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find_cheaper

Find cheaper alternatives for any Ozon product by comparing its own discount offers and price-sorted search results, ranked by final payable price.

Instructions

The cheapest lots of the same thing, ranked by payable price — top limit (default 10). Looks in both places Ozon keeps them: its own «Есть дешевле или быстрее» offers for this exact product, and a price-sorted search by the card's title, which reaches the same product listed separately. Entries carry seller and delivery when they came from the offers list, and offers have no title — confirm the model with product_details() before quoting one. Raises when the base price cannot be read, rather than answering "nothing is cheaper" for a product it failed to price.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoHow many entries to return at most.
sku_or_urlYesA product SKU ("3077454533") or a full ozon.ru product URL. Variants have their own SKUs.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
baseYes
cheaperNo

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observedv1.2.1

TDQS

A4.7/5.0
Behavior5/5

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

With no annotations provided, the description carries full responsibility for behavioral disclosure. It clearly explains ranking by payable price, the two lookup sources, the caveat that offer entries have no title and need confirmation, and the important failure behavior of raising instead of falsely reporting nothing cheaper.

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?

The description is compact and front-loaded with the core behavior, followed by source detail, a caveat, and the failure mode. Every sentence adds meaningful operational information without wasted words.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given an output schema exists, the description covers the non-obvious behavioral and data-quality aspects: ranking, limit, source logic, missing titles on offers, and exception behavior. It is sufficiently complete for an agent to select and invoke the tool correctly.

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 useful context beyond the schema by explaining that sku_or_url drives both the exact product offers and a title-based search, and by restating the limit default in the operational context of ranking output.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: it finds the cheapest lots of the same product ranked by payable price. It also distinguishes itself from generic search by explaining its two sources and the exact-product focus.

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 the tool is appropriate: when finding cheaper copies of the same product, using both Ozon's offers list and title-based search. It does not explicitly name alternative sibling tools or state when not to use it, but it does provide a useful follow-up instruction to verify offers with product_details() before quoting them.

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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