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Glama

smartscout_product_search

Search Amazon products by ASIN, title, brand, category, price, sales, rating, or reviews, then sort results by sales, price, rank, or reviews.

Instructions

Search for products by ASIN, title, brand, or other criteria

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
asinNoASIN to search for (exact match)
brandNoBrand name to filter by
limitNoNumber of results to return (max 1000)
titleNoProduct title to search for (partial match)
orderByNoColumn to order byMONTHLYUNITSSOLD
categoryNoCategory to filter by
maxPriceNoMaximum price filter
minPriceNoMinimum price filter
minSalesNoMinimum monthly sales filter
minRatingNoMinimum rating filter (1-5)
minReviewsNoMinimum review count filter
subcategoryNoSubcategory to filter by

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

C2.9/5.0
Behavior2/5

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

No annotations are provided, so the description carries the full behavioral burden, and it discloses almost nothing: no auth requirements, no pagination behavior, no default/max result handling (the limit cap of 1000 lives only in the schema), and no note that filters combine as AND. For a 12-parameter query tool with zero annotation coverage, this is a significant gap.

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?

A single short sentence with no filler, appropriately front-loaded with the verb and resource. It is efficient but borders on under-specified for a 12-parameter tool.

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?

With 12 optional parameters, no annotations, and no output schema, the description is too thin: it does not explain the result shape, ordering defaults, or how the numerous filters compose. An agent could call it, but not confidently or correctly in edge cases.

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 every parameter is already documented in the schema, making the baseline 3. The description restates only three of the twelve parameters (ASIN, title, brand) and adds no semantics beyond what the schema provides, e.g. how price, sales, and rating filters interact.

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 clear verb+resource ('Search for products') and enumerates the primary search keys (ASIN, title, brand). However, it does not distinguish this tool from close siblings such as smartscout_product_details, smartscout_top_products, or smartscout_product_keywords, so the agent cannot tell from the text alone which product tool to pick.

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

Usage Guidelines2/5

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

No when-to-use guidance, no prerequisites, and no mention of alternatives among the many sibling search/product tools. The trailing 'or other criteria' is vague and gives the agent no routing signal.

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