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cfrs2005

GS Robot MCP Server

by cfrs2005

execute_s_line_site_task_workflow

Automates S-line robot task workflows by processing site information to select maps, retrieve subareas, build tasks, and submit them for execution.

Instructions

Executes complete S-line robot task workflow with site information.

Automated process: Site info → Map selection → Subarea retrieval → Task building → Task submission

Args:
    robot_id: The ID of the target robot.
    task_parameters: Task parameters including map criteria and task settings.

Returns:
    A dictionary containing the workflow execution result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
robot_idYes
task_parametersYes

Implementation Reference

  • Primary MCP tool handler and registration for 'execute_s_line_site_task_workflow'. Delegates to GausiumMCP instance.
    @mcp.tool()
    async def execute_s_line_site_task_workflow(
        robot_id: str,
        task_parameters: dict
    ):
        """Executes complete S-line robot task workflow with site information.
        
        Automated process: Site info → Map selection → Subarea retrieval → Task building → Task submission
    
        Args:
            robot_id: The ID of the target robot.
            task_parameters: Task parameters including map criteria and task settings.
    
        Returns:
            A dictionary containing the workflow execution result.
        """
        return await mcp.execute_s_line_site_task_workflow(
            robot_id=robot_id,
            task_parameters=task_parameters
        )
  • GausiumMCP class method implementing the workflow by delegating to TaskExecutionEngine.
    async def execute_s_line_site_task_workflow(
        self,
        robot_id: str,
        task_parameters: Dict[str, Any]
    ) -> Dict[str, Any]:
        """
        执行S线有站点任务完整工作流。
        
        自动化流程:站点信息 → 地图选择 → 分区获取 → 任务构建 → 任务下发
        
        Args:
            robot_id: 机器人ID
            task_parameters: 任务参数
            
        Returns:
            工作流执行结果
        """
        return await self.task_engine.execute_s_line_site_task(
            robot_id=robot_id,
            task_parameters=task_parameters
        )
  • Core implementation of the S-line site task workflow in TaskExecutionEngine, handling site info retrieval, map selection, subarea fetching, task building, and submission.
    async def execute_s_line_site_task(
        self,
        robot_id: str,
        task_parameters: Dict[str, Any]
    ) -> Dict[str, Any]:
        """
        执行S线有站点任务。
        
        工作流:
        1. 获取站点信息
        2. 解析可用地图
        3. 获取目标地图分区
        4. 构建并下发有站点临时任务
        
        Args:
            robot_id: 机器人ID
            task_parameters: 任务参数
            
        Returns:
            任务执行结果
        """
        logger.info(f"Starting S-line site task execution for robot: {robot_id}")
        
        async with GausiumAPIClient() as client:
            try:
                # 1. 获取站点信息
                site_info = await client.call_endpoint(
                    'get_site_info',
                    path_params={'robot_id': robot_id}
                )
                
                # 2. 解析可用地图
                available_maps = self._extract_maps_from_site(site_info)
                if not available_maps:
                    raise ValueError("No maps found in site information")
                
                # 3. 选择目标地图
                target_map_id = self._select_map(
                    available_maps, 
                    task_parameters.get('map_criteria', {})
                )
                
                # 4. 获取地图分区
                subareas = await client.call_endpoint(
                    'get_map_subareas',
                    path_params={'map_id': target_map_id}
                )
                
                # 5. 构建任务数据
                task_data = self._build_site_task_data(
                    target_map_id, 
                    subareas, 
                    task_parameters
                )
                
                # 6. 下发有站点临时任务
                task_result = await client.call_endpoint(
                    'submit_temp_site_task',
                    json_data=task_data
                )
                
                logger.info(f"S-line site task executed successfully: {task_result}")
                return task_result
                
            except Exception as e:
                logger.error(f"S-line site task execution failed: {str(e)}")
                raise
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the automated process steps, which gives some context about what the tool does internally. However, it doesn't disclose critical behavioral traits such as whether this is a read-only or destructive operation, authentication requirements, rate limits, error handling, or what 'complete workflow' entails in terms of time or resource consumption. The description adds minimal value beyond the basic purpose.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized and front-loaded: the first sentence states the core purpose, followed by a bullet-point-like automated process list and parameter explanations. Each sentence adds value without redundancy. However, the structure could be slightly improved by using actual bullet points or clearer formatting for the process steps.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the complexity (workflow execution with nested parameters), lack of annotations, and no output schema, the description is incomplete. It doesn't explain the return value beyond 'a dictionary containing the workflow execution result', leaving the agent uncertain about success/failure indicators, data format, or error responses. For a tool with 2 parameters (one nested) and significant behavioral implications, more context is needed to guide effective use.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, so the schema provides no parameter descriptions. The description adds some semantics: it explains that 'robot_id' is for the target robot and 'task_parameters' includes map criteria and task settings. However, it doesn't detail what specific criteria or settings are expected, the format of 'task_parameters', or provide examples. With 2 parameters and low schema coverage, this partial compensation earns a baseline score.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: executing a complete S-line robot task workflow with site information. It specifies the verb ('executes') and resource ('S-line robot task workflow'), and distinguishes it from sibling tools like 'execute_s_line_no_site_task_workflow' by mentioning site information. However, it doesn't fully differentiate from 'execute_m_line_task_workflow' beyond the S-line specificity.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description implies usage context through the automated process steps (Site info → Map selection → Subarea retrieval → Task building → Task submission), suggesting this is for comprehensive workflow execution. It distinguishes from 'execute_s_line_no_site_task_workflow' by including site information. However, it lacks explicit guidance on when to use this versus alternatives like 'submit_temp_site_task' or 'execute_m_line_task_workflow', and doesn't mention prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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