tiktok_video_comments_listList comments on a TikTok video by URL. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the TikTok video whose comments should be listed. | |
| trim | No | When true, returns a smaller response with fewer fields. | |
| cursor | No | Opaque cursor from a previous response to fetch the next page. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds the behavioral detail that the response is a list and that pagination via cursor may be required, which goes beyond the readOnlyHint annotation. It does not contradict any annotations. However, it doesn't disclose other behaviors like rate limits or response size limits, but the annotations cover the read-only nature, so the added cursor info is valuable.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two short sentences convey the core purpose and a key usage note. It's front-loaded with the primary action and avoids unnecessary details. Each sentence earns its place, making it highly concise and well-structured.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a simple read-only list tool, the description covers the essential: it lists comments, returns a list, and mentions pagination. It could mention what the list contains (comment objects) or any limits, but given the schema and annotations, it's fairly complete. It might benefit from noting that it returns top-level comments (vs replies), but that is inferable from the sibling name and the resource.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
All parameters are described in the schema (100% coverage). The description mentions the URL and cursor usage, but the schema already provides detailed descriptions for each parameter (e.g., cursor as 'Opaque cursor from a previous response'). The description adds no new semantic information beyond what the schema already states, so a baseline score of 3 is appropriate.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the action (list comments) and the resource (TikTok video by URL). It distinguishes from siblings like tiktok_video_comments_replies_list by the verb and resource, even though it doesn't explicitly name the alternative. The purpose is unambiguous and specific.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description provides a usage hint about using cursor when paginated, which is helpful for handling large results. However, it does not explicitly state when to use this tool versus similar comment-listing tools on other platforms or the replies variant. The guidance is limited to pagination, not tool selection.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool is clearly scoped to a specific platform and action (e.g., facebook_post_get vs instagram_post_get). Descriptions explicitly differentiate similar tools across platforms, and within-a-platform tools like tiktok_search_videos_list vs tiktok_search_hashtag_list have clear disambiguation notes.
All 167 tools follow a strict `platform_resource_action` pattern (e.g., youtube_video_comments_list). No mixing of styles—snake_case throughout, with consistent verb ordering (get, list, search, etc.).
The server has 167 tools, which is far beyond the typical well-scoped range of 3-15. While the broad multi-platform scope justifies many tools, this extreme number makes the tool surface overwhelming and difficult for an agent to navigate efficiently.
The tool set covers a wide range of platforms and operations including profile retrieval, post/video fetching, comments, search, transcripts, and ad library access. Minor gaps exist (e.g., no Facebook events or LinkedIn messaging), but the surface is comprehensive for a read-only data aggregation use case.