feat: 修复了一些bug

* feat: Make skill individuals directly accessible to consciousness node

- Added `available_skills` to `ConsciousnessNodeDeps` and `ForWorkflowEngineInput`.
- Updated `WorkflowRunningEngine` to retrieve all available skills from `GlobalStateMachine` and pass them during `ForWorkflowEngineInput` creation.
- Updated `ConsciousnessNode` to dynamically inject these skills into the system prompt. This allows the AI to correctly insert `skill_individuals` into `PretorWorkflow` steps (as tools for `composite_individual` or `primary_individual`).

Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

* feat: Expose skill individuals to consciousness node & fix frontend tool parsing

- Added `available_skills` to `ConsciousnessNodeDeps` and `ForWorkflowEngineInput`.
- Updated `WorkflowRunningEngine` to retrieve all available skills from `GlobalStateMachine` and pass them into `ForWorkflowEngineInput`.
- Updated `ConsciousnessNode` to dynamically inject these skills into the prompt, enabling AI to integrate `skill_individuals` into `PretorWorkflow` steps directly.
- Fixed a frontend parsing bug in `WorkerIndividualSettings.tsx` where backend tool responses (an array of strings) were being incorrectly flattened, resulting in arrays of index numbers instead of actual tool names.

Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

---------

Co-authored-by: google-labs-jules[bot] <161369871+google-labs-jules[bot]@users.noreply.github.com>
Co-authored-by: zhaoxi826 <198742034+zhaoxi826@users.noreply.github.com>

frontend/src/components/Agent/WorkerIndividualSettings.tsx

@@ -45,7 +45,7 @@ export function WorkerIndividualSettings() {
       setProviders(Object.values(provRes.data.provider_list || {}));
       setWorkers(workRes.data.workers || []);
 
-      const allTools = toolsRes.data.tools ? Object.values(toolsRes.data.tools).flatMap(tGroup => Object.keys(tGroup as any)) : [];
+      const allTools = toolsRes.data.tools || [];
       setAvailableTools(allTools);
       setAvailableSkills(Object.keys(skillsRes.data.skills || {}));
 

pretor/core/individual/consciousness_node/consciousness_node.py

@@ -78,6 +78,11 @@ class ConsciousnessNode:
             )
             if ctx.deps.workflow_template:
                 prompt += f"- 选定工作流模板 (Workflow Template): {ctx.deps.workflow_template}\n"
+            if ctx.deps.available_skills:
+                prompt += "\n=== 当前可用 Skill Individual ===\n"
+                prompt += "你可以直接将以下 Skill Individual 安排进工作流的步骤中（设置 node 为 composite_individual 或 primary_individual，并将 agent_id 设置为对应的 Skill Individual 名称），作为可调用的工具。\n"
+                for skill in ctx.deps.available_skills:
+                    prompt += f"- 名称: {skill['name']}\n  描述: {skill['description']}\n"
 
             return prompt
 
@@ -140,7 +145,8 @@ class ConsciousnessNode:
                 deps = ConsciousnessNodeDeps(
                     original_command=payload.original_command,
                     workflow_template=payload.workflow_template,
-                    command="拆解原始命令变成一个工作流"
+                    command="拆解原始命令变成一个工作流",
+                    available_skills=payload.available_skills
                 )
                 self.logger.debug("ConsciousnessNode: 开始生成工作流 (原生重试开启)")
                 result = await self.agent.run(

pretor/core/individual/consciousness_node/template.py

@@ -44,6 +44,7 @@ class ConsciousnessNodeDeps(DepsModel):
     original_command: str
     workflow_template: str | None = None
     command: str
+    available_skills: list[dict] | None = None
 
 
 class ConsciousnessNodeInput(InputModel):
@@ -53,6 +54,7 @@ class ConsciousnessNodeInput(InputModel):
 class ForWorkflowEngineInput(ConsciousnessNodeInput):
     workflow_template: str
     original_command: str
+    available_skills: list[dict] | None = None
 
 
 class ForWorkflowInput(ConsciousnessNodeInput):

pretor/core/workflow/workflow_runner.py

@@ -300,9 +300,21 @@ class WorkflowRunningEngine:
                 workflow_template = event.context.get("workflow_template", "")
                 workflow_template = get_workflow_template(workflow_template)
 
+                available_skills = None
+                if self.global_state_machine:
+                    try:
+                        raw_skills = await self.global_state_machine.get_skill_list.remote()
+                        available_skills = [
+                            {"name": name, "description": details[0], "instructions": details[1]}
+                            for name, details in raw_skills.items()
+                        ]
+                    except Exception as e:
+                        self.logger.warning(f"获取技能列表失败: {e}")
+
                 payload = ForWorkflowEngineInput(
                     original_command=event.message,
-                    workflow_template=workflow_template
+                    workflow_template=workflow_template,
+                    available_skills=available_skills
                 )
 
                 result_obj = await self.consciousness_node.working.remote(payload)

pretor/worker_individual/worker_cluster.py

@@ -38,12 +38,14 @@ class WorkerCluster:
         self.max_capacity = max_capacity
         self._active_workers: OrderedDict[str, BaseIndividual] = OrderedDict()
         self.status = "running"
-        self.task_queue = Queue()
+        self.task_queue = None
         self.results_futures = {}
         self.runners = []
         self.num_runners = num_runners
 
     async def start(self):
+        if self.task_queue is None:
+            self.task_queue = Queue()
         self.runners = [asyncio.create_task(self._runner(i)) for i in range(self.num_runners)]
         logger.info(f"WorkerCluster 已启动 {self.num_runners} 个 runner 协程。")
 
@@ -77,6 +79,9 @@ class WorkerCluster:
     async def _runner(self, runner_id: int):
         while True:
             try:
+                if self.task_queue is None:
+                    await asyncio.sleep(0.1)
+                    continue
                 task = await self.task_queue.get_async()
                 task_id = task.get("task_id")
                 agent_id = task.get("agent_id")

tests/core/workflow/workflow_runner_test.py

@@ -143,6 +143,11 @@ async def test_workflow_running_engine_runner():
     )
     await engine.workflow_queue.put(mock_event)
 
+    # Mock the global_state_machine get_skill_list.remote method properly
+    mock_gsm = MagicMock()
+    mock_gsm.get_skill_list.remote = AsyncMock(return_value={"test_skill": ("description", "instructions")})
+    engine.global_state_machine = mock_gsm
+
     with patch("pretor.core.workflow.workflow_runner.WorkflowEngine") as mock_wf_engine_cls,             patch("builtins.open", new_callable=MagicMock) as mock_open:
 
         # Instead of patching hook, we inject it directly