feat(coordinator): 添加团队节点默认最大工具迭代次数配置

添加 DEFAULT_TEAM_NODE_MAX_TOOL_ITERATIONS 配置项以控制团队节点的最大工具迭代次数，
并修改 LocalAgentRunner 中的逻辑来使用此默认值当 envelope 中未指定时。

fix(runtime): 修复团队节点运行成功判断逻辑

更新运行成功判断条件，将 finish_reason 为 "max_tool_iterations_finalized" 的情况
视为运行失败，并添加对原始工具调用输出的检测，避免将其误判为成功完成。

feat(mcp): 添加团队工作流MCP工具类别支持

增加新的本地MCP工具类别 "team_workflow" 及其对应的工具创建功能，
为团队工作流提供本地工具支持。

refactor(engine): 调整AgentLoop最大工具迭代次数设置

将 AgentProfile 中的默认 max_tool_iterations 从 30 增加到 100，
同时移除 TaskExecutionPlanner 构造函数中的重复参数传递。

perf(mcp): 优化MCP连接管理避免重复连接

添加 mcp_connected 标志来跟踪MCP连接状态，确保 connect_all 只执行一次，
提高性能并避免不必要的重复连接。

refactor(skills): 移除技能团队模板相关功能

移除与技能团队模板相关的代码，包括解析、存储和处理逻辑，
简化技能记录结构和加载流程。

feat(process): 增强会话过程投影器功能

添加技能激活快照事件处理，改进团队运行完成消息显示，
并增强技能激活事件的时间戳记录功能。

refactor(tasks): 简化任务尝试编排器团队执行逻辑

移除团队执行相关代码，将所有任务统一按单步执行处理，
简化任务编排器的复杂度并提升执行效率。

fix(evidence): 修复节点证据评估中需求验证逻辑

更新节点证据评估逻辑，跳过自然语言证据需求的确定性验证，
只执行机器可读的需求验证，避免因自然语言需求导致的节点失败。

docs/superpowers/examples/install_mgm_skill_metadata.py

@@ -0,0 +1,85 @@
+from __future__ import annotations
+
+import hashlib
+import json
+from datetime import datetime, timezone
+from pathlib import Path
+
+
+def main() -> None:
+    skill_name = "mgm-galaxy-financial-chart-report-safe"
+    workspace = Path("/root/.beaver/workspace")
+    skill_dir = workspace / "skills" / skill_name
+    skill_md = skill_dir / "versions" / "v0001" / "SKILL.md"
+    content = skill_md.read_text(encoding="utf-8")
+    digest = "sha256:" + hashlib.sha256(content.encode("utf-8")).hexdigest()
+    now = datetime.now(timezone.utc).isoformat()
+
+    (skill_dir / "current.json").write_text(
+        json.dumps({"current_version": "v0001"}, indent=2, ensure_ascii=False) + "\n",
+        encoding="utf-8",
+    )
+    (skill_dir / "skill.json").write_text(
+        json.dumps(
+            {
+                "name": skill_name,
+                "display_name": "MGM/Galaxy Financial Chart Report Safe",
+                "description": "Compare MGM China and Galaxy Entertainment using official financial sources, produce chart-ready Markdown, and avoid claiming generated chart image/file artifacts.",
+                "created_at": now,
+                "updated_at": now,
+                "current_version": "v0001",
+                "status": "active",
+                "tags": ["finance", "research", "report", "chart-ready-data", "mgm", "galaxy"],
+                "owners": ["steven"],
+                "source_kind": "workspace",
+                "lineage": [],
+            },
+            indent=2,
+            ensure_ascii=False,
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+    (skill_dir / "versions" / "v0001" / "version.json").write_text(
+        json.dumps(
+            {
+                "skill_name": skill_name,
+                "version": "v0001",
+                "content_hash": digest,
+                "summary_hash": digest,
+                "created_at": now,
+                "created_by": "steven",
+                "change_reason": "Add real Skill Team Template example for MGM/Galaxy finance report demo",
+                "parent_version": None,
+                "review_state": "published",
+                "frontmatter": {
+                    "name": skill_name,
+                    "description": "Compare MGM China and Galaxy Entertainment using official financial sources, produce chart-ready Markdown, and avoid claiming generated chart image/file artifacts.",
+                    "tools": ["web_search", "web_fetch"],
+                },
+                "summary": "MGM/Galaxy finance report skill with a task-only Beaver team template for official source collection, metric extraction, validation, and Markdown chart-ready reporting.",
+                "tool_hints": ["web_search", "web_fetch"],
+                "provenance": {"source_kind": "manual_demo", "target_instance": "steven"},
+                "tree_hash": "",
+            },
+            indent=2,
+            ensure_ascii=False,
+        )
+        + "\n",
+        encoding="utf-8",
+    )
+
+    index_path = workspace / "skills" / "_index" / "published.json"
+    try:
+        payload = json.loads(index_path.read_text(encoding="utf-8"))
+    except FileNotFoundError:
+        payload = {"items": []}
+    items = [str(item) for item in payload.get("items", [])]
+    if skill_name not in items:
+        items.append(skill_name)
+    index_path.write_text(json.dumps({"items": items}, indent=2, ensure_ascii=False) + "\n", encoding="utf-8")
+    print(f"installed metadata for {skill_name}: {digest}")
+
+
+if __name__ == "__main__":
+    main()