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amazon_best_sellers

Get Amazon best-seller rankings for a category — Best Sellers, New Releases, Movers & Shakers, Most Wished For, or Gift Ideas. Each item includes rank, rank change, ASIN, title, price, and rating. Each page returns up to 50 ranked items (rankings typically cover the top 100).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNoPage number, 1 or 2 (default: 1). Each page returns up to 50 items; rankings cover the top 100.
typeNoRanking typebest_sellers
countryNoMarketplace country code (default: "us")us
categoryYesCategory slug, e.g. electronics or software (see /docs/amazon-categories)

TDQS

A4.4/5.0
Behavior4/5

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

With no annotations provided, the description carries the full burden. It discloses pagination behavior ('each page returns up to 50 ranked items'), the typical top-100 coverage, and the fields included in each item. It does not mention authentication, rate limits, or error behavior, but for a read-only rankings tool the disclosed behavior is substantial.

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?

Two tight sentences deliver the core action, the supported ranking types, the return fields, and pagination constraints. There is no fluff or repetition of obvious information.

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?

Given no output schema or annotations, the description does a good job of explaining what the response contains and how pagination works. It could be more complete by noting valid country-code values or potential limitations, but the essential information for selecting and calling the tool is present.

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?

Schema coverage is 100%, so the baseline is 3. The description adds meaningful context beyond the schema by explaining page size, top-100 coverage, and what each returned item contains. It reinforces the enum values and category slug concept, though it does not add much detail for the country parameter.

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 starts with a specific verb and resource: 'Get Amazon best-seller rankings for a category.' It enumerates the supported ranking types and clarifies that the result is a ranked list, which clearly distinguishes it from sibling product-search and product-detail tools like search_amazon_products and amazon_product_details.

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 makes the tool's purpose immediately evident: use when you need category best-seller rankings rather than product details or free-form product searches. It does not explicitly name alternatives or state when not to use it, but the context is clear enough that an agent can route appropriately.

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

B3.1/5.0
Disambiguation4/5

Most tools are clearly scoped by platform and resource (e.g. search_twitter vs twitter_user_tweets vs twitter_tweet_details). A few pairs like twitter_tweet_comments vs twitter_user_replies or facebook_page_posts vs search_facebook_posts could cause minor confusion, but descriptions generally clarify the distinction.

Naming Consistency4/5

The dominant pattern is snake_case with a platform_prefix_resource suffix, and search_* consistently marks search operations. Minor deviations include noun-style names like amazon_best_sellers and place_photos, and the odd get_ skill/comments tools, but the overall convention is predictable.

Tool Count2/5

74 tools is far beyond the typical well-scoped MCP server, even for a multi-platform API aggregator. The breadth is justified by the many platforms covered, but an agent will face a very large action space, and this could reasonably be split into per-platform servers.

Completeness4/5

The server provides strong lifecycle coverage for its read-only domain: search, profile/details, posts, and engagement data across most platforms. Gaps exist for some platforms (e.g. no LinkedIn person profile, no Facebook event details, no Truth Social profile/search, no Reddit subreddit-specific tools), but the core workflows are well covered.

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