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TikTok User Followers

tiktok_user_followers
Read-only

Get a TikTok user's followers, newest first, by username, numeric user ID or profile URL (provide exactly one). Returns username, display name, user ID, bio, follower and following counts, total likes, video count, verification status, region, join date and linked Instagram, X and YouTube accounts for each follower, 100 per page. A private account returns a 403 limited_account error. Billed $0.006 per page.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
urlNoTikTok profile URL, e.g. https://www.tiktok.com/@tiktok (max 500 characters). Provide exactly one of username, user_id, or url.
pagesNoNumber of pages to fetch, 1-1000 (default: 1). Each page returns up to 100 followers.
user_idNoNumeric TikTok user ID, as returned by Search Users or User Profile. Provide exactly one of username, user_id, or url.
usernameNoTikTok username, with or without leading @ (max 100 characters). Provide exactly one of username, user_id, or url.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A4.5/5.0
Behavior5/5

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

Annotations cover read-only/open-world/non-destructive safety, and the description goes well beyond them: it discloses pagination granularity (100 per page), a concrete error path (403 limited_account for private accounts) and per-page billing ($0.006). These are exactly the operational facts an agent needs before paying for calls.

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?

Front-loads purpose and identifiers, then packs return fields, pagination, error behavior and pricing into tight clauses with no filler. Every sentence contributes something an agent cannot get from the schema or annotations.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

With no output schema, the description carries the return-value burden and does so by enumerating the per-follower fields (username, counts, verification, region, join date, linked accounts). Error handling, pagination and cost are all covered, so an agent can call and interpret results without further information.

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

Parameters3/5

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

Schema description coverage is 100% and the schema already documents each parameter including the 'provide exactly one' rule and the 100-per-page behavior, so the description largely restates it. It adds the 'newest first' ordering, but that is output/behavioral rather than parameter meaning, leaving the baseline of 3 appropriate.

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 ('Get a TikTok user's followers') plus a scope/ordering qualifier ('newest first'), which cleanly separates it from the sibling tiktok_user_following. The identifier options are named up front so the agent knows exactly what resource is being retrieved.

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 'provide exactly one' constraint gives clear invocation context, and the identifier list clarifies accepted inputs. However, it never names an alternative tool or states when-not to use it (e.g. vs tiktok_user_following), so the routing guidance relies on the tool name rather than explicit exclusions.

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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