build: 内网环境下跳过 Windows node-pty 补丁构建并关闭 GitHub 发布

调整 electron-builder 配置，Windows 平台仅打包 zip 格式，注释掉 NSIS 和 portable 目标；
注释掉 Windows Hello helper 资源配置以避免路径不存在导致的打包失败；
将发布配置设为 null 以关闭 GitHub 发布请求；
修改 afterPack 脚本，跳过 Windows 下 node-pty ConPTY 补丁的重建和复制，因内网无 MSVC 工具链无法完成该操作。

electron/bridges/inspection/reportExport.cjs

@@ -94,10 +94,12 @@ function _severityLabel(sev) { return _severityInfo(sev).label; }
 
 /** 健康分数 → 等级文本 */
 function _healthLevelText(score) {
-  if (score >= 85) return "[健康]";
-  if (score >= 70) return "[良好]，存在少量隐患";
-  if (score >= 50) return "[一般]，需重点处置风险";
-  return "[较差]，存在严重故障，需优先处置";
+  if (score >= 90) return "[优秀]";
+  if (score >= 80) return "[健康]";
+  if (score >= 70) return "[良好]";
+  if (score >= 60) return "[一般]";
+  if (score >= 40) return "[较差]";
+  return "[严重]";
 }
 
 function _severityColor(sev) {
@@ -110,42 +112,90 @@ function _severityColor(sev) {
 // ─── 健康评分算法 ────────────────────────────────────
 
 /** 单次巡检快照的健康评分（满分 100，最低 0） */
-function calcSnapshotHealthScore(snap, aiSummary) {
-  let offlineCount = snap.devices.filter(d => !d.ok).length;
-  let critical = 0, warning = 0, info = 0, low = 0;
-  const risks = []; // [{ severity, count }]
+// ─── 健康评分算法（多维度加权） ─────────────────────
+// 满分 100，四维度加权：
+//   Reachability 40%  设备可及性 —— 在线设备占比
+//   Coverage     25%  巡检覆盖率 —— 命令成功率（仅在线设备）
+//   Risk         25%  隐患评级   —— AI hidden_risks 加权，上限 20
+//   Efficiency   10%  执行效率   —— 超时/时长异常
+//
+// 设计思路：
+// - 比例扣分而非线性叠加：设备越多，单台离线扣分越小
+// - 离线设备不参与覆盖率计算（本来就连不上）
+// - Risk 维度有上限，防止 AI 隐患把总分打崩
+// - Efficiency 权重偏低，因耗时不直接反映健康度
 
-  // AI 汇总里的 hidden_risks 按 severity 计数
-  if (aiSummary?.hidden_risks) {
-    for (const r of aiSummary.hidden_risks) {
-      const sev = r.severity || "info";
-      if (sev === "critical") critical++;
-      else if (sev === "warning") warning++;
-      else if (sev === "info") info++;
-      else low++;
-      risks.push({ severity: sev });
-    }
+function calcSnapshotHealthScore(snap, aiSummary) {
+  const devices = snap?.devices || [];
+  const total = devices.length;
+  if (total === 0) {
+    return { score: 0, levelText: _healthLevelText(0), breakdown: "无设备数据" };
   }
 
-  const deduct = offlineCount * 8 + critical * 12 + warning * 6 + info * 3 + low * 1;
-  const score = Math.max(0, 100 - deduct);
-  return {
-    score,
-    levelText: _healthLevelText(score),
-    deduction: {
-      offline: { count: offlineCount, points: offlineCount * 8 },
-      critical: { count: critical, points: critical * 12 },
-      warning:  { count: warning,  points: warning * 6 },
-      info:     { count: info,     points: info * 3 },
-      low:      { count: low,      points: low * 1 },
-    },
-  };
+  // ── 维度 1: 设备可及性（满分 40）─────────────────
+  const online = devices.filter(d => d.ok).length;
+  const offline = total - online;
+  const reachabilityScore = Math.round(40 * (online / total));
+
+  // ── 维度 2: 巡检覆盖率（满分 25）─────────────────
+  let totalCmds = 0, okCmds = 0;
+  for (const d of devices) {
+    if (!d.ok) continue; // 离线跳过
+    const cmds = d.commands || [];
+    for (const c of cmds) {
+      totalCmds++;
+      // command not found / 未识别 是框架 fallback，不算失败
+      if (!c.ok && /command not found|未识别|not recognized/i.test(c.stderr || c.stdout || "")) continue;
+      if (c.ok) okCmds++;
+    }
+  }
+  const coverageRatio = totalCmds === 0 ? 1 : okCmds / totalCmds;
+  const coverageScore = Math.round(25 * coverageRatio);
+
+  // ── 维度 3: 隐患评级（满分 25，上限扣 20）───────
+  const risks = aiSummary?.hidden_risks || [];
+  let riskPenalty = 0, riskCritical = 0, riskWarning = 0, riskInfo = 0;
+  for (const r of risks) {
+    if (!r || !r.severity) continue;
+    const sev = r.severity.toLowerCase();
+    if (sev === "critical") { riskPenalty += 5; riskCritical++; }
+    else if (sev === "warning" || sev === "high") { riskPenalty += 3; riskWarning++; }
+    else { riskPenalty += 1; riskInfo++; }
+  }
+  riskPenalty = Math.min(riskPenalty, 20); // 最多扣到只剩 5 分
+  const riskScore = 25 - riskPenalty;
+
+  // ── 维度 4: 执行效率（满分 10）───────────────────
+  let efficiencyScore = 10;
+  const durationMs = snap?.duration_ms || 0;
+  const avgMsPerDevice = total > 0 ? durationMs / total : 0;
+  if (avgMsPerDevice > 15000) {
+    const penalty = Math.min(6, Math.floor((avgMsPerDevice - 15000) / 10000));
+    efficiencyScore = 10 - penalty;
+  }
+  const timeoutDevices = devices.filter(d =>
+    d.ok && (d.commands || []).some(c => !c.ok && /ETIMEDOUT|timeout/i.test(c.stderr || c.stdout || ""))
+  ).length;
+  if (timeoutDevices > 0) {
+    efficiencyScore = Math.max(4, efficiencyScore - Math.min(3, timeoutDevices));
+  }
+
+  // ── 最终得分（四维度求和）───────────────────────
+  const score = Math.max(0, reachabilityScore + coverageScore + riskScore + efficiencyScore);
+  const breakdown = [
+    `设备可及性: ${reachabilityScore}/40（在线 ${online}/${total}）`,
+    `巡检覆盖率: ${coverageScore}/25（命令成功率 ${(coverageRatio * 100).toFixed(1)}%）`,
+    `隐患评级:   ${riskScore}/25（隐患 ${risks.length} 条: 严重 ${riskCritical}, 警告 ${riskWarning}, 提示 ${riskInfo}）`,
+    `执行效率:   ${efficiencyScore}/10（平均 ${(avgMsPerDevice / 1000).toFixed(1)}s/台${timeoutDevices > 0 ? `, ${timeoutDevices} 台超时` : ""}）`,
+  ].join("\n");
+
+  return { score, levelText: _healthLevelText(score), breakdown };
 }
 
 /** 日报告健康评分（基于每个快照的分数，取算术平均 + max/min） */
 function calcDailyHealthScore(snapScores) {
   if (!snapScores || snapScores.length === 0) {
-    return { score: 0, levelText: "[一般]，无快照数据", max: 0, min: 0 };
+    return { score: 0, levelText: _healthLevelText(0), max: 0, min: 0 };
   }
   const sum = snapScores.reduce((a, b) => a + b, 0);
   const score = Math.round(sum / snapScores.length);