feat: Make skill individuals directly accessible to consciousness node (#54)

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

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)

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