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Vee3

by io.github.Vee3io

tiktok.user_info

Look up a TikTok user profile. Provide either user_id or unique_id, not both.

Cost = 2 tokens.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
user_idNoTikTok numeric user id.
unique_idNoTikTok unique id (username).

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
msgNoUpstream status message.
codeNoUpstream status code (0 = success).
dataNoCapability-specific payload from the upstream provider.
processed_timeNoUpstream processing time in seconds.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changed
    • changedOutput schema / properties / processed_time / anyOf
      Previous value: -[
-  {},
-  {
-    "type": "null"
-  }
-]New value: +[
+  {
+    "type": "number"
+  },
+  {
+    "type": "null"
+  }
+]
  2. First observed

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations provided, the description carries the transparency burden. It discloses the cost (2 tokens) and the mutual exclusivity of parameters. However, it doesn't specify what happens if both or neither parameter is provided, or error behavior for invalid IDs. This is a simple read operation, so the disclosure is adequate but not rich, hence a 3.

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?

The description is extremely concise: two sentences that immediately state the purpose and the key parameter constraint. It is front-loaded and contains zero wasted words. Every sentence earns its place.

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 low-complexity lookup tool with an output schema and fully described parameters, the description is largely complete. It includes the essential context (profile lookup, parameter constraint, cost). It doesn't cover return values, but the output schema handles that. A small gap is lack of error case behavior, but this doesn't significantly impact completeness for this simple tool.

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?

The schema already fully describes both parameters (user_id and unique_id) with descriptions. The description adds meaningful semantics beyond the schema by introducing the mutual exclusion constraint ('not both'), which is not captured in the schema. This raises the baseline from 3 to 4.

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?

The description clearly states the tool's function: 'Look up a TikTok user profile.' This is a specific action with a clear resource, and it distinguishes this tool from sibling TikTok tools (e.g., user_videos, user_followers) by focusing on profile data. The action verb 'look up' and resource 'profile' are unambiguous.

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?

The description provides clear context that this tool is for profile lookups and includes the important usage constraint 'Provide either user_id or unique_id, not both.' This implies when to use it (for profile info) and provides parameter-level guidance. It doesn't explicitly mention alternatives or when-not-to-use, but the context is clear enough for an agent to differentiate from sibling tools.

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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TDQS

A4.1/5.0
Disambiguation5/5

Each tool has a distinct purpose, further clarified by group prefixes and clear descriptions. Within each group, tools perform different operations (e.g., domains.lookup vs. domains.whois vs. domains.rdap) with no ambiguity.

Naming Consistency5/5

All tools follow a consistent group.tool_name pattern using snake_case. The naming is predictable and uniformly applied across all groups.

Tool Count4/5

78 tools is high, but the server aggregates multiple distinct API domains (11 groups). Each group has a reasonable number of tools, typically under 10, with TikTok having 17. The count reflects breadth, not bloat.

Completeness5/5

Each domain's tool set covers the primary expected operations (e.g., search, details, reviews, metrics, user info). There are no obvious gaps for read-only analytical use; features like posting are likely out of scope.

Resources