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TokConnect: TikTok Research

search_live

Search TikTok LIVE rooms by keyword. Preserves the native live_info payload. Room status and counters describe the response time, not historical performance. One upstream request. Returns native data, cursor, has_more and log_pb.impr_id. Pass that ID as search_id with the returned cursor for another page; no automatic paging or analysis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
countNoRequested results, 1-30; default 10.
cursorNoReturned cursor; default 0.
keywordYesSearch phrase, 1-300 bytes.
search_idNoFirst page log_pb.impr_id; required when cursor > 0.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.1/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does well: it discloses a single upstream request, that the response is native/unprocessed data, and importantly that room status and counters reflect the response time rather than historical performance. It omits auth requirements, rate limits, and error behavior, 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.

Conciseness4/5

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

Four compact sentences, front-loaded with the purpose before the payload and paging caveats. Dense but every sentence carries information; minor awkwardness in the status/counters sentence.

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?

For a tool with no annotations and no output schema, the description compensates by naming the returned fields (native data, cursor, has_more, log_pb.impr_id) and explaining how to page. An agent can call it correctly and chain pages, though return-shape detail and error handling remain thin.

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 coverage is 100%, so the baseline is 3, but the description adds real value by spelling out the pagination loop: use log_pb.impr_id as search_id together with the returned cursor, and it clarifies cursor semantics (returned cursor, default 0) beyond the schema text.

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

Purpose5/5

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

States a specific verb and resource ("Search TikTok LIVE rooms by keyword"), and the LIVE-rooms scope distinguishes it from siblings like search_videos, search_all, and search_users without needing to open any schema.

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?

Gives clear operational guidance for paging (pass log_pb.impr_id as search_id with the returned cursor) and warns there is no automatic paging or analysis, but never states when to choose this tool over the many sibling search_* tools, which is the main selection decision an agent faces.

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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