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Wulnut
by Wulnut

list_task_comments

Retrieve paginated comments for a specific work item using its issue ID. Review discussion and feedback by browsing comment lists from your project.

Instructions

获取指定工作项下的评论列表。

Args:
    issue_id: 工作项 ID。
    page_num: 页码,从 1 开始(默认 1)。
    page_size: 每页数量(默认 20,最大值由服务端限制)。
    project: 项目标识符(可选)。可以是项目名称或 project_key;不传则使用环境变量 FEISHU_PROJECT_KEY 指定的默认项目。
    work_item_type: 工作项类型名称(可选)。不传则使用默认类型。
    user_key: (可选) 飞书用户标识符 (X-USER-KEY)。

Returns:
    JSON 字符串。
    data 格式:
    {
      "total": int,
      "page_num": int,
      "page_size": int,
      "items": [
        {
          "comment_id": str|int,
          "author": Any,
          "create_time": Any,
          "content": str
        }
      ]
    }

Examples:
    list_task_comments(issue_id=123, page_num=1, page_size=20)

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
projectNo
issue_idYes
page_numNo
user_keyNo
page_sizeNo
work_item_typeNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.0.2

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations provided, the description carries the behavioral disclosure burden. It discloses pagination behavior, optional project/type fallback defaults, environment variable usage, and the JSON return shape. It does not mention error cases or explicitly confirm read-only semantics, but '获取...列表' sufficiently implies a non-mutating list operation.

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

Conciseness5/5

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

The description is well-structured with a clear one-line purpose, an Args section, a Returns section, and a minimal example. Every section adds necessary value, especially given the lack of schema descriptions, and there is no wasteful filler.

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?

For a 6-parameter tool with no annotations, the description covers parameter semantics, defaults, return format, and a usage example. It is sufficiently complete for an agent to call the tool correctly, though it could add error behavior or clarification of the optional user_key usage.

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 fully compensates by documenting every parameter: issue_id, page_num, page_size, project, work_item_type, and user_key. It adds meaningful semantics like defaults, the server-side page_size limit, the FEISHU_PROJECT_KEY fallback, and what 'project' can be.

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

Purpose5/5

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

The description begins with a clear verb and resource: '获取指定工作项下的评论列表' (retrieve the comment list under a specified work item). This differentiates it from sibling comment mutation tools like add_task_comment, update_task_comment, and delete_task_comment.

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 makes it clear this is for listing comments and provides an example call, but it does not explicitly state when to use this tool over alternatives or when not to use it. Sibling names imply the distinction, but no direct usage guidance is provided.

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