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TokConnect: TikTok Research

topic_detail

CSI topic metadata — fetch one topic by its existing CSI queryId. Returns a normalized topic record and available topCountries, relatedProduct and usesInsightsVideoEndpoint metadata. The endpoint flag is TikTok metadata, not a promise that related_videos uses that endpoint. Does not fetch videos, popularity charts or demographics; those are separate tools.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
query_idYesCSI topic queryId returned by search_topics, browse_topics, trending_topics or related_topics. Not a video ID, username or keyword.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.4/5.0
Behavior4/5

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

No annotations, so the description carries the behavioral burden. It discloses return content and a non-obvious caveat about usesInsightsVideoEndpoint being metadata rather than a functional promise, which is valuable. It doesn't discuss auth, rate limits, or error cases.

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?

Three sentences, front-loaded with purpose, then returns, then exclusions. No filler; every clause adds actionable information.

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, so the description must explain return values, which it does adequately by listing key fields. It also clarifies boundaries against other tools. Missing details on error handling or pagination, but for a single-object fetch that's minor.

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 baseline is 3. The description adds meaning by specifying this is a CSI queryId and clarifying it's not a video ID, username, or keyword—information echoed in the schema but reinforced in the main description.

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?

Specific verb (fetch) + resource (one CSI topic) + identifier (queryId). It also names the exact fields returned and explicitly disambiguates from siblings by stating it does not fetch videos, popularity charts, or demographics.

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?

Clearly scopes what the tool does not do and implies proper usage (single topic lookup by ID). It references source tools indirectly via 'existing CSI queryId' but doesn't explicitly list which tools generate valid IDs, though the schema description does.

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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