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Roland0511

MCP Feishu Project Manager

by Roland0511

get_work_item_detail

Retrieve detailed information about specific work items in Feishu project management systems. Use this tool to access requirements, versions, or defect details by providing work item IDs and types.

Instructions

获取指定工作项的详情信息 Args: work_item_type_key: 工作项类型,可选值为"story"、"version"、"issue", 分别对应需求、版本、缺陷。 work_item_ids: 工作项ID,多个ID之间用逗号分隔

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
work_item_type_keyYes
work_item_idsYes

Implementation Reference

  • MCP tool handler for get_work_item_detail: parses input IDs and fetches details via FSProjClient.
    @mcp.tool("get_work_item_detail")
    def get_work_item_detail(work_item_type_key: WorkItemType, work_item_ids: str):
        """获取指定工作项的详情信息
        Args:
            work_item_type_key: 工作项类型,可选值为"story"、"version"、"issue", 分别对应需求、版本、缺陷。
            work_item_ids: 工作项ID,多个ID之间用逗号分隔
        """
        client.get_plugin_token()
        id_list = [int(id.strip()) for id in work_item_ids.split(",")]
        return client.get_workitem_detail(work_item_type_key, id_list)
  • Literal type defining allowed work_item_type_key values (story, version, issue). Used in tool signature.
    WorkItemType = Literal["story", "version", "issue"]
  • FSProjClient helper method that performs the actual API call to retrieve work item details.
    def get_workitem_detail(self, work_item_type_key: WorkItemType, work_item_ids: List[int]) -> List[Dict]:
        """获取工作项详情
        
        Args:
            work_item_type_key: 工作项类型标识
            
        """
        data = {
            "work_item_ids": work_item_ids
        }
        
        response = self._request(
            "POST", 
            f"/open_api/{self.project_key}/work_item/{work_item_type_key}/query",
            json_data=data
        )
        err_code = response.get("code", 0)
        if err_code != 0:
            raise Exception(f"获取工作项详情失败,错误码: {err_code}, 错误信息: {response.get('err_msg')}")
        return response.get("data", {})
Behavior2/5

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

With no annotations provided, the description carries full burden for behavioral disclosure. It only states what the tool does (retrieves details) but doesn't mention whether this is a read-only operation, what permissions might be required, whether there are rate limits, what format the details come in, or any error conditions. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 concise with a clear structure: purpose statement followed by parameter explanations. The Chinese text is efficient with no wasted words. It could be slightly improved by front-loading the most critical information more explicitly, but overall it's well-structured and to the point.

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

Completeness3/5

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

Given the tool's moderate complexity (2 required parameters, no output schema, no annotations), the description is minimally adequate. It explains what the tool does and documents the parameters well, but lacks information about the return format, error handling, or behavioral constraints. Without annotations or output schema, the agent won't know what to expect from the response.

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

Parameters5/5

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

The description provides excellent parameter semantics beyond the input schema. While the schema has 0% description coverage, the description explains: 1) what 'work_item_type_key' represents ('工作项类型' - work item type), 2) the meaning of each enum value ('story'对应需求, 'version'对应版本, 'issue'对应缺陷), and 3) how to format 'work_item_ids' ('多个ID之间用逗号分隔' - multiple IDs separated by commas). This fully compensates for the schema's lack of descriptions.

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: '获取指定工作项的详情信息' (Get details of specified work items). It specifies the verb ('获取' - get) and resource ('工作项的详情信息' - work item details), making the purpose unambiguous. However, it doesn't distinguish this tool from potential sibling tools that might also retrieve work item information, keeping it from a perfect score.

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?

The description provides no guidance on when to use this tool versus alternatives. While sibling tools like 'get_view_detail' or 'get_work_item_type_meta' exist, there's no indication of when this specific tool is appropriate versus those others. The description only explains what the tool does, not when to choose it.

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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