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lark-agent

by Wulnut
OverviewSchemaSourceRelated ServersDiscussionsAdmin
Python
Remote

update_task

Update work item fields in Feishu/Lark project management by specifying issue ID and new values for title, priority, status, assignee, or custom fields via JSON to keep project data accurate.

Instructions

更新工作项的字段。

可以同时更新多个字段，这些字段可以通过 fields_json 一次性传入。

Args:
    issue_id: 要更新的工作项 ID。
    project: 项目标识符（可选）。
    work_item_type: 工作项类型名称（可选）。
    name: 新标题（可选）。
    priority: 新优先级（可选）。
    description: 新描述（可选）。
    status: 新状态（可选）。
    assignee: 新负责人（可选）。
    field_name: 单个自定义字段名称（可选）。
    field_value: 单个自定义字段值（可选）。
    fields_json: JSON 格式的字段字典（可选），用于批量更新多个自定义字段。
                 例如: '{"Soc Vendor": "Amlogic", "DDR 大小": "128MB"}'
    user_key: (可选) 飞书用户标识符 (X-USER-KEY)，用于以特定用户身份进行操作。

Returns:
    成功时返回 "更新成功"。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameNo
statusNo
projectNo
assigneeNo
issue_idYes
priorityNo
user_keyNo
field_nameNo
descriptionNo
field_valueNo
fields_jsonNo
work_item_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.2

TDQS

A3.6/5.0
Behavior3/5

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

With no annotations, the description carries the burden of behavioral disclosure. It does add useful behavioral context: multiple fields can be updated at once, fields_json enables bulk custom-field updates, user_key allows acting as a specific user, and success returns '更新成功'. However, it does not mention permissions, reversibility, partial-failure behavior, or side effects for a mutating operation.

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 organized with a short summary, an Args list, and a Returns line. Each parameter earns its place given the zero schema coverage, though the repeated '（可选）' markers add some redundancy with the schema's optionality.

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

Completeness4/5

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

The description covers all 12 parameters and the return value, which is essential because the schema provides no descriptions. It does not clarify interactions or conflicts between field_name/field_value vs fields_json, nor does it mention valid values or when to prefer transition_task_status, leaving minor gaps for a 12-parameter tool.

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?

Schema description coverage is 0%, so the description must explain all parameters. It does: every parameter is listed with a plain-language meaning, and fields_json is accompanied by a concrete JSON example. This compensates fully for the 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 tool updates work item fields, with a specific verb and resource. It also highlights multi-field updates via fields_json, but it does not explicitly distinguish itself from the sibling tool batch_update_tasks or clarify that status transitions should go through transition_task_status.

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 explicit guidance is given about when to use this tool versus alternatives such as transition_task_status or batch_update_tasks. The description lists parameters but does not state prerequisites, exclusions, or which scenarios favor a sibling tool.

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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