feat: structure main agent result cards

collector-service/app/oneliner_features.py

@@ -2740,6 +2740,115 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None:
             return intent_routes[intent_key]
         return route("goto-production", "production", "回到生产中心", "继续推进当前主 Agent 任务的执行结果。")
 
+    def _build_agent_run_result_sections(
+        row: dict[str, Any],
+        plan: dict[str, Any],
+        recommended_action: dict[str, Any],
+    ) -> dict[str, Any]:
+        source_screen = str(plan.get("source_screen") or row.get("source_screen") or "").strip().lower()
+        recommended_screen = str(recommended_action.get("screen") or "").strip().lower()
+        screen_key = recommended_screen or source_screen
+        intent_key = str(plan.get("intent_key") or row.get("intent_key") or "custom").strip().lower() or "custom"
+        platform = str(plan.get("platform") or row.get("platform") or "").strip()
+        platform_label = legacy.platform_label(platform) if platform else ""
+        plan_summary = str(plan.get("summary") or row.get("summary") or "").strip() or "主 Agent 已按当前上下文完成首轮收口。"
+        goal = str(plan.get("goal") or row.get("title") or "主 Agent 任务").strip() or "主 Agent 任务"
+        override_notice = _parse_json(row.get("active_admin_override_notice_json"), {})
+
+        workstream_map = {
+            "dashboard": ("dashboard", "首页动作"),
+            "discovery": ("discovery", "对标推进"),
+            "tracking": ("tracking", "跟踪推进"),
+            "production": ("production", "生产推进"),
+            "review": ("review", "复盘推进"),
+            "strategy": ("strategy", "策略治理"),
+            "playbook": ("playbook", "Agent 治理"),
+            "agent": ("playbook", "Agent 治理"),
+            "automation": ("automation", "自动流程"),
+            "intake": ("intake", "项目推进"),
+            "projects": ("intake", "项目推进"),
+        }
+        workstream_key, workstream_label = workstream_map.get(screen_key, ("production", "主 Agent 执行结果"))
+
+        if intent_key in {"analyze_account", "analyze_top_videos", "import_homepage"}:
+            workstream_key, workstream_label = "discovery", "对标推进"
+        elif intent_key == "track_account":
+            workstream_key, workstream_label = "tracking", "跟踪推进"
+        elif intent_key in {"ai_video", "real_cut", "live_recorder"}:
+            workstream_key, workstream_label = "production", "生产推进"
+        elif intent_key == "review":
+            workstream_key, workstream_label = "review", "复盘推进"
+        elif intent_key in {"create_assistant"}:
+            workstream_key, workstream_label = "playbook", "Agent 治理"
+        elif intent_key in {"create_project"}:
+            workstream_key, workstream_label = "intake", "项目推进"
+        elif intent_key in {"storage_status", "ops_admin"}:
+            workstream_key, workstream_label = "automation", "自动流程"
+
+        def card(title: str, body: str, *, tone: str = "blue", tags: list[str] | None = None) -> dict[str, Any]:
+            return {
+                "title": title,
+                "body": body,
+                "tone": tone,
+                "tags": [item for item in list(tags or []) if str(item).strip()],
+            }
+
+        cards = [
+            card(
+                "当前焦点",
+                f"围绕「{goal}」先完成一版可执行收口，避免你先在多个页面之间来回切换。",
+                tone="blue",
+                tags=[platform_label or "当前平台", workstream_label],
+            )
+        ]
+
+        focus_body_map = {
+            "discovery": "优先回到找对标，继续看账号、相似关系和高分样本，再决定是否导入或加入跟踪。",
+            "tracking": "优先回到跟踪账号，看最近日报窗口和值得继续跟进的对象，再决定同步或加深跟踪。",
+            "production": "优先回到生产中心，看队列、失败恢复和产物，再决定下一步是推进还是补救。",
+            "review": "优先回到发布与复盘，把最近完成任务沉淀成结构化复盘，再决定是否继续发布。",
+            "strategy": "优先回到我的策略，先看当前生效层和管理员覆盖，再决定是否继续调整用户策略。",
+            "playbook": "优先回到 Agent 工作区，结合当前平台 Agent、模型和技能，继续完善执行能力。",
+            "automation": "优先回到自动流程，先看依赖健康和动作防呆，再决定是否恢复或放行动作。",
+            "intake": "优先回到我的项目，先补项目、账号和导入基础，再决定往哪个工作页继续推进。",
+            "dashboard": "优先回到首页当前推荐动作，把这一轮的重点从概览转成真实执行。",
+        }
+        cards.append(
+            card(
+                workstream_label,
+                focus_body_map.get(workstream_key, plan_summary),
+                tone="green",
+                tags=[recommended_action.get("label") or "回到业务页"],
+            )
+        )
+        cards.append(
+            card(
+                "建议落点",
+                str(recommended_action.get("summary") or plan_summary).strip() or "回到对应业务页面继续推进。",
+                tone="orange" if override_notice.get("title") else "blue",
+                tags=[
+                    recommended_action.get("screen") or "",
+                    "管理员覆盖生效中" if override_notice.get("title") else "",
+                    "全平台" if str(plan.get("platform_scope") or row.get("platform_scope") or "") == "all_platforms" else "单平台",
+                ],
+            )
+        )
+        if override_notice.get("title"):
+            cards.append(
+                card(
+                    "管理员覆盖提醒",
+                    str(override_notice.get("summary") or "当前执行会优先遵循管理员覆盖层。").strip(),
+                    tone="orange",
+                    tags=[str(override_notice.get("title") or "管理员覆盖").strip()],
+                )
+            )
+
+        return {
+            "workstream_key": workstream_key,
+            "workstream_label": workstream_label,
+            "cards": cards,
+        }
+
     def _complete_agent_run_for_read(row: dict[str, Any]) -> dict[str, Any]:
         current_status = str(row.get("run_status") or "")
         run_id = str(row.get("id") or "")
@@ -2783,6 +2892,7 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None:
         summary_text = str(plan.get("summary") or row.get("summary") or "").strip() or "主 Agent 已根据当前计划完成第一版执行收口。"
         execution_summary = f"已完成「{str(plan.get('goal') or row.get('title') or '主 Agent 任务').strip() or '主 Agent 任务'}」的首轮执行建议。"
         recommended_action = _build_agent_run_recommended_action(row, plan)
+        result_sections = _build_agent_run_result_sections(row, plan, recommended_action)
         result_payload = {
             "result_kind": "main_agent_plan",
             "run_id": run_id,
@@ -2794,6 +2904,7 @@ def register_oneliner_routes(app: Any, legacy: Any) -> None:
             "platform": str(plan.get("platform") or row.get("platform") or "").strip(),
             "platform_scope": str(plan.get("platform_scope") or row.get("platform_scope") or "single_platform").strip() or "single_platform",
             "recommended_action": recommended_action,
+            "result_sections": result_sections,
             "active_admin_override_notice": _parse_json(row.get("active_admin_override_notice_json"), {}),
         }
         _log_agent_run_event(

tests/test_main_agent_governance.py

@@ -292,6 +292,9 @@ class MainAgentGovernanceTests(unittest.TestCase):
         self.assertEqual(payload["result"]["result_kind"], "main_agent_plan")
         self.assertEqual(payload["result"]["recommended_action"]["action"], "goto-discovery")
         self.assertEqual(payload["result"]["recommended_action"]["screen"], "discovery")
+        self.assertEqual(payload["result"]["result_sections"]["workstream_key"], "discovery")
+        self.assertGreaterEqual(len(payload["result"]["result_sections"]["cards"]), 2)
+        self.assertEqual(payload["result"]["result_sections"]["cards"][0]["title"], "当前焦点")
         event_types = [item["event_type"] for item in payload["events"]]
         self.assertIn("run.progress", event_types)
         self.assertIn("run.done", event_types)

web/storyforge-web-v4/assets/app.js

@@ -1808,6 +1808,10 @@ function renderOneLinerExecutionPayloadHtml(payload) {
     const landingSummary = String(
       payload.recommended_action?.summary || payload.execution_summary || payload.summary_text || ""
     ).trim();
+    const resultSections = payload.result_sections && typeof payload.result_sections === "object"
+      ? payload.result_sections
+      : {};
+    const resultCards = safeArray(resultSections.cards).slice(0, 4);
     const landingAttrs = buildMainAgentLandingAttrs({
       runId: landingRunId,
       screen: landingScreen,
@@ -1825,6 +1829,29 @@ function renderOneLinerExecutionPayloadHtml(payload) {
           ${payload.recommended_action?.action ? `<span class="tag clickable-tag" data-action="${escapeHtml(payload.recommended_action.action)}" data-main-agent-run-id="${escapeHtml(landingRunId)}" data-main-agent-screen="${escapeHtml(landingScreen)}" data-main-agent-title="${escapeHtml(landingTitle)}" data-main-agent-summary="${escapeHtml(landingSummary)}" ${landingAttrs}>${escapeHtml(payload.recommended_action.label || "回到对应页面")}</span>` : ""}
         </div>
       </div>
+      ${resultCards.length ? `
+        <div class="task-item compact" style="margin-top:12px;">
+          <h4>${escapeHtml(resultSections.workstream_label || "执行结果分组")}</h4>
+          <p>${escapeHtml(payload.summary_text || "主 Agent 已将当前执行结果整理为可继续推进的结构化建议。")}</p>
+          <div class="detail-grid" style="margin-top:12px;">
+            ${resultCards.map((card, index) => {
+              const tags = safeArray(card?.tags).slice(0, 3);
+              const tone = String(card?.tone || "").trim();
+              const toneClass = tone === "orange" ? "orange" : tone === "green" ? "green" : "blue";
+              return `
+                <div class="task-item compact">
+                  <h4>${escapeHtml(card?.title || (index === 0 ? "当前焦点" : "执行结果"))}</h4>
+                  <p>${escapeHtml(card?.body || "主 Agent 已生成一条可继续执行的结果说明。")}</p>
+                  <div class="task-meta">
+                    <span class="tag ${toneClass}">${escapeHtml(card?.title || (index === 0 ? "当前焦点" : "结果卡片"))}</span>
+                    ${tags.map((tag) => `<span class="tag">${escapeHtml(tag)}</span>`).join("")}
+                  </div>
+                </div>
+              `;
+            }).join("")}
+          </div>
+        </div>
+      ` : ""}
       ${payload.recommended_action?.summary ? `
         <div class="task-item compact" style="margin-top:12px;">
           <h4>建议回跳</h4>

web/storyforge-web-v4/tests/workbench-pages.test.mjs

@@ -249,6 +249,9 @@ test("main agent result rendering offers a direct route back into the recommende
   const execution = extractBetween(APP, "function renderOneLinerExecutionPayloadHtml(payload)", "function parseOneLinerActionPayloadValue(value)");
   const lastAction = extractBetween(APP, "function renderLastActionCard()", "function getJobRecoveryCategory(job)");
   assert.match(execution, /recommended_action/);
+  assert.match(execution, /result_sections/);
+  assert.match(execution, /当前焦点/);
+  assert.match(execution, /detail-grid/);
   assert.match(execution, /data-action="\$\{escapeHtml\(payload\.recommended_action\.action\)\}"/);
   assert.match(lastAction, /open-oneliner-run-result/);
   assert.match(lastAction, /recommended_action/);