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BuySignal Deals Search

Search BuySignal Deals

search_deals
Read-onlyIdempotent

Search BuySignal's live UK/Canada deal database across 20+ retailers.

BuySignal aggregates real-time price drops from major UK retailers (Currys, Argos, John Lewis, Very, JD Sports, Foot Locker, Boots, The Fragrance Shop, and more) and Canadian retailers (Best Buy Canada, Canada Computers, Sport Chek, and more).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNomax number of results to return (default 20, max 50).
queryNooptional text to match against the deal title (case-insensitive substring match).
marketNo"uk" or "ca" (Canada). Defaults to "uk".uk
categoryNo"tech", "fashion", or "fragrance". Omit to search all categories in that market.
max_priceNoonly return deals at or below this sale price (GBP for uk, CAD for ca).
min_discountNoonly return deals with at least this discount percentage off the original price.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description contributes that results are 'live'/'real-time' price drops, which is genuine behavioral context, but says nothing about pagination, result freshness, rate limits, or empty-result behavior.

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?

Two sentences, front-loaded with the action and database name, with the second sentence supplying coverage detail rather than filler. The retailer enumeration is somewhat long but does earn its place by conveying breadth of coverage.

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?

With an output schema present and 100% schema coverage across six optional parameters, the description only needs to establish what corpus is searched and across which markets, which it does. The missing piece is when-to-use guidance, which keeps it from a 5.

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 (limit, query, market, category, max_price, min_discount) is already documented in the schema. The description adds no syntax or semantics beyond that, 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?

States a specific verb (Search) and resource (deal database) and names the covered markets and retailers, so an agent knows exactly what corpus is being queried. It falls short of 5 only because there are no siblings to differentiate from, so the ranking/routing value of a 5 isn't achievable.

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?

The description never says when to reach for this tool, what user intents it serves, or what it is not for (e.g. no exclusions, no alternative tools, no guidance on combining filters). Only the data coverage is described, so usage must be entirely inferred.

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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