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by com.hasdata
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tiktok_search: GET /

hasdata_tiktok_search_getTikTokSearch
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Search TikTok

Searches TikTok by keyword and returns either videos (with description, hashtags, mentions, like/comment/share/play counts, cover and playable video URLs, music, and author) or users (nickname, bio, avatar, verified flag, follower count). Each author and each user carries a hasdataLink to their profile endpoint and a hasdataPostsLink to their posts endpoint. Supports token-based pagination via nextPageToken. Use for content discovery, trend research, influencer discovery, or building datasets from a keyword.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "keyword": "<keyword>"
    },
    "name": "hasdata_tiktok_search_getTikTokSearch"
  }
}

Input Schema

NameRequiredDescriptionDefault
typeNoWhat to search for — videos or users. Defaults to video.
keywordYesThe phrase to search for on TikTok.
nextPageTokenNoDefines the next page token. Use the `nextPageToken` value returned by the previous response. Omit it to fetch the first page.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.9/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnlyHint/openWorldHint/destructive=false, so the safety profile is covered. The description adds genuinely useful context: the token-based pagination model via nextPageToken, the fields returned per result type, and the embedded hasdataLink/hasdataPostsLink pointers.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loaded with the one-line purpose, then output shape, pagination, and use cases in sequence. It is on the longer side but each sentence carries distinct information, so little is wasted.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden and does so by describing video vs user fields and the cross-links. Combined with full schema coverage and safety annotations, an agent has enough to call it correctly, though the sibling boundary remains implicit.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the enum, keyword, and nextPageToken semantics are already fully documented in the schema. The description only restates pagination at a high level, adding no syntax or format detail beyond what the schema provides; baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a clear verb+resource ('Searches TikTok by keyword') and enumerates the two result shapes (videos vs users) with their fields. It stops short of explicitly contrasting with the closely related siblings like hasdata_tiktok_profile or hasdata_tiktok_posts, though the hasdataLink/hasdataPostsLink mentions hint at the boundary.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides concrete use cases: 'content discovery, trend research, influencer discovery, or building datasets from a keyword.' This gives clear positive context for when to reach for it, but names no alternatives or exclusions (e.g., when to prefer the profile or posts endpoints).

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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