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get_deals

Get discounted products sorted by discount percentage. Returns schema.org/Product entities with schema.org/Offer properties: price, priceCurrency, availability, originalPrice, and discountPercentage. Covers Singapore, Malaysia, Indonesia, Thailand, Vietnam, and US e-commerce. Supports currency, region (sea, us, eu, au) and country (SG, US, VN, MY, ...) filters. BUY-74597 degraded contract: when the discount-index scan cannot complete inside the user-facing timeout, this tool returns a 200-OK envelope with meta.status="degraded", meta.emptiness_reason="api_error" with meta.degraded_kind="timeout" (or "partial_timeout" / "auth_failure"), meta.confidence="low", and meta.diagnostic.timed_out_stage (typically offer_aggregation). It never returns an unqualified empty result when the cause is timeout, auth failure, upstream exception, or circuit breaker. Branch on meta.degraded === true or meta.status === "degraded".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoNumber of results (max 100, default 20)
marketNoAlias for country_code (deprecated, use country_code).
offsetNoPagination offset
regionNoFilter by region (sea, us, eu, au)
countryNoAlias for country_code (deprecated, use country_code)
currencyNoFilter by currency code (SGD, USD, MYR, VND, THB). Defaults to SGD.SGD
deliver_toNoTreat as REQUIRED for buyer-facing use: ISO-3166 country of the END USER (e.g. "SG", "US"). Without it results are not shipping-ranked and may be undeliverable. Preferred over country_code/country.
country_codeNoFilter by ISO country code. Alias: country.
min_discountNoMinimum discount percentage (default 10)

TDQS

A4.2/5.0
Behavior5/5

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

With no annotations, the description carries the full burden and handles it exceptionally. It discloses a detailed degraded contract including meta.status='degraded', degraded_kind values, meta.diagnostic.timed_out_stage, and a guarantee that it never returns an unqualified empty result for timeout, auth failure, upstream exception, or circuit breaker failures.

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 front-loaded with the core purpose and organized logically: purpose, output shape, coverage/filters, then degraded behavior. The degraded-contract section is long but earns its place because there is no output schema and the failure mode is non-obvious.

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 a 9-parameter tool with no annotations and no output schema, the description is unusually complete: it covers return entity/properties, market coverage, filters, and the degraded failure contract. It does not mention the buyer-facing deliver_to requirement in prose, and the coverage mention of Indonesia vs. the country_code enum is slightly unclear.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema coverage is 100%, so the baseline is 3. The description adds value by naming the supported market coverage and filter domains (region values sea/us/eu/au and country values SG/US/VN/MY/...), going slightly beyond the schema text. It does not deepen semantics for limit, offset, min_discount, or deliver_to, but the schema already covers those.

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 states a specific verb and resource: 'Get discounted products sorted by discount percentage,' and it specifies the return entity shape (schema.org/Product with Offer properties). It is clear, but it does not explicitly differentiate this from the sibling get_deals_v2, so it stops short of full sibling distinction.

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

Usage Guidelines4/5

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

The description gives clear context for when to use the tool, including market coverage (Singapore, Malaysia, Indonesia, Thailand, Vietnam, US) and supported filters (currency, region, country). However, it does not explicitly state when to prefer an alternative sibling tool or provide exclusion guidance.

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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TDQS

A3.6/5.0
Disambiguation1/5

Five tools have near-identical v1/v2 pairs (compare_products, find_best_price, get_deals, get_product, search_products), making it very hard for an agent to know which variant to call without parsing subtle differences like required deliver_to. Although unique tools exist, the overlap dominates the surface.

Naming Consistency5/5

All tools use a consistent snake_case verb_noun pattern such as search_products, get_deals, compare_products, and list_categories. The versioned variants consistently append _v2, giving a predictable and easy-to-infer naming convention.

Tool Count4/5

13 tools is within a reasonable scope for a product-search and comparison MCP server. However, five of the tools are versioned duplicates that add little distinct capability, making the set feel slightly padded rather than optimally concise.

Completeness4/5

The tool surface covers the core buyer journey: search, compare, best-price lookup, deals, product details, similar products, categories, and catalog ingestion. Gaps are minor, such as no delete/remove catalog operation or dedicated merchant management, but primary shopping and product-discovery tasks are well supported.