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tiktok_search

Search TikTok videos by keyword through Crawlora MCP, using cursor and count to page results and return matching video items with has_more metadata.

Instructions

Search TikTok videos. Searches TikTok videos for keyword. cursor defaults to 0 and count defaults to 20, capped at 50. The response has the matching video items, a cursor and has_more for paging. An empty, blocked or malformed result from TikTok returns an upstream error.

Input Schema

NameRequiredDescriptionDefault
countNoResult count, clamped to 50
cursorNoPagination cursor
keywordYesSearch keyword

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

A3.9/5.0
Behavior4/5

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

With no annotations provided, the description carries the load and does it well for the core behaviors: default cursor (0), default count (20), cap of 50, the response shape (video items, cursor, has_more), and the failure mode (empty/blocked/malformed upstream returns an error). It does not mention auth needs, rate limits, or caching, keeping it short of a 5.

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

Conciseness5/5

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

Four short sentences, front-loaded with the purpose, then paging defaults, response contents, and failure semantics — each sentence adds distinct information with no filler or repetition.

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?

No output schema and no annotations exist, so the description must cover both, and it does: return fields and error behavior are stated. Missing only ancillary context (permissions, rate limits, result freshness), which is a minor gap for a public search endpoint.

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

Parameters4/5

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

Schema description coverage is 100%, so the baseline is 3. The description goes beyond the schema by supplying the actual defaults that the schema omits (cursor=0, count=20) while restating the 50 clamp, which materially helps an agent construct a first call.

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 specific verb+resource combination ("Search TikTok videos") and identifies the required input (keyword). It implicitly contrasts with hashtag/user search by specifying videos, but never names the sibling tools (tiktok_search_hashtag, tiktok_search_user) or states an explicit boundary, so the differentiation is left to inference.

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

Usage Guidelines3/5

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

The purpose sentence implies the use case (keyword-based video search), but there is no explicit when-to-use, when-not-to-use, or alternative routing despite a large set of near-neighbor tiktok_* search tools. The pagination details hint at iterative use, but no guidance on which tool to pick is offered.

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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