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Crawlora MCP

chewy_products

Read-only

A batch of up to 20 Chewy products' lightweight summaries (price, rating, stock, images) in one call. part_numbers is a comma-separated list of Chewy part numbers, e.g. "52448,767758" -- the same value chewy_product returns as part_number/parent_part_number, and chewy_category/chewy_search return as products[].part_number. An unrecognized part number is omitted from products and listed in not_found rather than failing the whole call.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
part_numbersYesRequired. Comma-separated Chewy part numbers, up to 20 per request, e.g. 52448,767758. This is the same value chewy_product returns as part_number/parent_part_number, and chewy_category/chewy_search return as products[].part_number.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataYesThe tool result payload (shape varies per tool; see each tool's docs resource).

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.7/5.0
Behavior4/5

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

Beyond the readOnlyHint/openWorldHint annotations, the description discloses two meaningful behaviors: the hard batch cap of 20 and partial-failure semantics where unrecognized part numbers are omitted from products and reported in not_found instead of failing the call. This is useful operational context not present in the structured fields.

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?

Front-loads what the tool returns and the batch limit, then covers the parameter and the not_found behavior. The middle clause duplicating the schema's part-number provenance is mildly redundant but the passage is still tight and front-loaded.

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?

An output schema exists, so return values need not be enumerated, and the description still adds the important partial-failure behavior. Batch limit, input format, and failure handling are all covered, leaving only minor gaps (no explicit sibling routing).

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%, and the description's explanation of part_numbers (comma-separated, example, provenance) is essentially a restatement of the schema's own parameter description. It adds no format or edge-case detail beyond what the schema already provides, so the baseline 3 is appropriate.

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?

States a specific action and resource: batch retrieval of up to 20 lightweight Chewy product summaries in one call. It names related siblings (chewy_product, chewy_category, chewy_search) as the source of part numbers, implying its batch role, but does not explicitly contrast itself as the multi-lookup alternative to single-product chewy_product.

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?

Usage is implied by 'up to 20 ... in one call' and the provenance of part_numbers, so an agent can infer it is for multi-product lookups. However, there is no explicit when-to-use vs chewy_product or chewy_variants guidance, and no exclusion conditions.

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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