Search TikTok creators by keyword/name, returning matching profiles. Use for influencer discovery and account lookup. Paginate with cursor.
| Name | Required | Description | Default |
|---|---|---|---|
| count | No | Number of items to return, <=30 | |
| 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. | |
| keyword | Yes | Search query text |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description mentions pagination with 'cursor', which is a useful behavioral trait. With no annotations, the description carries the full burden; it could disclose more about auth needs or rate limits, but the basic pagination behavior is covered.
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?
Three concise sentences with purpose first, no fluff. Every sentence adds value.
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 lacks detail about the response structure (profile fields) and does not explain what 'matching profiles' contains, which would help agents understand return values better, especially without an output schema.
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%, so parameters are well-documented in the schema. The description reinforces the cursor parameter's purpose but adds no new meaning beyond what the schema already provides.
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 searches TikTok creators by keyword/name and returns matching profiles, distinguishing it from other TikTok search tools (e.g., search videos, hashtags) and creator-specific tools (e.g., creator profile).
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 explicitly recommends use for 'influencer discovery and account lookup', providing clear usage context. However, it does not mention when to avoid using this tool or suggest alternatives like tiktok_resolve_username for exact username resolution.
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.