tiktok_profile_followers_listList followers of a TikTok profile by handle. Returns a list (use cursor when paginated).
| Name | Required | Description | Default |
|---|---|---|---|
| trim | No | Optional flag for a smaller response with fewer fields. | |
| cursor | No | Pagination cursor returned by a previous response. | |
| handle | Yes | TikTok handle whose followers should be listed. | |
| userId | No | Optional TikTok user id to speed up the request. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare the tool as read-only and open-world, so the safety profile is covered. The description adds the pagination behavior via cursor, which is behaviorally important and not implied by annotations. It does not detail response structure, but the read-only nature and the list return type cover the core expectations.
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 two short sentences with no waste. The main purpose is front-loaded, followed by a concise note on pagination. Every word contributes to understanding, and it avoids unnecessary elaboration.
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?
The description is adequate for a simple list tool, but it does not specify the structure of the returned list items (e.g., whether they are full user objects or just handles). Since there is no output schema, this is a notable gap. It also does not mention any pagination limits, but the cursor note hints at that. Overall, it covers the essentials but leaves room for improvement.
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?
Schema coverage is 100%, with all parameters described. The description only mentions the handle and cursor, which are already in the schema, and does not add new semantic meaning. The baseline of 3 applies because the schema carries the parameter details.
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), the resource (followers of a TikTok profile), and the key identifier (by handle). This is specific and distinguishes it from the sibling tool tiktok_profile_following_list, which deals with following. It also mentions the return type (a list) and pagination, reinforcing its purpose.
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 does not provide any guidance on when to use this tool versus alternatives, nor does it mention exclusions or conditions. It simply states what it does. With a close sibling like tiktok_profile_following_list, explicit differentiation would help an agent choose correctly, but it is absent.
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.