List the accounts a creator follows (paginated). Use for interest-graph and collaboration analysis. Paginate with cursor.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of items to return, <=50 | |
| cursor | No | Pagination cursor — pass the `cursor`/`max_cursor`/`has_more` value from a prior response. | |
| expand | No | Return the full untrimmed payload. Default false = compact JSON. | |
| user_id | Yes | @username or numeric user_id |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions pagination but omits behavioral traits like authentication needs, rate limits, or safety (read-only nature).
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 sentences, no waste. First sentence states purpose and pagination; second adds use case and cursor hint. Perfectly front-loaded and efficient.
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?
Schema covers all parameters, but with no output schema, the description lacks details on return format or error conditions. Adequate but incomplete for a mutation-free data retrieval tool.
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?
With 100% schema description coverage, the schema already explains all four parameters. The description reinforces cursor usage but adds no significant meaning beyond that.
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 verb 'List' and the resource 'accounts a creator follows', with pagination. It distinguishes from siblings like tiktok_creator_followers by specifying direction.
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?
It provides use cases ('interest-graph and collaboration analysis') and pagination guidance, but does not explicitly exclude alternatives or state when not to use this tool compared to siblings.
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 targets a distinct data type or action (creator, video, comment, sound, hashtag, search, etc.) with no functional overlap. Agents can easily distinguish them based on their clear entity-action pairing.
All tools follow a 'tiktok_' prefix and a consistent noun-first pattern (e.g., 'tiktok_creator_profile', 'tiktok_video_stats'), but there is a minor inconsistency between 'creator' and 'user' for the same entity (e.g., 'tiktok_user_stories' vs 'tiktok_creator_profile').
At 19 tools, the count is slightly high but justified by the breadth of TikTok's public data surface (profiles, videos, comments, sounds, hashtags, searches, etc.). Each tool serves a specific purpose, and the set feels comprehensive rather than bloated.
The tool set covers most read-only operations for TikTok public data, including profiles, videos, comments, sounds, hashtags, and searches. Missing are direct trending feeds or aggregated analytics, but search capabilities compensate. No create/update/delete exists, which is expected for a data extraction server.