Get the connected TikTok account's profile (username, display name, avatar) and stats (followers, following, likes, videos).
| Name | Required | Description | Default |
|---|---|---|---|
| in_workspace | No | Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected. |
Changes observed during successful MCP inspections.
Input schema / properties / in_workspaceAdded value: +{
+ "description": "Run this one call in this workspace id instead of the session's. Nothing is stored; other sessions are not affected.",
+ "type": "integer"
+}Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, idempotentHint=true, destructiveHint=false and openWorldHint=false, so the safety and determinism profile is covered. The description adds that it reads the 'connected' account (single-account scope) and lists returned fields, but says nothing about auth requirements, rate limits, or what happens when no account is connected. With annotations carrying the safety burden, this is adequate but not rich.
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?
A single, well-formed sentence with zero waste, front-loading the verb and resource and parenthetically enumerating the returned fields. Nothing needs to be trimmed.
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?
There is no output schema, but the description compensates by listing the exact fields returned, which is the key information an agent needs. It omits edge cases (no connected account, error behavior), which keeps it just short of fully complete for a stats tool.
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 description coverage is 100% and the single parameter (in_workspace) is fully documented in the schema, so baseline 3 applies. The description adds nothing about the parameter, which is acceptable given the schema already explains its semantics.
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?
States a specific verb (Get) and resource (connected TikTok account's profile and stats) and enumerates exactly what comes back (username, display name, avatar, followers, following, likes, videos). This clearly distinguishes it from the siblings tiktok_list_videos and tiktok_publish_video, which operate on videos rather than the account itself.
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?
Usage is implied by the name and description (fetch account-level metrics), but there is no explicit when-to-use, when-not-to-use, or routing to alternatives. An agent can infer the purpose but gets no guidance on conditions or prerequisites.
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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