品對應")
+    if sales_delta_pct is None:
+        issues.append("前期業績不足")
+
+    return {
+        "pchome_product_id": str(sales_row.get("pchome_product_id") or ""),
+        "product_name": sales_row.get("product_name") or "未命名商品",
+        "category": sales_row.get("category") or "",
+        "vendor": sales_row.get("vendor") or "",
+        "sales_7d": round(sales_7d, 2),
+        "sales_prev_7d": round(sales_prev_7d, 2),
+        "sales_delta_pct": round(sales_delta_pct, 1) if sales_delta_pct is not None else None,
+        "qty_7d": round(qty_7d, 2),
+        "last_sale_date": str(sales_row.get("last_sale_date") or ""),
+        "external_price": external_payload,
+        "priority_score": round(priority_score, 1),
+        "recommended_action": {
+            "code": action_code,
+            "label": action_label,
+            "message": action_message,
+        },
+        "reason_lines": reason_lines[:4],
+        "data_quality": {
+            "label": "資料可直接判斷" if external_row else "需要補資料",
+            "score": round(max(0, min(100, data_quality_score)), 1),
+            "issues": issues,
+        },
+    }
+
+
+def build_pchome_growth_opportunities(engine, limit: int = 20) -> dict[str, Any]:
+    """讀取 PChome 業績與已驗證外部價格，產生營運用作戰清單。"""
+    limit = max(5, min(int(limit or 20), 50))
+    generated_at = datetime.now().isoformat(timespec="seconds")
+    source_scope = {
+        "primary_goal": "提升 PChome 業績",
+        "primary_sales_source": PRIMARY_SALES_SOURCE,
+        "active_external_sources": list(ACTIVE_EXTERNAL_SOURCES),
+        "paused_external_sources": list(PAUSED_EXTERNAL_SOURCES),
+        "plain_note": "蝦皮與酷澎先暫停，不進作戰清單，也不發告警。",
+    }
+
+    if not _table_exists(engine, "daily_sales_snapshot"):
+        return {
+            "success": True,
+            "system_name": SYSTEM_DISPLAY_NAME,
+            "generated_at": generated_at,
+            "source_scope": source_scope,
+            "stats": {
+                "latest_sales_date": None,
+                "candidate_count": 0,
+                "mapped_count": 0,
+                "mapping_rate": 0,
+                "needs_mapping_count": 0,
+            },
+            "opportunities": [],
+            "message": "目前還沒有 PChome 業績資料，請先完成業績匯入。",
+        }
+
+    with engine.connect() as conn:
+        sales_rows, latest_sales_date = _fetch_sales_rows(conn, limit=limit)
+        sales_ids = [str(row.get("pchome_product_id") or "") for row in sales_rows]
+        external_map = _fetch_external_price_map(conn, sales_ids)
+
+    opportunities = []
+    for row in sales_rows:
+        key = str(row.get("pchome_product_id") or "").strip()
+        opportunities.append(_score_opportunity(row, external_map.get(key)))
+
+    opportunities.sort(key=lambda item: item["priority_score"], reverse=True)
+    opportunities = opportunities[:limit]
+    needs_mapping_count = sum(1 for item in opportunities if not item.get("external_price"))
+    mapped_count = len(opportunities) - needs_mapping_count
+    mapping_rate = round(mapped_count / max(len(opportunities), 1) * 100, 1)
+    action_counts: dict[str, int] = {}
+    for item in opportunities:
+        label = item["recommended_action"]["label"]
+        action_counts[label] = action_counts.get(label, 0) + 1
+
+    return {
+        "success": True,
+        "system_name": SYSTEM_DISPLAY_NAME,
+        "generated_at": generated_at,
+        "source_scope": source_scope,
+        "stats": {
+            "latest_sales_date": latest_sales_date,
+            "candidate_count": len(opportunities),
+            "mapped_count": mapped_count,
+            "mapping_rate": mapping_rate,
+            "needs_mapping_count": needs_mapping_count,
+            "total_sales_7d": round(sum(_to_float(item.get("sales_7d")) for item in opportunities), 2),
+            "action_counts": action_counts,
+        },
+        "opportunities": opportunities,
+        "message": "已整理今日 PChome 業績成長作戰清單。",
+    }
diff --git a/templates/ai_intelligence.html b/templates/ai_intelligence.html
index 871ebdb..18af13b 100644
--- a/templates/ai_intelligence.html
+++ b/templates/ai_intelligence.html
@@ -1,5 +1,5 @@
 {% extends 'ewoooc_base.html' %}
-{% block title %}AI 競情中樞 · EwoooC{% endblock %}
+{% block title %}PChome 業績成長自動化作戰系統 · EwoooC{% endblock %}
 
 {% block extra_css %}
 <style>
@@ -233,6 +233,97 @@
         background: rgba(250, 247, 240, 0.54);
     }
 
+    .growth-ops-grid {
+        display: grid;
+        grid-template-columns: minmax(0, 0.9fr) minmax(0, 1.7fr);
+        gap: 14px;
+    }
+
+    .growth-metric-row {
+        display: grid;
+        grid-template-columns: repeat(3, minmax(0, 1fr));
+        gap: 8px;
+    }
+
+    .growth-metric {
+        border: 1px solid var(--momo-border-subtle);
+        border-radius: 8px;
+        background: rgba(250, 247, 240, 0.62);
+        padding: 10px;
+    }
+
+    .growth-metric strong {
+        display: block;
+        color: var(--momo-text-strong);
+        font-family: var(--momo-font-mono);
+        font-size: 1.35rem;
+        line-height: 1.1;
+    }
+
+    .growth-metric span {
+        color: var(--momo-text-muted);
+        font-size: 0.75rem;
+        font-weight: 800;
+    }
+
+    .growth-source-note {
+        margin-top: 10px;
+        color: var(--momo-text-muted);
+        font-size: 0.82rem;
+        line-height: 1.55;
+    }
+
+    .growth-list {
+        display: grid;
+        gap: 8px;
+        max-height: 292px;
+        overflow-y: auto;
+        padding-right: 4px;
+    }
+
+    .growth-item {
+        display: grid;
+        grid-template-columns: minmax(0, 1fr) auto;
+        gap: 10px;
+        align-items: start;
+        border: 1px solid rgba(42, 37, 32, 0.1);
+        border-radius: 8px;
+        background: rgba(255, 255, 255, 0.78);
+        padding: 10px 12px;
+    }
+
+    .growth-item-title {
+        margin: 0;
+        color: var(--momo-text-strong);
+        font-size: 0.9rem;
+        font-weight: 800;
+        line-height: 1.35;
+    }
+
+    .growth-item-meta,
+    .growth-item-reason {
+        margin: 4px 0 0;
+        color: var(--momo-text-muted);
+        font-size: 0.78rem;
+        line-height: 1.45;
+    }
+
+    .growth-action-pill {
+        display: inline-flex;
+        align-items: center;
+        justify-content: center;
+        min-width: 92px;
+        border: 1px solid rgba(42, 37, 32, 0.12);
+        border-radius: 999px;
+        background: rgba(242, 178, 90, 0.2);
+        color: var(--momo-text-strong);
+        font-size: 0.74rem;
+        font-weight: 900;
+        padding: 5px 8px;
+        text-align: center;
+        white-space: nowrap;
+    }
+
     @media (max-width: 992px) {
         .ai-intel-hero {
             grid-template-columns: 1fr;
@@ -332,8 +423,8 @@
         #competitorTable td:nth-child(2)::before { content: "MOMO"; }
         #competitorTable td:nth-child(3)::before { content: "PChome"; }
         #competitorTable td:nth-child(4)::before { content: "價差"; }
-        #competitorTable td:nth-child(5)::before { content: "標籤"; }
-        #competitorTable td:nth-child(6)::before { content: "分數"; }
+        #competitorTable td:nth-child(5)::before { content: "狀態"; }
+        #competitorTable td:nth-child(6)::before { content: "可信度"; }
         #competitorTable td:nth-child(7)::before { content: "更新"; }
 
         .ai-panel .card-footer {
@@ -341,6 +432,15 @@
             flex-direction: column;
             gap: 4px;
         }
+
+        .growth-ops-grid,
+        .growth-metric-row {
+            grid-template-columns: 1fr;
+        }
+
+        .growth-item {
+            grid-template-columns: 1fr;
+        }
     }
 </style>
 {% endblock %}
@@ -353,23 +453,23 @@
         <div>
             <h1 class="ai-intel-title">
                 <i class="fas fa-brain"></i>
-                AI 競情中樞
-                <span class="ai-intel-badge">ICAIM</span>
+                PChome 業績成長自動化作戰系統
+                <span class="ai-intel-badge">AI 競情中樞</span>
             </h1>
-            <p class="ai-intel-subtitle">Hermes 3 分析師 × NemoTron 派發器，使用資料庫內的競品價格、AI 決策與 PChome 比對記錄進行監控。</p>
+            <p class="ai-intel-subtitle">把 PChome 後台業績、MOMO 外部價格參考與商品對應狀態整理成每天可處理的作戰清單。</p>
         </div>
         <div class="ai-intel-actions">
             <span id="lastUpdateBadge" class="ai-status-badge">
                 <i class="fas fa-sync me-1"></i>載入中...
             </span>
             <button class="btn btn-outline-danger btn-sm ai-action-btn" id="btnTrigger" onclick="triggerAnalysis()">
-                <i class="fas fa-bolt me-1"></i>立即分析
+                <i class="fas fa-bolt me-1"></i>整理建議
             </button>
             <button class="btn btn-outline-primary btn-sm ai-action-btn" id="btnPickList" onclick="generatePickList()">
-                <i class="fas fa-wand-magic-sparkles me-1"></i>產生挑品清單
+                <i class="fas fa-wand-magic-sparkles me-1"></i>產生作戰商品
             </button>
             <button class="btn btn-outline-warning btn-sm ai-action-btn" id="btnBackfill" onclick="backfillPchomeMatches()">
-                <i class="fas fa-magnifying-glass-chart me-1"></i>補抓未搜尋
+                <i class="fas fa-magnifying-glass-chart me-1"></i>補商品對應
             </button>
             <button class="btn btn-outline-secondary btn-sm ai-action-btn" onclick="loadDashboard()">
                 <i class="fas fa-redo me-1"></i>重新整理
@@ -377,6 +477,47 @@
         </div>
     </section>
 
+    <!-- ── PChome 成長作戰清單 ── -->
+    <section class="card shadow-sm ai-panel" id="growthOpsPanel">
+        <div class="card-header d-flex justify-content-between align-items-center py-2 bg-white border-bottom">
+            <span class="ai-panel-title">
+                <i class="fas fa-compass"></i>PChome 成長作戰
+                <small class="text-muted fw-normal ms-2">先處理最可能影響業績的商品</small>
+            </span>
+            <button class="btn btn-outline-secondary btn-sm ai-action-btn" onclick="loadGrowthOps(true)">
+                <i class="fas fa-redo me-1"></i>更新清單
+            </button>
+        </div>
+        <div class="card-body">
+            <div class="growth-ops-grid">
+                <div>
+                    <div class="growth-metric-row">
+                        <div class="growth-metric">
+                            <strong id="growthCandidateCount">—</strong>
+                            <span>作戰商品</span>
+                        </div>
+                        <div class="growth-metric">
+                            <strong id="growthMappedCount">—</strong>
+                            <span>可直接比價</span>
+                        </div>
+                        <div class="growth-metric">
+                            <strong id="growthNeedsMapping">—</strong>
+                            <span>待補對應</span>
+                        </div>
+                    </div>
+                    <p class="growth-source-note" id="growthSourceNote">來源整理中...</p>
+                </div>
+                <div>
+                    <div class="growth-list" id="growthOpsList">
+                        <div class="text-center py-4 text-muted">
+                            <div class="spinner-border spinner-border-sm me-2"></div>整理作戰清單中...
+                        </div>
+                    </div>
+                </div>
+            </div>
+        </div>
+    </section>
+
     <!-- ── KPI 卡片 ── -->
     <div class="row g-3 mb-4" id="kpiRow">
         <div class="col-6 col-md-3">
@@ -392,7 +533,7 @@
                 <div class="card-body text-center py-3">
                     <div class="fs-2 fw-bold text-success" id="kpiCompetitors">—</div>
                     <div class="small text-muted mt-1">
-                        <i class="fas fa-store me-1"></i>有效競品比價
+                        <i class="fas fa-store me-1"></i>可直接比價
                         <span id="kpiMatchRate" class="text-muted" style="font-size:0.7rem"></span>
                     </div>
                 </div>
@@ -404,8 +545,7 @@
                 <div class="card-body text-center py-3">
                     <div class="fs-2 fw-bold text-danger" id="kpiHighRisk">—</div>
                     <div class="small text-muted mt-1">
-                        <i class="fas fa-exclamation-triangle me-1"></i>高風險商品
-                        <span class="text-muted" style="font-size:0.7rem">(貴&gt;15%)</span>
+                        <i class="fas fa-exclamation-triangle me-1"></i>需檢查價格
                     </div>
                 </div>
             </div>
@@ -414,7 +554,7 @@
             <div class="card border-0 shadow-sm h-100">
                 <div class="card-body text-center py-3">
                     <div class="fs-2 fw-bold text-info" id="kpiAiRecs">—</div>
-                    <div class="small text-muted mt-1"><i class="fas fa-robot me-1"></i>AI 挑品/決策記錄</div>
+                    <div class="small text-muted mt-1"><i class="fas fa-robot me-1"></i>作戰建議紀錄</div>
                 </div>
             </div>
         </div>
@@ -423,12 +563,12 @@
     <!-- ── 主體分兩欄（競品比價 + AI 決策） ── -->
     <div class="row g-3">
 
-        <!-- ── 左：PChome 競品比價 ── -->
+        <!-- ── 左：外部價格參考 ── -->
         <div class="col-xl-7">
             <div class="card shadow-sm h-100 ai-panel">
                 <div class="card-header d-flex justify-content-between align-items-center py-2 bg-white border-bottom">
                     <span class="ai-panel-title">
-                        <i class="fas fa-balance-scale text-warning me-2"></i>PChome 競品比價監控
+                        <i class="fas fa-balance-scale text-warning me-2"></i>MOMO 外部價格參考
                     </span>
                     <div class="d-flex gap-2 align-items-center">
                         <select class="form-select form-select-sm" id="riskFilter" onchange="filterTable()" style="width:100px">
@@ -455,8 +595,8 @@
                                 <th class="text-end" style="min-width:75px">MOMO</th>
                                 <th class="text-end" style="min-width:75px">PChome</th>
                                 <th class="text-end" style="min-width:70px">價差</th>
-                                <th style="min-width:90px">競品標籤</th>
-                                <th class="text-center" style="min-width:55px">分數</th>
+                                <th style="min-width:90px">比價狀態</th>
+                                <th class="text-center" style="min-width:55px">可信度</th>
                                 <th class="text-muted" style="min-width:80px">更新</th>
                             </tr>
                         </thead>
@@ -469,18 +609,18 @@
                 </div>
                 <div class="card-footer bg-white py-2 d-flex justify-content-between small text-muted">
                     <span id="compCount">—</span>
-                    <span>僅顯示已通過身份比對的競品</span>
+                    <span>僅顯示已確認同款的商品</span>
                 </div>
             </div>
         </div>
 
-        <!-- ── 右：AI 決策日誌 ── -->
+        <!-- ── 右：作戰建議紀錄 ── -->
         <div class="col-xl-5">
             <div class="card shadow-sm h-100 ai-panel">
                 <div class="card-header py-2 bg-white border-bottom">
                     <span class="ai-panel-title">
-                        <i class="fas fa-robot text-danger me-2"></i>AI 決策日誌
-                        <small class="text-muted fw-normal ms-2">挑品 Agent × Hermes × NemoTron</small>
+                        <i class="fas fa-robot text-danger me-2"></i>作戰建議紀錄
+                        <small class="text-muted fw-normal ms-2">挑品、比價與人工覆核</small>
                     </span>
                 </div>
                 <div class="card-body p-0 ai-recs-scroll">
@@ -492,7 +632,7 @@
                 </div>
                 <div class="card-footer bg-white py-2 d-flex justify-content-between small text-muted">
                     <span id="aiRecsCount">—</span>
-                    <span>可手動產生挑品清單</span>
+                    <span>可手動產生作戰商品</span>
                 </div>
             </div>
         </div>
@@ -518,7 +658,10 @@
 let allCompetitors = [];
 
 // ── 頁面載入 ────────────────────────────────────────
-document.addEventListener('DOMContentLoaded', loadDashboard);
+document.addEventListener('DOMContentLoaded', () => {
+    loadDashboard();
+    loadGrowthOps();
+});
 
 async function loadDashboard() {
     try {
@@ -558,6 +701,86 @@ function renderKPIs(stats) {
             : 'card border-0 shadow-sm h-100';
 }
 
+function formatMoney(value) {
+    const num = Number(value || 0);
+    return 'NT$ ' + Math.round(num).toLocaleString();
+}
+
+function escapeHtml(value) {
+    return String(value ?? '').replace(/[&<>"']/g, (ch) => ({
+        '&': '&amp;',
+        '<': '&lt;',
+        '>': '&gt;',
+        '"': '&quot;',
+        "'": '&#39;',
+    }[ch]));
+}
+
+async function loadGrowthOps(forceRefresh = false) {
+    const list = document.getElementById('growthOpsList');
+    if (forceRefresh) {
+        list.innerHTML = `<div class="text-center py-4 text-muted">
+            <div class="spinner-border spinner-border-sm me-2"></div>更新作戰清單中...
+        </div>`;
+    }
+
+    try {
+        const url = '/api/ai/pchome-growth/opportunities?limit=8' + (forceRefresh ? '&refresh=1' : '');
+        const res = await fetch(url);
+        const data = await res.json();
+        if (!data.success) throw new Error(data.error || '讀取失敗');
+
+        const stats = data.stats || {};
+        document.getElementById('growthCandidateCount').textContent = (stats.candidate_count || 0).toLocaleString();
+        document.getElementById('growthMappedCount').textContent = (stats.mapped_count || 0).toLocaleString();
+        document.getElementById('growthNeedsMapping').textContent = (stats.needs_mapping_count || 0).toLocaleString();
+
+        const scope = data.source_scope || {};
+        const active = (scope.active_external_sources || []).join('、') || '尚未接入';
+        const paused = (scope.paused_external_sources || []).join('、') || '無';
+        document.getElementById('growthSourceNote').textContent =
+            `業績來源：${scope.primary_sales_source || 'PChome 後台業績'}。外部價格先看：${active}。暫停來源：${paused}。`;
+
+        renderGrowthOps(data.opportunities || []);
+    } catch (error) {
+        console.error(error);
+        list.innerHTML = `<div class="text-center py-4 text-muted">
+            <i class="fas fa-circle-exclamation d-block mb-2"></i>
+            PChome 成長作戰清單暫時無法讀取，請稍後再試。
+        </div>`;
+    }
+}
+
+function renderGrowthOps(rows) {
+    const list = document.getElementById('growthOpsList');
+    if (!rows.length) {
+        list.innerHTML = `<div class="text-center py-4 text-muted">
+            <i class="fas fa-circle-info d-block mb-2"></i>
+            目前沒有足夠資料，請先確認 PChome 業績檔已匯入。
+        </div>`;
+        return;
+    }
+
+    list.innerHTML = rows.map((row) => {
+        const action = row.recommended_action || {};
+        const reason = (row.reason_lines || []).slice(0, 2).join(' ');
+        const price = row.external_price;
+        const priceText = price && price.gap_pct !== null && price.gap_pct !== undefined
+            ? `外部價差 ${price.gap_pct > 0 ? '+' : ''}${price.gap_pct}%`
+            : '尚未可比價';
+        return `<article class="growth-item">
+            <div>
+                <h3 class="growth-item-title">${escapeHtml(row.product_name)}</h3>
+                <p class="growth-item-meta">
+                    ${formatMoney(row.sales_7d)} · 近 7 天業績 · ${escapeHtml(priceText)}
+                </p>
+                <p class="growth-item-reason">${escapeHtml(reason)}</p>
+            </div>
+            <span class="growth-action-pill">${escapeHtml(action.label || '待判斷')}</span>
+        </article>`;
+    }).join('');
+}
+
 // ── 競品比價表格（熱力圖底色）──────────────────────
 function renderCompetitorTable(rows) {
     const tbody = document.getElementById('competitorTbody');
@@ -570,7 +793,7 @@ function renderCompetitorTable(rows) {
     }
 
     tbody.innerHTML = rows.map(r => {
-        // 熱力圖底色（行層級）
+        // 行底色
         let rowBg = '';
         if (r.gap_pct > 20)       rowBg = 'background:#fee2e2';   // 淺紅 — 嚴重貴
         else if (r.gap_pct > 10)  rowBg = 'background:#fef9c3';   // 淺黃 — 有風險
@@ -595,7 +818,7 @@ function renderCompetitorTable(rows) {
                 'match_type_exact':['bg-success text-white',  '同款確認'],
                 'price_alert_exact':['bg-danger text-white',  '價差告警'],
                 'evidence_brand':  ['bg-light text-dark',     '品牌一致'],
-                'evidence_identity':['bg-light text-dark',    '身份證據'],
+                'evidence_identity':['bg-light text-dark',    '同款證據'],
                 'match_shared_model_token':['bg-light text-dark','型號一致'],
                 'match_product_line':['bg-light text-dark',   '品線一致'],
                 'alert_tier_price':['bg-warning text-dark',   '優先追蹤'],
@@ -640,23 +863,22 @@ function filterTable() {
     renderCompetitorTable(filtered);
 }
 
-// ── AI 決策日誌（含推理足跡）───────────────────────
+// ── 作戰建議紀錄 ────────────────────────
 function renderAiRecs(recs) {
     const container = document.getElementById('aiRecsList');
     document.getElementById('aiRecsCount').textContent =
-        recs.length ? `共 ${recs.length} 筆決策記錄` : '尚無決策記錄';
+        recs.length ? `共 ${recs.length} 筆建議` : '尚無建議';
 
     if (!recs.length) {
         container.innerHTML = `
         <div class="text-center py-5">
             <i class="fas fa-brain fa-3x text-muted mb-3 d-block"></i>
-            <p class="text-muted mb-1">AI 決策日誌尚為空</p>
+            <p class="text-muted mb-1">目前還沒有作戰建議</p>
             <p class="small text-muted mb-3">
-                排程每 6 小時執行一次 Hermes 分析 + NemoTron 派發<br>
-                或點擊「立即分析」手動觸發
+                系統會定期整理，也可以手動更新。
             </p>
             <button class="btn btn-sm btn-outline-danger" onclick="triggerAnalysis()">
-                <i class="fas fa-bolt me-1"></i>立即觸發分析
+                <i class="fas fa-bolt me-1"></i>整理建議
             </button>
         </div>`;
         return;
@@ -676,14 +898,6 @@ function renderAiRecs(recs) {
         const confColor     = confPct >= 80 ? 'bg-success' : confPct >= 60 ? 'bg-warning' : 'bg-danger';
         const gapSign       = r.gap_pct > 0 ? '+' : '';
 
-        // 推理足跡
-        const hermesInfo = r.hermes_duration
-            ? `${r.analyst} ${r.hermes_duration}s${r.hermes_tokens ? ' / ' + r.hermes_tokens + 'tok' : ''}`
-            : r.analyst;
-        const nimInfo = r.nim_tokens
-            ? `${r.dispatcher} ${r.nim_tokens}tok`
-            : r.dispatcher;
-
         return `<div class="border rounded mb-2 p-2" style="font-size:0.83rem">
             <div class="d-flex justify-content-between align-items-start mb-1">
                 <span class="fw-bold text-truncate me-2" style="max-width:200px" title="${r.name}">${r.name}</span>
@@ -704,9 +918,8 @@ function renderAiRecs(recs) {
                     </div>
                     <small class="text-muted">${confPct}%</small>
                 </div>
-                <small class="text-muted" title="推理足跡">
-                    <i class="fas fa-microchip me-1" style="font-size:0.68rem"></i>${hermesInfo} → ${nimInfo}
-                    · ${r.created_at}
+                <small class="text-muted">
+                    ${r.created_at}
                 </small>
             </div>
         </div>`;
@@ -720,7 +933,7 @@ async function generatePickList() {
     const msg = document.getElementById('triggerToastMsg');
 
     btn.disabled = true;
-    btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>挑品中...';
+    btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>整理中...';
 
     try {
         const res = await fetch('/api/ai/product-picks/generate', {
@@ -739,12 +952,12 @@ async function generatePickList() {
 
         if (data.success) loadDashboard();
     } catch (e) {
-        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>挑品失敗：' + e.message;
+        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>整理失敗：' + e.message;
         toast.className = 'toast align-items-center text-white border-0 bg-danger';
         new bootstrap.Toast(toast, { delay: 4000 }).show();
     } finally {
         btn.disabled = false;
-        btn.innerHTML = '<i class="fas fa-wand-magic-sparkles me-1"></i>產生挑品清單';
+        btn.innerHTML = '<i class="fas fa-wand-magic-sparkles me-1"></i>產生作戰商品';
     }
 }
 
@@ -755,7 +968,7 @@ async function backfillPchomeMatches() {
     const msg = document.getElementById('triggerToastMsg');
 
     btn.disabled = true;
-    btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>補抓中...';
+    btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>整理中...';
 
     try {
         const res = await fetch('/api/ai/pchome-match/backfill', {
@@ -767,19 +980,19 @@ async function backfillPchomeMatches() {
 
         msg.innerHTML = data.success
             ? `<i class="fas fa-check-circle me-1"></i>${data.message}`
-            : `<i class="fas fa-times-circle me-1"></i>${data.error || '補抓啟動失敗'}`;
+            : `<i class="fas fa-times-circle me-1"></i>${data.error || '商品對應啟動失敗'}`;
         toast.className = 'toast align-items-center text-white border-0 ' +
                           (data.success ? 'bg-success' : 'bg-danger');
         new bootstrap.Toast(toast, { delay: 6000 }).show();
 
         if (data.success) setTimeout(loadDashboard, 90000);
     } catch (e) {
-        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>補抓失敗：' + e.message;
+        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>商品對應失敗：' + e.message;
         toast.className = 'toast align-items-center text-white border-0 bg-danger';
         new bootstrap.Toast(toast, { delay: 4000 }).show();
     } finally {
         btn.disabled = false;
-        btn.innerHTML = '<i class="fas fa-magnifying-glass-chart me-1"></i>補抓未搜尋';
+        btn.innerHTML = '<i class="fas fa-magnifying-glass-chart me-1"></i>補商品對應';
     }
 }
 
@@ -790,7 +1003,7 @@ async function triggerAnalysis() {
     const msg   = document.getElementById('triggerToastMsg');
 
     btn.disabled = true;
-    btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>啟動中...';
+        btn.innerHTML = '<span class="spinner-border spinner-border-sm me-1"></span>整理中...';
 
     try {
         const res  = await fetch('/api/ai/icaim/trigger', { method: 'POST' });
@@ -809,12 +1022,12 @@ async function triggerAnalysis() {
             setTimeout(loadDashboard, 60000);
         }
     } catch (e) {
-        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>觸發失敗：' + e.message;
+        msg.innerHTML = '<i class="fas fa-times-circle me-1"></i>整理失敗：' + e.message;
         toast.className = 'toast align-items-center text-white border-0 bg-danger';
         new bootstrap.Toast(toast, { delay: 4000 }).show();
     } finally {
         btn.disabled = false;
-        btn.innerHTML = '<i class="fas fa-bolt me-1"></i>立即分析';
+        btn.innerHTML = '<i class="fas fa-bolt me-1"></i>整理建議';
     }
 }
 </script>
diff --git a/tests/test_frontend_v2_assets.py b/tests/test_frontend_v2_assets.py
index 6e815d0..6ab1824 100644
--- a/tests/test_frontend_v2_assets.py
+++ b/tests/test_frontend_v2_assets.py
@@ -379,13 +379,15 @@ def test_ai_intelligence_uses_v2_shell_and_real_runtime_apis():
     assert "{% block ewooo_content %}" in template
     assert "ai-intel-hero" in template
     assert "ai-status-badge" in template
-    assert "PChome 競品比價監控" in template
-    assert "AI 決策日誌" in template
+    assert "PChome 業績成長自動化作戰系統" in template
+    assert "MOMO 外部價格參考" in template
+    assert "/api/ai/pchome-growth/opportunities" in template
+    assert "作戰建議紀錄" in template
     assert "fetch('/api/ai/icaim/dashboard')" in template
     assert "fetch('/api/ai/product-picks/generate'" in template
     assert "fetch('/api/ai/pchome-match/backfill'" in template
     assert "JSON.stringify({ limit: 50 })" in template
-    assert "僅顯示已通過身份比對的競品" in template
+    assert "僅顯示已確認同款的商品" in template
     assert "tagMap[t] || ['bg-light text-dark', t]" not in template
     assert "\"match_type_exact\":[" not in template
     assert "'match_type_exact':[" in template
@@ -684,8 +686,8 @@ def test_ai_product_pick_agent_uses_real_competitor_data_and_dashboard_action():
     assert "每日 10:30：pchome_match_backfill" in run_scheduler_source
     assert '"run_pchome_match_backfill_task"' in agent_actions_source
 
-    assert "產生挑品清單" in template
-    assert "補抓未搜尋" in template
+    assert "產生作戰商品" in template
+    assert "補商品對應" in template
     assert "generatePickList" in template
     assert "backfillPchomeMatches" in template
     assert "/api/ai/product-picks/generate" in template
diff --git a/tests/test_pchome_revenue_growth_service.py b/tests/test_pchome_revenue_growth_service.py
new file mode 100644
index 0000000..299ab13
--- /dev/null
+++ b/tests/test_pchome_revenue_growth_service.py
@@ -0,0 +1,87 @@
+from sqlalchemy import create_engine, text
+
+
+def _seed_growth_tables(engine):
+    with engine.begin() as conn:
+        conn.execute(text(
+            'CREATE TABLE daily_sales_snapshot ('
+            '"商品ID" TEXT, "商品名稱" TEXT, snapshot_date TEXT, "總業績" REAL, "數量" REAL, "商品館" TEXT)'
+        ))
+        conn.execute(text(
+            "CREATE TABLE competitor_prices ("
+            "sku TEXT, source TEXT, competitor_product_id TEXT, competitor_product_name TEXT, "
+            "price REAL, match_score REAL, tags TEXT, crawled_at TEXT, expires_at TEXT)"
+        ))
+        conn.execute(text(
+            "CREATE TABLE products ("
+            "id INTEGER PRIMARY KEY, i_code TEXT, name TEXT, status TEXT)"
+        ))
+        conn.execute(text(
+            "CREATE TABLE price_records ("
+            "id INTEGER PRIMARY KEY, product_id INTEGER, price REAL, timestamp TEXT)"
+        ))
+        conn.execute(text("""
+            INSERT INTO daily_sales_snapshot
+                ("商品ID", "商品名稱", snapshot_date, "總業績", "數量", "商品館")
+            VALUES
+                ('PCH-1', '高業績商品', '2026-06-14', 120000, 36, '保養'),
+                ('PCH-1', '高業績商品', '2026-06-08', 180000, 50, '保養'),
+                ('PCH-2', '待補對應商品', '2026-06-14', 90000, 18, '彩妝'),
+                ('PCH-2', '待補對應商品', '2026-06-08', 30000, 8, '彩妝')
+        """))
+        conn.execute(text(
+            "INSERT INTO products (id, i_code, name, status) "
+            "VALUES (1, 'MOMO-1', 'MOMO 參考商品', 'ACTIVE')"
+        ))
+        conn.execute(text(
+            "INSERT INTO price_records (product_id, price, timestamp) "
+            "VALUES (1, 900, '2026-06-14 10:00:00')"
+        ))
+        conn.execute(text("""
+            INSERT INTO competitor_prices
+                (sku, source, competitor_product_id, competitor_product_name,
+                 price, match_score, tags, crawled_at, expires_at)
+            VALUES
+                ('MOMO-1', 'pchome', 'PCH-1', '高業績商品',
+                 1000, 0.91, '["identity_v2","match_type_exact"]', '2026-06-14 11:00:00', NULL)
+        """))
+
+
+def test_pchome_growth_opportunities_use_plain_language_and_pause_shopee_coupang():
+    from services.pchome_revenue_growth_service import build_pchome_growth_opportunities
+
+    engine = create_engine("sqlite:///:memory:")
+    _seed_growth_tables(engine)
+
+    payload = build_pchome_growth_opportunities(engine, limit=5)
+
+    assert payload["success"] is True
+    assert payload["system_name"] == "PChome 業績成長自動化作戰系統"
+    assert payload["source_scope"]["active_external_sources"] == ["MOMO 外部價格參考"]
+    assert payload["source_scope"]["paused_external_sources"] == ["蝦皮", "酷澎"]
+    assert payload["stats"]["candidate_count"] == 2
+    assert payload["stats"]["mapped_count"] == 1
+    assert payload["stats"]["needs_mapping_count"] == 1
+
+    actions = {item["pchome_product_id"]: item["recommended_action"]["label"] for item in payload["opportunities"]}
+    assert actions["PCH-1"] == "檢查售價與活動"
+    assert actions["PCH-2"] == "先補商品對應"
+    assert all("identity" not in " ".join(item["reason_lines"]).lower() for item in payload["opportunities"])
+
+
+def test_ai_product_pick_sales_join_by_sku_disabled_by_default(monkeypatch):
+    from services.ai_product_pick_agent import _sales_join_by_momo_sku_enabled
+
+    monkeypatch.delenv("PCHOME_SALES_JOIN_BY_MOMO_SKU_ENABLED", raising=False)
+
+    assert _sales_join_by_momo_sku_enabled() is False
+
+
+def test_ai_intelligence_template_uses_pchome_growth_name_and_endpoint():
+    from pathlib import Path
+
+    template = Path("templates/ai_intelligence.html").read_text(encoding="utf-8")
+
+    assert "PChome 業績成長自動化作戰系統" in template
+    assert "/api/ai/pchome-growth/opportunities" in template
+    assert "待補對應" in template