tiktok_video_comments_replies_listList replies to a TikTok video comment. Accepts a comment id. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| url | Yes | Link to the TikTok video that contains the parent comment. | |
| cursor | No | Opaque cursor from a previous response to fetch the next page. | |
| commentId | Yes | Parent comment id from List TikTok video comments (`data.comments[].id`). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint=true, and the description adds useful behavioral context by noting the tool returns a list and supports cursor-based pagination. It does not contradict annotations, and given the read-only nature, no further side-effect disclosure is needed.
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?
The description is a single, concise sentence that delivers the core purpose and pagination note upfront. No wasted words or redundant details.
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 with a well-documented schema, the description is largely sufficient. It covers what the tool does, the key input (comment id), and the output (list with pagination). The only minor gap is not explicitly stating that the video URL is required, but the schema marks it and the description does not mislead.
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?
The schema fully describes all three parameters (url, cursor, commentId), including that commentId originates from the comments list. The description adds no unique parameter semantics beyond restating 'accepts a comment id', which is already in the schema. With 100% schema coverage, the baseline 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 tool lists replies to a TikTok video comment, accepts a comment id, and returns a list with pagination. It distinguishes from tiktok_video_comments_list (which lists comments on a video) by its focus on replies and explicit comment id requirement.
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 implies usage when you have a comment id and want its replies, but does not explicitly state when to use this tool over alternatives (e.g., youtube_video_comments_replies_list) or provide exclusions. It also omits mention that the video url is required, though the schema covers that. Guidance is implied rather than explicit.
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.