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tiktok-shop-mcp

tiktok-shop-mcp

by Buer2333

get_shop_videos_performance_tool

Ranks shop videos by GMV, views, and click-through, with seller and account-type filters, to reveal which videos drive TikTok Shop sales.

Instructions

Get performance ranking for all videos driving shop sales (GMV, views, click-through). account_type: ALL/SELF/AFFILIATE. Use seller_name to specify shop.

Input Schema

NameRequiredDescriptionDefault
currencyNoUSD
page_sizeNo
page_tokenNo
sort_fieldNogmv
sort_orderNoDESC
end_date_ltNo
seller_nameNo
account_typeNoALL
start_date_geNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.3.0

TDQS

B3.1/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It usefully discloses the ranking basis and the account_type choices (ALL/SELF/AFFILIATE), but says nothing about pagination behavior, default date ranges, sort behavior, or permissions — leaving meaningful behavioral gaps for a 9-parameter ranking tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Three short, front-loaded sentences with no filler; the core purpose and metrics come first. Slightly telegraphic but appropriately sized.

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

Completeness2/5

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

For a complex 9-parameter tool with no annotations and 0% schema coverage, the description is thin. An output schema exists so return values need not be restated, but date filtering, sorting, pagination, and currency semantics should have been addressed.

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

Parameters2/5

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

Schema description coverage is 0% across 9 parameters, so the description must compensate. It documents only account_type (with its enum values, which the schema lacks) and seller_name; currency, page_size, page_token, sort_field, sort_order, start_date_ge, and end_date_lt are left entirely unexplained.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description gives a specific verb+resource ('performance ranking for all videos driving shop sales') and names the metrics (GMV, views, click-through), so the agent knows exactly what this returns. It does not explicitly distinguish itself from nearby siblings like get_account_video_gmv_tool or get_videos_bestselling_tool, which keeps it from a 5.

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

Usage Guidelines3/5

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

The line 'Use seller_name to specify shop' implies scoping context, and account_type values are listed, so usage is partially implied. However, there is no when-to-use/when-not guidance nor any explicit routing to alternative video-performance or bestselling-videos tools.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.