Skip to main content
Glama
3vgen

market-screening

by 3vgen

search_products

Search products across configured Russian stores by query, returning prices, unit prices, stock, and promos so you can compare comparable items and find the cheapest basket.

Instructions

Search a product in the configured stores.

query: what to look for, in Russian, e.g. "молоко 2.5%", "куриное филе". stores: optional list of store keys from list_stores (default: all). Returns per store a list of products: price in rubles, old_price if on promo, unit_price per kg / l / pcs (compare by this), stock, badges, url. Search is fuzzy: results can include unrelated items (e.g. oat drink for "молоко").

Input Schema

NameRequiredDescriptionDefault
limitNo
queryYes
storesNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations, the description carries the full behavioral burden, and it does well: it discloses fuzzy matching that can return unrelated items, and describes returned fields such as price in rubles, old_price during promo, unit_price for comparison, stock, badges, and url. It omits limit behavior, rate limits, and any auth/permission context.

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 front-loaded with purpose, then labeled parameter notes, return shape, and the important fuzzy-search caveat. It is dense but efficient, with no filler sentences.

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 search tool with no output schema and no annotations, it supplies substantial context: query language, store scoping, return fields, and fuzzy behavior. It is not fully complete because limit semantics and any pagination or permission behavior are absent.

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 0%, so the description must compensate. It explains query semantics (Russian, examples) and stores semantics (optional store keys from list_stores, default all), but it does not document the limit parameter at all, leaving one of three parameters unexplained.

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 ('product') with scope ('configured stores'). It references list_stores only as the source of store keys, and does not explicitly contrast itself with optimize_basket or any other alternative.

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

Usage Guidelines3/5

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

Gives useful usage context: query should be in Russian with examples, and stores is optional with default all, sourced from list_stores. However, it does not say when to use this tool versus optimize_basket, nor give any when-not-to-use guidance.

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

Deploy Server

Other Tools