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everlane_collections

Retrieve Everlane collections as structured JSON data. Specify page and limit to paginate through results and get clean, normalized collection lists for commerce workflows.

Instructions

List Everlane collections. Returns normalized collections from Everlane (https://www.everlane.com). The storefront URL is fixed server-side. Valid empty result pages return 200 with an empty collections array.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageNo1-based page, defaults to 1
limitNoMaximum collections, defaults to 50 and supports up to 250
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 of behavioral disclosure. It adds valuable context: the storefront URL is fixed server-side (explaining why no URL parameter is needed) and that valid empty result pages return 200 with an empty collections array. This non-obvious response behavior helps the agent correctly interpret results. It doesn't mention error cases or rate limits, but the coverage is strong for a simple read 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?

The description is three sentences, each earning its place: the first states the action, the second identifies the source and notes the fixed URL, and the third clarifies a specific response behavior. It is compact and front-loaded with the core purpose, though the phrase 'normalized collections' is slightly vague.

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

Completeness3/5

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

For a simple list tool with two optional parameters, this is reasonably complete. There is no output schema, so the description does not detail the shape of the collection items, but it does disclose the fixed URL and empty-page behavior. It could be strengthened by describing the collection item fields, but given the tool's simplicity and full schema coverage, a 3 is fair.

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%, so the input schema fully documents both parameters (page and limit) with defaults and limits. The description adds no additional parameter-level meaning beyond what the schema provides. Baseline 3 is appropriate because the schema does the heavy lifting.

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 uses the verb 'List' with the resource 'Everlane collections', clearly identifying what the tool does and the data source. It is not a tautology and distinguishes the tool as a listing endpoint. However, it does not explicitly differentiate from siblings like everlane_pages or everlane_collection_products, so it falls just short of 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 description implies the tool is for listing collections from Everlane's fixed storefront URL, which provides context. It does not explicitly state when to use this tool versus alternatives such as everlane_collection_products, everlane_products, or everlane_pages. The lack of explicit exclusions or alternative routing makes this a minimum viable score.

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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