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Rank your best-performing posts

top_videos
Read-onlyIdempotent

Rank recent TikTok videos by views, likes, comments, shares, or engagement rate. Scans up to 200 recent posts to identify your high-performing content.

Instructions

Your best posts, ranked. TikTok has no ranked endpoint, so this pages recent videos and sorts them locally: scan is how far back it looks, and anything older than that cannot win. Use this rather than calling list_videos and sorting in context, which spends the whole window on videos you discard.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
scanNoHow many recent videos to look through before ranking. Default 60, maximum 200.
limitNoHow many to return. Default 10.
metricNoWhat to rank by. Default views.
accountNoWhich connected TikTok account to act as, by the name you gave it in TIKTOK_ACCOUNTS. Defaults to the first. Call list_accounts to see them.
Install Server

TDQS

A4.9/5.0
Behavior5/5

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

Beyond the readOnly/idempotent/destructive annotations, the description discloses non-obvious behavior: TikTok has no ranked endpoint, ranking is done locally after pagination, and anything older than scan cannot appear. This adds real behavioral context an agent would otherwise not know.

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 with no filler. The value proposition is front-loaded, the key limitation is stated early, and the alternative-use guidance is packed into one tight sentence.

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?

Given rich annotations, full schema coverage, and clear usage guidance, the description covers the main caveat and selection criteria. There is no output schema, but the return type (ranked videos) is inferable from the title and limit parameter, so nothing critical is missing.

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 input schema already covers all four parameters with 100% coverage, so the baseline is 3. The description adds meaningful interpretive value for `scan` ('how far back it looks, and anything older than that cannot win'), which justifies a slightly higher score; limit/metric/account are left to the schema.

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 states a specific task—'Your best posts, ranked'—and explains that it pages recent videos and sorts them locally. It also explicitly contrasts itself with list_videos, making its distinct purpose immediately clear.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives explicit, actionable guidance: use this rather than calling list_videos and sorting in context, and explains why ('spends the whole window on videos you discard'). The scan-bound caveat further clarifies when this tool is appropriate.

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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