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cfrs2005

GS Robot MCP Server

by cfrs2005

generate_task_report_png

Generate a PNG map for an M-line task report by providing the robot serial number and report ID.

Instructions

Generates a PNG map for M-line task report.

Args:
    serial_number: The serial number of the target robot.
    report_id: The ID of the task report.

Returns:
    A dictionary containing the map generation result.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
serial_numberYes
report_idYes

Implementation Reference

  • The core handler method in the GausiumMCP class that validates parameters and calls the API client to generate a task report PNG map.
    async def generate_task_report_png(
        self,
        serial_number: str,
        report_id: str
    ) -> Dict[str, Any]:
        """
        M线任务报告地图生成。
    
        Args:
            serial_number: 机器人序列号
            report_id: 报告ID
    
        Returns:
            地图生成结果
    
        Raises:
            ValueError: 参数为空
            httpx.HTTPStatusError: API调用错误
            httpx.RequestError: 网络问题
        """
        if not serial_number:
            raise ValueError("Serial number cannot be empty")
        if not report_id:
            raise ValueError("Report ID cannot be empty")
    
        async with GausiumAPIClient() as client:
            return await client.call_endpoint(
                'generate_task_report_png',
                path_params={
                    'serial_number': serial_number,
                    'report_id': report_id
                }
            )
  • API endpoint schema definition for generate_task_report_png, mapping to GET robots/{serial_number}/taskReports/{report_id}/map under v1alpha1.
    'generate_task_report_png': APIEndpoint(
        name="generate_task_report_png",
        path="robots/{serial_number}/taskReports/{report_id}/map",
        method=HTTPMethod.GET,
        version=APIVersion.V1_ALPHA1,
        description="M线任务报告地图生成"
    ),
  • The MCP tool registration/decorator that exposes generate_task_report_png as a tool, delegating to the GausiumMCP class method.
    @mcp.tool()
    async def generate_task_report_png(serial_number: str, report_id: str):
        """Generates a PNG map for M-line task report.
    
        Args:
            serial_number: The serial number of the target robot.
            report_id: The ID of the task report.
    
        Returns:
            A dictionary containing the map generation result.
        """
        return await mcp.generate_task_report_png(serial_number=serial_number, report_id=report_id)
Behavior2/5

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

No annotations are provided, so the description must disclose behavior fully. It mentions generation but does not state side effects (e.g., file storage), error conditions, or the format of the returned dictionary. The return type is vague.

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 concise with a clear structure (heading plus args/returns). It avoids unnecessary text, though the brevity sacrifices completeness. Still effective for its length.

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 simplicity of 2 string parameters and no output schema, the description is incomplete. It omits the structure of the return dictionary, typical usage scenarios, and relationship to sibling tools.

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

Parameters2/5

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

Schema description coverage is 0%, so the description should enrich parameter meaning. It merely rephrases the parameter names ('serial number of target robot', 'ID of the task report') without adding contextual hints like where to obtain these values.

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 it generates a PNG map for an M-line task report, identifying the specific resource and action. While the meaning of 'M-line' may be unclear, it distinguishes this tool from sibling map and report tools.

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

Usage Guidelines2/5

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

No guidance on when to use this tool versus alternatives like download_robot_map_v1/v2 or get_task_reports_smart. The description does not provide context for appropriate invocation.

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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