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hhy5562877

Douyin MCP

by hhy5562877

get_sub_comments

Retrieve paginated replies for a specific Douyin comment by providing its comment ID. Access nested sub-comments with cursor and count controls for efficient pagination.

Instructions

Get replies (sub-comments) for a Douyin comment.

Args: comment_id: The parent comment ID cursor: Pagination cursor (default 0) count: Number of replies per page (default 20) source_keyword: Optional search keyword (used for referer)

Returns: dict containing replies list and pagination metadata

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNo
cursorNo
comment_idYes
source_keywordNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior3/5

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

No annotations are provided, so the description carries the burden of behavioral disclosure. It does disclose the return shape (dict with replies list and pagination metadata) and explains that source_keyword is used for the referer. However, it does not mention authentication needs, rate limits, error behavior, or confirm that this is a read-only operation, leaving some gaps relevant to a no-annotation tool.

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 compact, front-loaded with the core purpose, and uses a clear Args/Returns structure. Every sentence contributes meaning, and there is no repeated or redundant information.

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 tool is a straightforward paginated read operation with four parameters, all of which are explained. An output schema is present, so the description does not need to fully document return values. The main gap is the lack of any mention of auth or rate limits, but given the tool's simplicity, the description is largely sufficient.

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%, and the description fully compensates by explaining every parameter: comment_id is the parent comment ID, cursor is the pagination cursor, count is the number of replies per page, and source_keyword is an optional search keyword used for the referer. This adds real semantic meaning beyond the bare schema types and defaults.

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 opens with a specific verb+resource combination: 'Get replies (sub-comments) for a Douyin comment.' This clearly identifies the operation and naturally distinguishes it from the sibling get_video_comments, which presumably fetches top-level comments for a video rather than nested replies.

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

Usage Guidelines4/5

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

The description makes clear that the tool is for fetching replies to a parent comment, implying it should be used after a comment ID is obtained from a parent-comment tool like get_video_comments. It does not explicitly state when not to use it or name an alternative, but the context is clear enough for an agent to select it correctly.

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