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update_bitable_record

Modify specific data in a Feishu Bitable record by updating field values for a single entry in a multidimensional table.

Instructions

    更新多维表格中的单条记录

    参数:
        app_token: 多维表格的token
        table_id: 数据表ID
        record_id: 记录ID
        fields: 要更新的字段字典

    返回:
        更新后的记录信息
    

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
app_tokenYes
table_idYes
record_idYes
fieldsYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The primary handler function implementing the 'update_bitable_record' tool. It uses the Lark_oapi to update a single record in a Bitable app table, decorated with @mcp.tool() for registration and @handle_feishu_error for error handling.
    @mcp.tool()
    @handle_feishu_error
    def update_bitable_record(
        app_token: str, table_id: str, record_id: str, fields: dict
    ) -> str:
        """
        更新多维表格中的单条记录
    
        参数:
            app_token: 多维表格的token
            table_id: 数据表ID
            record_id: 记录ID
            fields: 要更新的字段字典
    
        返回:
            更新后的记录信息
        """
        client = get_client()
        request = (
            UpdateAppTableRecordRequest.builder()
            .app_token(app_token)
            .table_id(table_id)
            .record_id(record_id)
            .request_body(lark.AppTableRecord.builder().fields(fields).build())
            .build()
        )
        response = client.bitable.v1.app_table_record.update(request)
        return lark.JSON.marshal(response.data, indent=4)
  • The call to register_bitable_record_tools(mcp), which defines and registers the update_bitable_record tool among others.
    register_bitable_app_tools(mcp)
    register_bitable_record_tools(mcp)
  • Imports for helper functions: get_client() used to obtain the Feishu client, and handle_feishu_error decorator applied to the tool.
    from ..client import get_client
    from ..exceptions import handle_feishu_error
Behavior2/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. While it correctly identifies this as an update operation, it doesn't mention important behavioral aspects like authentication requirements, error handling, whether the update is idempotent, what happens with invalid fields, or any rate limits. The description only states what the tool does at a basic functional level.

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 well-structured with clear sections for purpose, parameters, and return value. It's appropriately sized for a 4-parameter tool, with no redundant information. Every sentence serves a purpose, though the parameter explanations could be more informative.

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 that this is a mutation tool with no annotations, 4 parameters (including a nested object), and an output schema exists, the description is moderately complete. It covers the basic purpose and parameters but lacks important behavioral context for a write operation. The existence of an output schema means the description doesn't need to explain return values in detail, which helps.

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?

With 0% schema description coverage, the description attempts to compensate by listing all 4 parameters with brief explanations. However, the explanations are minimal ('多维表格的token', '数据表ID', '记录ID', '要更新的字段字典') and don't provide format requirements, constraints, or examples. The description adds some value over the bare schema but doesn't fully compensate for the complete lack of schema 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 verb ('更新' meaning 'update') and resource ('多维表格中的单条记录' meaning 'single record in a multi-dimensional table'), which is specific and unambiguous. It distinguishes from batch operations by specifying 'single record', but doesn't explicitly differentiate from other sibling tools like batch_update_bitable_records beyond this implicit distinction.

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. There are multiple sibling tools for batch operations and other bitable functions, but the description doesn't mention any of them or provide context about when this single-record update is preferred over batch operations or other related tools.

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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