diff --git a/pipeline_service/agent_loop.py b/pipeline_service/agent_loop.py
index 82d3456..682b96d 100644
--- a/pipeline_service/agent_loop.py
+++ b/pipeline_service/agent_loop.py
@@ -172,6 +172,7 @@ AGENT_TOOLS = [
     {"name":"git_status","description":"查看git仓库状态","params":{"repo_dir":"仓库子目录(可选,默认repos下第一个)"}},
     {"name":"git_commit_push","description":"git add + commit + push","params":{"message":"提交信息","repo_dir":"仓库子目录(可选)"}},
     {"name":"ask_question","description":"向用户提问（缺少信息时使用）","params":{"question":"问题"}},
+    {"name":"deliver","description":"提交最终交付件（代码文件已用write_file写好、git已提交时调用）","params":{"deliverable_type":"交付件类型(如code_files/design_doc)","summary":"概述","result":"交付件正文","files":"JSON数组[{\"path\":\"repos/仓库/src/x.py\",\"content\":\"代码内容\"}](可选)","git_commit_message":"git提交信息(可选)"}},
 ]
 
 AGENT_SYSTEM_PROMPT = """你是软件开发产线中的「__ROLE__」角色Agent。
@@ -510,6 +511,28 @@ def _resolve_repo_target(workspace_dir, repo_dir):
     return workspace_dir
 
 
+def _agent_tools_to_openai_schema(agent_tools):
+    """把 v1 AGENT_TOOLS（{name,description,params}）转成 OpenAI function-calling schema。"""
+    return [
+        {
+            "type": "function",
+            "function": {
+                "name": t["name"],
+                "description": t["description"],
+                "parameters": {
+                    "type": "object",
+                    "properties": {
+                        k: {"type": "string", "description": v}
+                        for k, v in (t.get("params") or {}).items()
+                    },
+                    "required": list((t.get("params") or {}).keys()),
+                },
+            },
+        }
+        for t in agent_tools
+    ]
+
+
 async def _exec_agent_tool(tool, params, workspace_dir):
     p = params or {}
     try:
@@ -619,22 +642,51 @@ async def role_agent_run(project_id, role, agent_id=None, model_name=None):
         msgs = [{"role": "system", "content": system}]
         msgs.append({"role": "user", "content": f"执行任务：{title}\n参数：{params_str}"})
 
-        from .llm_bridge import llm_call_msgs
+        from .llm_bridge import llm_call_msgs, llm_call_msgs_native
+        tools_schema = _agent_tools_to_openai_schema(AGENT_TOOLS)
 
         deliverable = None
         ask_question = None
 
-        # ── Tool Loop ──
+        # ── Tool Loop（原生 function calling）──
         for turn in range(15):
             try:
-                raw = await llm_call_msgs(msgs, model=model_name, temperature=0.4)
+                resp = await llm_call_msgs_native(msgs, tools=tools_schema, model=model_name, temperature=0.4)
             except Exception as e:
                 await sor.sqlExe("UPDATE pipeline_tasks SET state='failed' WHERE id=${tid}$", {"tid": task_id})
                 logger.error(f"role_agent_run llm failed: task={task_id} err={e}")
                 return {"status": "failed", "task_id": task_id, "error": str(e)[:200]}
 
-            act = _parse_agent_action(raw)
+            native_calls = (resp.get("tool_calls") or []) if isinstance(resp, dict) else []
 
+            if native_calls:
+                # 回填 assistant（含 tool_calls，OpenAI 原生格式）
+                msgs.append({"role": "assistant", "content": resp.get("content") or None, "tool_calls": native_calls})
+                for tc in native_calls:
+                    fn = tc.get("function", {}) if isinstance(tc, dict) else {}
+                    tool = fn.get("name", "")
+                    try:
+                        params = json.loads(fn.get("arguments") or "{}")
+                    except Exception:
+                        params = {}
+
+                    if tool == "deliver":
+                        deliverable = {"action": "deliver", **params}
+                        break
+                    if tool == "ask_question":
+                        ask_question = params.get("question", "")
+                        break
+
+                    result = await _exec_agent_tool(tool, params, workspace_dir)
+                    msgs.append({"role": "tool", "tool_call_id": tc.get("id", ""), "content": str(result)})
+                    logger.info(f"role_agent tool_call: {tool} -> {str(result)[:100]}")
+                if deliverable or ask_question:
+                    break
+                continue
+
+            # 无 tool_calls → 文本兜底（deliver/ask 的 JSON）
+            raw = resp.get("content", "") if isinstance(resp, dict) else str(resp)
+            act = _parse_agent_action(raw)
             if act.get('action') == 'deliver':
                 deliverable = act
                 break
@@ -647,7 +699,7 @@ async def role_agent_run(project_id, role, agent_id=None, model_name=None):
                 result = await _exec_agent_tool(tool, params, workspace_dir)
                 msgs.append({"role": "assistant", "content": raw})
                 msgs.append({"role": "user", "content": f"工具 {tool} 结果：\n{result}"})
-                logger.info(f"role_agent tool_call: {tool} -> {result[:100]}")
+                logger.info(f"role_agent tool_call(text): {tool} -> {str(result)[:100]}")
             else:
                 deliverable = {"result": raw}
                 break
@@ -671,6 +723,11 @@ async def role_agent_run(project_id, role, agent_id=None, model_name=None):
         # 写入代码文件
         files_written = []
         code_files = deliverable.get("files") or []
+        if isinstance(code_files, str):
+            try:
+                code_files = json.loads(code_files)
+            except Exception:
+                code_files = []
         if isinstance(code_files, list):
             for f in code_files:
                 if isinstance(f, dict) and f.get("path") and f.get("content"):