Eagles and Angels Limited AI Gateway

Best sellers

best_sellers

Read-onlyIdempotent

The store's best-selling / most popular products, ranked by real units sold from captured orders. Use this to answer "what is your best product", "most popular", "top seller", or to recommend what to buy.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`days`	No	Look-back window in days (default 90, max 365)
`limit`	No	How many products to return (default 10, max 25)

Output Schema

TableJSON Schema

Name	Required	Description	Default
`window_days`	No
`best_sellers`	Yes

TDQS

A4.3/5.0

Behavior4/5

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds meaningful behavioral context beyond that: it clarifies that popularity is based on actual captured order units rather than views, ratings, or editorial choices. This helps an agent set correct expectations about the output semantics.

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 sentences with no filler. The core definition comes first, followed by explicit user-intent examples. Every phrase earns its place and the description is immediately scannable.

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?

The tool is simple, has fully documented optional parameters, full annotation coverage, and an output schema. The description adds the only missing semantic detail—what 'best sellers' means operationally—making it complete for selection and invocation.

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%, with both 'days' and 'limit' fully documented including defaults and maximums. The description adds no additional parameter syntax or format nuance; it provides only high-level context about the ranking, so a baseline score of 3 is 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?

The description clearly identifies a specific resource ('the store's best-selling / most popular products'), a specific ranking criterion ('real units sold from captured orders'), and concrete intents ('best product', 'most popular', 'top seller'). This differentiates it from sibling tools like list_products and popular_content by scope and metric.

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 explicitly maps natural language queries to this tool: 'what is your best product', 'most popular', 'top seller', and recommendation requests. It gives strong positive usage context, though it does not explicitly state when to prefer a sibling like related_products or popular_content.

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

A3.9/5.0

Disambiguation3/5

Most tools are scoped to either products or articles, but there are overlapping pairs: check_inventory and get_product both return price and variant stock, and fetch and get_article both retrieve full-text content. search, search_products, and search_articles also share similar search intent, though their descriptions help clarify scope.

Naming Consistency3/5

The set mixes verb+noun tools like list_products, get_article, and search_products with bare verbs like fetch and search, and noun-phrase tools like best_sellers, popular_content, related_products, and store_info. The naming is readable and partially patterned, but not consistently structured.

Tool Count4/5

15 tools is at the upper end of the typical range, covering both a storefront and a publication plus sitewide search. The count is reasonable for the combined scope, though a few tools like check_inventory and get_product overlap enough that the set could be slightly tighter.

Completeness4/5

The gateway covers catalog browsing, product search, inventory, cart building, store policies, article search/retrieval, recent content, popular content, and general site search. Minor gaps include no paged listing of all articles beyond recent and no direct category-filtered product listing, but core workflows are well supported.

Resources

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