fix(reassess): stale_detector timeout 60->240s + batch cap 5/run + GATE_ZONE_SANITY

Three issues from zhiwei's strategy report:

1. '37 reassess all timed out (subprocess 60s)': real cause is per-call LLM
   latency exceeding the 60s per-subprocess limit during the key5-dead/
   gateway-unstable window. NOT 'no concurrency control' as reported (60s
   is per stock, not for the batch). Fixes: per-call timeout 60->240s
   (LLM cold-start is 20-100s), and cap AUTO_REASSESS batch to 5 stocks
   per run with remainder continuing next run (was unbounded serial calls
   that also blew the 120s cron script window).

2. '15 stocks entry-zone center wrongly 97.0': quality gates had no
   zone-sanity-vs-price check, so bad data (bad quote or LLM template
   output) could be written freely. New GATE_ZONE_SANITY (CRITICAL):
   zone center must be within 0.3x-3x of current price. Verified: rejects
   the exact 97-center-vs-5.69-price corruption, passes legit zones.

3. 'reassess overwrites manual SQL fixes': true by design; with
   GATE_ZONE_SANITY at write time, reassess can no longer overwrite good
   values with garbage - invalid writes get rejected + flagged instead.

deploy/profile-scripts/stale_detector.py

@@ -142,7 +142,7 @@ def main():
                 reassess_scripts.append(code)
                 print(f"[AUTO_REASSESS] {name}({code}) 价{cur_price:.2f}偏离买入区中心{center:.2f} {drift:+.0f}% → 触发重评")
         if reassess_scripts:
-            # 调用 per_stock_reassess
+            # 调用 per_stock_reassess（每轮最多5只，防LLM慢导致整批超时；其余下轮继续）
             reassess_path = None
             for p in ['/home/hmo/MoFin/scripts/per_stock_reassess.py',
                       '/home/hmo/.hermes/profiles/position-analyst/scripts/per_stock_reassess.py']:
@@ -150,12 +150,20 @@ def main():
                     reassess_path = p
                     break
             if reassess_path:
-                for code in reassess_scripts:
-                    r = subprocess.run(['python3', reassess_path, code],
-                                     capture_output=True, text=True, timeout=60)
-                    out = r.stdout.strip()[:200] if r.stdout else ""
-                    err = r.stderr.strip()[:200] if r.stderr else ""
-                    print(f"  → {code}: exited={r.returncode} {out}")
+                MAX_PER_RUN = 5
+                batch = reassess_scripts[:MAX_PER_RUN]
+                if len(reassess_scripts) > MAX_PER_RUN:
+                    print(f"[AUTO_REASSESS] 本轮限{MAX_PER_RUN}只，剩余{len(reassess_scripts)-MAX_PER_RUN}只下轮继续")
+                for code in batch:
+                    try:
+                        # LLM 重评冷启动 20-100s，60s 必死（37只全灭那次的根因）→ 240s
+                        r = subprocess.run(['python3', reassess_path, code],
+                                         capture_output=True, text=True, timeout=240)
+                        out = r.stdout.strip()[:200] if r.stdout else ""
+                        err = r.stderr.strip()[:200] if r.stderr else ""
+                        print(f"  → {code}: exited={r.returncode} {out}")
+                    except subprocess.TimeoutExpired:
+                        print(f"  → {code}: 超时240s（LLM仍慢），下轮重试")
     except Exception as e:
         print(f"[AUTO_REASSESS FAIL] {e}")
     # ----- 结束 自选股重评 -----

scripts/check_97_bug.py

@@ -0,0 +1,37 @@
+import sqlite3
+conn = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
+conn.row_factory = sqlite3.Row
+
+# 1. 找曾被 zhiwei 修过的 15 只（她提到的几只）当前值
+codes = ['000711', '603766', '600617', '688271']
+print('=== holding_strategies 当前值（她修过的几只）===')
+for code in codes:
+    r = conn.execute(
+        "SELECT code, name, entry_low, entry_high, stop_loss, take_profit, strategy_type, "
+        "quality_check, created_at, updated_at FROM holding_strategies WHERE code=? AND status='active'",
+        (code,)).fetchone()
+    if r:
+        c = (r['entry_low'] + r['entry_high']) / 2 if r['entry_low'] and r['entry_high'] else 0
+        print(f"  {r['code']} {r['name']}: 区{r['entry_low']}~{r['entry_high']} 中心{c:.2f} | type={r['strategy_type']} | created={r['created_at']} updated={r['updated_at']}")
+
+# 2. 找 candidates 里这些股票的评分/买入区（看是不是 promote 写进来的）
+print()
+print('=== candidates 对应记录 ===')
+for code in codes:
+    r = conn.execute(
+        "SELECT code, name, score, entry_low, entry_high, stop_loss, take_profit, promoted, created_at "
+        "FROM candidates WHERE code=?", (code,)).fetchone()
+    if r:
+        print(f"  {r['code']} {r['name']}: score={r['score']} 区{r['entry_low']}~{r['entry_high']} promoted={r['promoted']} created={r['created_at']}")
+
+# 3. 还有谁可能是 97 中心：找 entry 中心在 90~105 的活跃自选
+print()
+print('=== 当前活跃自选里中心 90~105 的（可能还有漏网的）===')
+rows = conn.execute(
+    "SELECT code, name, entry_low, entry_high FROM holding_strategies "
+    "WHERE status='active' AND decision_type='自选策略' AND entry_low > 0").fetchall()
+for r in rows:
+    c = (r['entry_low'] + r['entry_high']) / 2
+    if 90 <= c <= 105:
+        print(f"  {r['code']} {r['name']}: 区{r['entry_low']}~{r['entry_high']} 中心{c:.2f}")
+conn.close()

scripts/check_candidates_schema.py

@@ -0,0 +1,20 @@
+import sqlite3
+conn = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
+conn.row_factory = sqlite3.Row
+
+# candidates 表结构
+cols = [r[1] for r in conn.execute("PRAGMA table_info(candidates)")]
+print('candidates cols:', cols)
+print()
+
+codes = ['000711', '603766', '600617', '688271']
+print('=== candidates 对应记录 ===')
+for code in codes:
+    r = conn.execute("SELECT * FROM candidates WHERE code=?", (code,)).fetchone()
+    if r:
+        d = dict(r)
+        keys = [k for k in d.keys() if any(s in k.lower() for s in ['score', 'entry', 'stop', 'take', 'promot', 'created', 'name', 'code'])]
+        print(f"  {code}: " + ' | '.join(f'{k}={d[k]}' for k in keys))
+    else:
+        print(f'  {code}: 无记录')
+conn.close()

scripts/find_97_rows.py

@@ -0,0 +1,24 @@
+import sqlite3
+conn = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
+conn.row_factory = sqlite3.Row
+
+print('=== 中心 85~110 的活跃自选/持仓 ===')
+rows = conn.execute(
+    "SELECT code, name, entry_low, entry_high, decision_type, strategy_type, created_at, updated_at "
+    "FROM holding_strategies WHERE status='active' AND entry_low > 0").fetchall()
+found = 0
+for r in rows:
+    c = (r['entry_low'] + r['entry_high']) / 2
+    if 85 <= c <= 110:
+        print(f"  {r['code']} {r['name']}: 区{r['entry_low']}~{r['entry_high']} 中心{c:.2f} | {r['decision_type']}/{r['strategy_type']} | created={r['created_at']} updated={r['updated_at']}")
+        found += 1
+print(f'共 {found} 只')
+print()
+
+# holding_strategies 表结构 + 默认值
+print('=== holding_strategies schema ===')
+sql = conn.execute("SELECT sql FROM sqlite_master WHERE name='holding_strategies'").fetchone()[0]
+for line in sql.split('\n'):
+    if '97' in line or 'DEFAULT' in line.upper():
+        print(' ', line.strip())
+conn.close()

scripts/test_zone_gate.py

@@ -0,0 +1,22 @@
+import sys
+sys.path.insert(0, '/home/hmo/.hermes/profiles/position-analyst/scripts')
+sys.path.insert(0, '/home/hmo/MoFin')
+from strategy_lifecycle import validate_strategy
+
+# 模拟 97 中心坏数据（5元股票被写成中心97）
+bad = {'code': '000711', 'price': 5.69, 'entry_low': 94.0, 'entry_high': 100.0,
+       'stop_loss': 90.0, 'take_profit': 110.0, 'timing_signal': '买入',
+       'rr_ratio': 2.0, 'tech_snapshot': '强撑94 弱撑95 弱压99 强压100',
+       'sector_context': '环保', 'signal_factors': ['x'], 'currency': 'CNY'}
+passed, failures = validate_strategy(bad)
+print('坏数据(中心97 vs 价5.69): passed =', passed)
+for f in failures:
+    print('  FAIL:', f.get('id'), '-', f.get('desc', '')[:60])
+
+# 正常数据
+good = dict(bad)
+good['entry_low'], good['entry_high'], good['stop_loss'], good['take_profit'] = 5.23, 6.15, 5.0, 7.0
+passed2, failures2 = validate_strategy(good)
+print('好数据(区5.23~6.15): passed =', passed2)
+for f in failures2:
+    print('  FAIL:', f.get('id'), '-', f.get('desc', '')[:60])

scripts/trace_97_source.py

@@ -0,0 +1,19 @@
+import sqlite3
+conn = sqlite3.connect('/home/hmo/MoFin/data/mofin.db')
+conn.row_factory = sqlite3.Row
+
+codes = ['000711', '603766', '600617', '688271', '688608']
+for code in codes:
+    r = conn.execute(
+        "SELECT code, name, entry_low, entry_high, substr(full_analysis,1,1200) as fa, "
+        "reassessed_at, updated_at FROM holding_strategies WHERE code=? AND status='active'",
+        (code,)).fetchone()
+    if r:
+        print(f"=== {r['code']} {r['name']} 区{r['entry_low']}~{r['entry_high']} updated={r['updated_at']} reassessed={r['reassessed_at']}")
+        fa = r['fa'] or ''
+        # 找买入区间相关行
+        for line in fa.split('\n'):
+            if any(k in line for k in ['买入区间', '止损', '止盈', '综合结论']):
+                print('   ', line[:120])
+        print()
+conn.close()

strategy_lifecycle.py

@@ -90,6 +90,14 @@ STRATEGY_QUALITY_GATES = [
         "severity": "HIGH",
         "fix": "设置 d['currency']='HKD'"
     },
+    {
+        "id": "GATE_ZONE_SANITY",
+        "desc": "买入区中心不得偏离现价超过3倍（防坏行情/LLM幻觉注入异常值，如15只股被统一写成97的教训）",
+        "check": lambda d: (lambda p, c: p <= 0 or c <= 0 or (p >= c * 0.3 and p <= c * 3.0))(
+            d.get("price") or 0, ((d.get("entry_low") or 0) + (d.get("entry_high") or 0)) / 2),
+        "severity": "CRITICAL",
+        "fix": "买入区与现价偏离超3倍，疑似坏数据。用 technical_analysis 重算支撑阻力或人工修正"
+    },
     # --- 第4条 CRITICAL 红线：9维交叉验证 (2026-07-02 Dad要求) ---
     # 策略不能只有价格数字，必须有证据经过了多维分析:
     # 横切面: 大盘+行业+个股 | 纵切面: 基本面+消息面+技术面+资金流