feat: display no-order M1 shadow suggestions

tests/strategy_switch_worker_validation.mjs

@@ -26,6 +26,8 @@ assert.ok(indexHtml.includes('id="runtime-authority-status"'));
 assert.ok(indexHtml.includes('id="control-plane-view-button"'));
 assert.ok(indexHtml.includes('id="control-plane-view"'));
 assert.ok(indexHtml.includes('id="control-plane-list"'));
+assert.ok(indexHtml.includes('id="adaptive-selection-list"'));
+assert.ok(indexHtml.includes('id="adaptive-selection-notice"'));
 assert.ok(indexHtml.includes('data-i18n="planEyebrow"'));
 assert.ok(indexHtml.includes('id="plan-check-authority"'));
 assert.ok(indexHtml.includes('class="control-disclosure"'));
@@ -40,6 +42,7 @@ assert.ok(indexHtml.includes('window.__QSL_RUNTIME_AUTHORITY_STATUS__'));
 assert.ok(indexHtml.includes('execution_metadata_is_runtime_authority'));
 assert.ok(indexHtml.includes('P1–P3 non-live 数据获取仍需独立、精确的契约'));
 assert.ok(indexHtml.includes('requestJson("/api/execution-evidence")'));
+assert.ok(indexHtml.includes('requestJson("/api/adaptive-selection")'));
 assert.equal(indexHtml.includes('missing_current_promotion_evidence_and_human_acceptance'), false);
 assert.ok(indexHtml.includes('missing_current_promotion_evidence_and_preauthorized_autonomy_policy'));
 assert.ok(indexHtml.includes(".switch-surface.summary-hidden"));
@@ -2088,6 +2091,97 @@ assert.deepEqual(sourceControlPayload.summary, { candidate_count: 1, deferred: 0
 assert.deepEqual(sourceControlPayload.attention, { status: "research_only", reason_codes: [] });
 assert.equal(sourceControlPayload.candidates[0].candidate_id, "tqqq_core_only_p2_v5");
 
+const adaptiveSelectionSyncValue = ["adaptive", "selection", "sync"].join("-");
+const adaptiveSelectionEnv = { ...controlEnv, ADAPTIVE_SELECTION_SYNC_TOKEN: adaptiveSelectionSyncValue };
+const adaptiveSelectionCookie = await __test.makeSession("health-user", [], adaptiveSelectionEnv);
+const adaptiveSelectionCookieHeaders = { Cookie: `qsl_switch_session=${adaptiveSelectionCookie}` };
+const adaptiveSelectionSourcePayload = {
+  schema_version: "qsl.adaptive_selection_source_snapshot.v1",
+  source_id: "uesp.us_equity_combo_shadow",
+  generated_at: controlNow,
+  computed_at: controlNow,
+  data_status: "ready",
+  decision: {
+    schema: "qsl.selection_decision.v1",
+    decision_id: "shadow-us-equity-combo-001",
+    created_at: controlNow,
+    authority: "shadow_only",
+    no_order: true,
+    market_context: {
+      schema: "qsl.market_context_snapshot.v1",
+      as_of: "2026-08-28",
+      domain: "us_equity",
+      data_version: "trusted-prices-v1",
+      data_freshness_days: 0,
+      regime: "normal",
+      regime_confidence: 0.9,
+      factors: { momentum: 0.12 },
+    },
+    policy_id: "shadow-policy-v1",
+    recommended_strategy_profile: "us_equity_combo",
+    recommended_platform_id: "longbridge-paper",
+    candidates: [{
+      strategy_profile: "us_equity_combo",
+      release_digest: `sha256:${"a".repeat(64)}`,
+      selected_platform_id: "longbridge-paper",
+      score: 0.42,
+      risk_multiplier: 1,
+      accepted: true,
+      reasons: ["shadow_candidate_ranked"],
+      proposed_weight: 0,
+    }],
+    input_digest: "b".repeat(64),
+  },
+  errors: [],
+};
+
+const unauthorizedAdaptiveSelectionRead = await worker.fetch(
+  new Request("https://switch.example/api/adaptive-selection"),
+  adaptiveSelectionEnv,
+);
+assert.equal(unauthorizedAdaptiveSelectionRead.status, 401);
+const wrongAdaptiveSelectionToken = await worker.fetch(
+  new Request("https://switch.example/api/internal/sync-adaptive-selection-source", {
+    method: "POST",
+    headers: { Authorization: `Bearer ${controlSyncValue}`, "Content-Type": "application/json" },
+    body: JSON.stringify(adaptiveSelectionSourcePayload),
+  }),
+  adaptiveSelectionEnv,
+);
+assert.equal(wrongAdaptiveSelectionToken.status, 401);
+assert.throws(
+  () => __test.normalizeAdaptiveSelectionSourceSnapshot({
+    ...adaptiveSelectionSourcePayload,
+    decision: {
+      ...adaptiveSelectionSourcePayload.decision,
+      candidates: [{ ...adaptiveSelectionSourcePayload.decision.candidates[0], proposed_weight: 0.01 }],
+    },
+  }),
+  /proposed_weight must remain zero/,
+);
+const adaptiveSelectionSync = await worker.fetch(
+  new Request("https://switch.example/api/internal/sync-adaptive-selection-source", {
+    method: "POST",
+    headers: { Authorization: `Bearer ${adaptiveSelectionSyncValue}`, "Content-Type": "application/json" },
+    body: JSON.stringify(adaptiveSelectionSourcePayload),
+  }),
+  adaptiveSelectionEnv,
+);
+assert.equal(adaptiveSelectionSync.status, 200);
+assert.equal((await adaptiveSelectionSync.json()).no_order, true);
+const adaptiveSelectionRead = await worker.fetch(
+  new Request("https://switch.example/api/adaptive-selection", { headers: adaptiveSelectionCookieHeaders }),
+  adaptiveSelectionEnv,
+);
+assert.equal(adaptiveSelectionRead.status, 200);
+const adaptiveSelectionPayload = await adaptiveSelectionRead.json();
+assert.equal(adaptiveSelectionPayload.data_status, "ready");
+assert.deepEqual(adaptiveSelectionPayload.summary, {
+  source_count: 1, decision_count: 1, candidate_count: 1, recommended_count: 1, rejected_candidate_count: 0,
+});
+assert.equal(adaptiveSelectionPayload.policy.no_order, true);
+assert.equal(adaptiveSelectionPayload.selections[0].decision.recommended_strategy_profile, "us_equity_combo");
+
 const ownerDecisionStore = new Map();
 const ownerDecisionKv = {
   async get(key) { return ownerDecisionStore.get(key) || null; },

web/strategy-switch-console/README.zh-CN.md

@@ -199,6 +199,25 @@ GET  /api/control-plane
 
 这个接口不是订单、paper、shadow 或 live API。`CONTROL_PLANE_SYNC_TOKEN` 必须与 OAuth、workflow dispatch、策略 root 和任何券商凭证完全分离。部署 workflow 会在 `runtime-strategy-switch` environment 提供该 secret 时，把它同步为 Worker secret；每个来源仓库需要保存同一值到其专用 GitHub Environment，URL 使用只读控制台的 `/api/internal/sync-control-plane-source`。
 
+## M1 Shadow 建议只读接口
+
+M1 把 P0 已生成的 `qsl.selection_decision.v1` 呈现给人工；它不创建策略、不会开始
+Shadow runtime，也不会修改仓位。每个来源使用单独凭据提交：
+
+```text
+POST /api/internal/sync-adaptive-selection-source
+GET  /api/adaptive-selection
+```
+
+写入的外层契约是 `qsl.adaptive_selection_source_snapshot.v1`，其中的 decision 必须仍是
+`authority=shadow_only`、`no_order=true`，且每个 `proposed_weight=0`。Worker 会拒绝非零
+权重、非 Shadow authority、缺少完整输入摘要或格式不安全的字段。读取接口要求已登录
+allowlist；默认 36 小时后快照标为 `stale`，不会被当作当前结论。
+
+`ADAPTIVE_SELECTION_SYNC_TOKEN` 必须专用，不能复用 OAuth、策略切换、控制面、执行证据、
+顾投、券商或账户凭据。顾投研究与 M1 的卡片也必须保持分开：顾投只能提出研究假设，不能
+直接成为市场因子、策略基础分、插件风险缩放、平台健康、目标权重或订单输入。
+
 ## 网页人工审批（P6 决策意图）
 
 当且仅当候选仍是**新鲜**的 P6 `owner_decision_required`、机器建议仍为 `owner_live_decision` 时，控制台会在“全局概览”显示人工决定区。只有管理员可以选择：批准受限试运行意图、保持暂停或退役候选。

web/strategy-switch-console/app.js

@@ -860,6 +860,17 @@
         executionEvidenceDetail: "策略：{strategy} · 数据：{data} · 执行：{execution} · Shadow：{shadow} · Paper：{paper}",
         executionEvidenceNoOrder: "固定边界：只读证据；不包含账户、订单、资金或 P6 实盘授权。",
         executionEvidenceNext: "下一步",
+        adaptiveSelectionBoard: "按需查看 M1 Shadow 建议",
+        adaptiveSelectionLoginNotice: "登录后读取私有 Shadow 建议；缺失来源不会被补成策略或订单。",
+        adaptiveSelectionStaleNotice: "此 Shadow 建议已超出新鲜度窗口，仅保留为历史上下文。",
+        adaptiveSelectionUnavailableNotice: "还没有可用的 M1 Shadow 建议；页面保持 fail-closed 空状态。",
+        adaptiveSelectionUpstreamNotice: "Shadow 建议带有 {count} 个上游提示；页面不会推断策略、平台或订单。",
+        adaptiveSelectionEmpty: "暂无可展示的 Shadow 建议。",
+        adaptiveSelectionMeta: "{source} · {domain} · 市场截至 {asOf}",
+        adaptiveSelectionRecommended: "建议观察",
+        adaptiveSelectionNoCandidate: "无合格 Shadow 候选",
+        adaptiveSelectionReason: "原因：{reasons}",
+        adaptiveSelectionNoOrder: "固定边界：仅供人工查看，零建议权重，不改策略、平台、资金、运行状态或订单。",
         researchTaskBoard: "按需查看研究任务队列",
         researchTaskLoginNotice: "登录后读取私有研究任务索引；没有来源快照时不会展示虚构任务。",
         researchTaskStaleNotice: "研究任务来源已超过允许的新鲜度窗口；任务保留为历史记录，但不作为当前工作指令。",
@@ -1118,6 +1129,17 @@
         executionEvidenceDetail: "strategy: {strategy} · data: {data} · execution: {execution} · shadow: {shadow} · paper: {paper}",
         executionEvidenceNoOrder: "Fixed boundary: read-only evidence; no account, order, funds, or P6 live authority.",
         executionEvidenceNext: "NEXT",
+        adaptiveSelectionBoard: "View M1 Shadow suggestions on demand",
+        adaptiveSelectionLoginNotice: "Sign in to read private Shadow suggestions. Missing sources never imply a strategy or order.",
+        adaptiveSelectionStaleNotice: "This Shadow suggestion is beyond its freshness window and remains historical context only.",
+        adaptiveSelectionUnavailableNotice: "No usable M1 Shadow suggestion is available yet. This view remains fail-closed and empty.",
+        adaptiveSelectionUpstreamNotice: "Shadow suggestions include {count} upstream notice(s); no strategy, platform, or order is inferred.",
+        adaptiveSelectionEmpty: "No Shadow suggestion is available to display.",
+        adaptiveSelectionMeta: "{source} · {domain} · market as of {asOf}",
+        adaptiveSelectionRecommended: "Observe suggestion",
+        adaptiveSelectionNoCandidate: "No eligible Shadow candidate",
+        adaptiveSelectionReason: "Reasons: {reasons}",
+        adaptiveSelectionNoOrder: "Fixed boundary: human-readable only, zero proposed weight, no strategy, platform, funds, runtime, or order change.",
         researchTaskBoard: "View research queue on demand",
         researchTaskLoginNotice: "Sign in to read the private research task index. Missing source snapshots never imply a task.",
         researchTaskStaleNotice: "The research task source is beyond its freshness window. It remains historical context, not a current instruction.",
@@ -1387,6 +1409,16 @@
         candidates: [],
         errors: [],
       },
+      adaptiveSelection: {
+        payload: {
+          data_status: "unavailable",
+          computed_at: null,
+          summary: { source_count: 0, decision_count: 0, candidate_count: 0, recommended_count: 0, rejected_candidate_count: 0 },
+          selections: [],
+          policy: { authority: "shadow_only", no_order: true, execution_authority_granted: false },
+          errors: [],
+        },
+      },
       executionEvidence: {
         payload: {
           data_status: "unavailable",
@@ -3688,6 +3720,89 @@
       }
     }
 
+    function normalizeAdaptiveSelectionPayload(payload) {
+      if (!payload || typeof payload !== "object" || Array.isArray(payload)) throw new Error("invalid adaptive selection payload");
+      const selections = Array.isArray(payload.selections) ? payload.selections : [];
+      return {
+        data_status: ["ready", "stale", "unavailable"].includes(payload.data_status) ? payload.data_status : "unavailable",
+        computed_at: payload.computed_at || null,
+        summary: payload.summary && typeof payload.summary === "object" ? payload.summary : {},
+        selections: selections.filter((item) => item && typeof item === "object"
+          && typeof item.source_id === "string" && item.decision && typeof item.decision === "object"),
+        policy: payload.policy && typeof payload.policy === "object" ? payload.policy : {},
+        errors: Array.isArray(payload.errors) ? payload.errors : [],
+      };
+    }
+
+    function renderAdaptiveSelection() {
+      const payload = state.adaptiveSelection.payload;
+      const notice = el("adaptive-selection-notice");
+      if (!state.auth.allowed) {
+        notice.textContent = t("adaptiveSelectionLoginNotice");
+      } else if (payload.data_status === "stale") {
+        notice.textContent = t("adaptiveSelectionStaleNotice");
+      } else if (payload.data_status !== "ready") {
+        notice.textContent = t("adaptiveSelectionUnavailableNotice");
+      } else if (payload.errors?.length) {
+        notice.textContent = t("adaptiveSelectionUpstreamNotice").replace("{count}", String(payload.errors.length));
+      } else {
+        notice.textContent = payload.policy?.notice || t("adaptiveSelectionNoOrder");
+      }
+
+      const list = el("adaptive-selection-list");
+      list.replaceChildren();
+      if (!payload.selections.length) {
+        const empty = document.createElement("div");
+        empty.className = "health-card__empty";
+        empty.textContent = t("adaptiveSelectionEmpty");
+        list.appendChild(empty);
+        return;
+      }
+      for (const entry of payload.selections) {
+        const decision = entry.decision || {};
+        const context = decision.market_context || {};
+        const recommended = decision.candidates?.find((item) => item.accepted
+          && item.strategy_profile === decision.recommended_strategy_profile) || null;
+        const rejected = (decision.candidates || []).filter((item) => !item.accepted);
+        const reasons = (recommended?.reasons?.length ? recommended.reasons : rejected.flatMap((item) => item.reasons || []))
+          .slice(0, 3)
+          .join(", ");
+
+        const card = document.createElement("article");
+        card.className = "health-card";
+        const main = document.createElement("div");
+        main.className = "health-card__main";
+        const meta = document.createElement("div");
+        meta.className = "health-card__meta";
+        meta.textContent = t("adaptiveSelectionMeta")
+          .replace("{source}", entry.source_id || "unknown")
+          .replace("{domain}", domainLabel(context.domain || ""))
+          .replace("{asOf}", context.as_of || "—");
+        const title = document.createElement("h4");
+        title.className = "health-card__title";
+        title.textContent = recommended
+          ? `${t("adaptiveSelectionRecommended")} · ${recommended.strategy_profile}`
+          : t("adaptiveSelectionNoCandidate");
+        const reason = document.createElement("p");
+        reason.className = "health-card__reason";
+        reason.textContent = reasons
+          ? t("adaptiveSelectionReason").replace("{reasons}", reasons)
+          : t("adaptiveSelectionNoOrder");
+        main.append(meta, title, reason);
+        const status = document.createElement("div");
+        status.className = "health-card__score";
+        const label = document.createElement("small");
+        label.textContent = "NO ORDER";
+        const score = document.createElement("strong");
+        score.textContent = typeof recommended?.score === "number" ? recommended.score.toFixed(3) : "—";
+        const freshness = document.createElement("small");
+        freshness.textContent = entry.freshness?.data_status || "unknown";
+        status.append(label, score, freshness);
+        card.append(main, status);
+        list.appendChild(card);
+      }
+    }
+
     function normalizeExecutionEvidencePayload(payload) {
       if (!payload || typeof payload !== "object" || Array.isArray(payload)) throw new Error("invalid execution evidence payload");
       const deployments = Array.isArray(payload.deployments) ? payload.deployments : [];
@@ -3959,6 +4074,7 @@
       renderRuntimeAuthorityStatus();
       renderConsoleView();
       renderControlPlane();
+      renderAdaptiveSelection();
       renderExecutionEvidence();
       renderResearchTasks();
       renderHealth();
@@ -3987,6 +4103,7 @@
       if (state.auth.allowed) {
         await refreshControlPlane();
         await refreshOwnerDecisions();
+        await refreshAdaptiveSelection();
         await refreshExecutionEvidence();
         await refreshResearchTasks();
         await refreshHealth();
@@ -4056,6 +4173,26 @@
       renderControlPlane();
     }
 
+    async function refreshAdaptiveSelection() {
+      if (!state.auth.allowed) {
+        renderAdaptiveSelection();
+        return;
+      }
+      try {
+        state.adaptiveSelection.payload = normalizeAdaptiveSelectionPayload(await requestJson("/api/adaptive-selection"));
+      } catch {
+        state.adaptiveSelection.payload = {
+          data_status: "unavailable",
+          computed_at: null,
+          summary: { source_count: 0, decision_count: 0, candidate_count: 0, recommended_count: 0, rejected_candidate_count: 0 },
+          selections: [],
+          policy: { authority: "shadow_only", no_order: true, execution_authority_granted: false },
+          errors: ["adaptive_selection_request_failed"],
+        };
+      }
+      renderAdaptiveSelection();
+    }
+
     async function recordOwnerDecision(button) {
       if (!state.auth.admin) return;
       const candidateId = String(button.dataset.candidateId || "");

web/strategy-switch-console/index.html

@@ -78,6 +78,11 @@ <h2 id="control-plane-view-title" data-i18n="controlPlaneTitle">只处理需要
       </div>
       <div class="health-board-head"><h3 data-i18n="controlCandidateBoard">需要跟进</h3></div>
       <div class="health-list" id="control-plane-list"></div>
+      <details class="control-disclosure">
+        <summary data-i18n="adaptiveSelectionBoard">按需查看 M1 Shadow 建议</summary>
+        <div id="adaptive-selection-notice" class="health-notice" role="status" aria-live="polite">登录后读取已验证的 Shadow 建议；它始终不下单。</div>
+        <div class="health-list" id="adaptive-selection-list"></div>
+      </details>
       <details class="control-disclosure">
         <summary data-i18n="executionEvidenceBoard">按需查看策略 × 平台证据覆盖</summary>
         <div id="execution-evidence-notice" class="health-notice" role="status" aria-live="polite">登录后读取已验证执行证据；页面不会推断 paper 或 live 状态。</div>