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electricskateboard

Search tracked products

search_products
Read-onlyIdempotent

Finds products by name or brand across about 480 shops. Returns, for each match, the cheapest shop, how many shops carry it, our verdict on the price, and the product URL.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
brandNoBrand name, e.g. "Meepo", "Onewheel", "Exway".
limitNoHow many results (default 10, max 50).
queryYesProduct name or brand, e.g. "Meepo V5" or "Onewheel Pint".
countryNoTwo-letter country code of the shop charging the best price, e.g. "US", "CA", "DE".
vehicleNoOne of: electric-skateboard, electric-scooter, onewheel, electric-bike, skateboard.
currencyNoCurrency for max_price: USD, CAD, EUR, GBP, AUD. Defaults to USD.
max_priceNoUpper bound on the best price. Requires `currency` — we never convert, so this only filters products priced in that currency.
in_stock_onlyNoKeep only products the cheapest shop actually has in stock.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.6/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description earns credit by disclosing result semantics: cheapest shop per match, shop count, a price verdict, and the product URL. It adds no rate-limit or auth context, but it usefully describes the shape of the response for a tool with no output schema.

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, front-loaded with the core lookup behavior and followed by the return composition. Every clause carries information and there is no padding or repetition of the title.

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?

For an 8-parameter, no-output-schema search tool, the description covers the essential behavior and return shape, and the schema covers all parameters. It is largely complete, with only the sibling-disambiguation and any pagination/ordering behavior left unstated.

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 all eight parameters are already documented in the schema, including the interplay between max_price and currency. The description only restates the name/brand search dimension and adds no syntax or format detail beyond the schema, so the baseline 3 applies.

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 gives a specific verb+resource ("Finds products by name or brand") and a scope quantifier ("across about 480 shops"), which lets an agent distinguish it from a single-product lookup. It does not, however, explicitly contrast itself with siblings like product_price or where_to_buy, so it stops 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 Guidelines2/5

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

There is no when-to-use, when-not-to-use, or alternative-naming statement. With siblings such as product_price and where_to_buy present, an agent has no guidance on why it would pick search_products over them, leaving the choice to inference from name alone.

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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