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List TikTok video comments

list_tiktok_video_comments
Read-only

Fetch one cursor-paginated page of current comments for a TikTok video URL.

Pass the returned cursor to retrieve the next page. This is a metered live-data request.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlYes
cursorNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
okNo
dataNo
countNo
resultsNo
has_moreNo
not_foundNo
next_cursorNo
suggested_followupsNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • changedInput schema / properties / cursor / maxLength
      Previous value: -512New value: +2048
  2. Added

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already indicate readOnlyHint=true, openWorldHint=true, and destructiveHint=false. The description adds valuable context beyond those: this is a metered live-data request and each call returns only one cursor-paginated page. This helps the agent understand rate/cost implications and pagination mechanics, which the annotations do not convey.

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 and efficient: two short sentences plus a metering warning. Every sentence earns its place, the core purpose is front-loaded, and no redundant detail is included.

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

Completeness5/5

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

Given the existence of an output schema, the description does not need to detail return values. It covers the essential operational context: one page per call, cursor-based continuation, live-data nature, and metering. This is sufficient for an agent to select and invoke the tool correctly.

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

Parameters4/5

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

Schema description coverage is 0%, so the description must carry parameter meaning. It does: 'TikTok video URL' maps to the required url parameter, and 'Pass the returned cursor' explains how the optional cursor parameter is used. This adds real semantic value beyond bare schema names, though it could be slightly more explicit about the cursor being the pagination token.

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 states a specific action ('Fetch'), a clear resource ('comments'), and a precise scope ('for a TikTok video URL'). This clearly distinguishes it from sibling tools like get_tiktok_video_captions or list_tiktok_comment_replies, since it targets top-level video comments, not captions or 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 gives clear context: use this when you need a page of current comments for a TikTok video URL. It also explains pagination behavior ('Pass the returned cursor to retrieve the next page'). It does not explicitly name alternatives or say when not to use it, but the resource-focused wording makes the intended use reasonably clear.

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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