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Glama

Search products

search_products
Read-only

Search the canonical product catalog by free text (Hebrew or English), brand, category, or exact GTIN, and answer 'how much is X' for a SINGLE item. Also matches chain listing names. Send city or address and every hit comes back priced: fromPrice is the lowest it goes for at any storefront delivering there, so quote it as 'from ₪X across N storefronts' (pricedAtStorefronts) and never as one national price — there is no such thing here. pricedAtStorefronts=1 is one shop's price, not a market rate. normalizedUnitPrice is that same money per 100g/100ml/piece: compare on it, NOT on fromPrice, because a smaller pack is cheaper to buy and usually dearer per gram. Results come back cheapest per unit first. fromPrice is the ordinary price, never a loyalty-club or coupon rate. Without a location nothing can be priced and the price fields are absent. For a whole shopping list call optimize_delivery ONCE with query items — never price lines one by one here, and never add these prices up: they come from different storefronts and each carries its own delivery fee. After optimize_delivery priced the wrong product, call suggest_similar_products with the shopper's Hebrew words and the rejected product_id, then call optimize_delivery again with that product_id. Returns canonical products (not per-chain detail); call get_product for listings.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cityNoCity name in Hebrew or English (also accepts CBS locality codes). Aliases resolve to one place — e.g. 'הרצליה', 'Herzliya', and '6400' are the same filter. May be combined with location as a disambiguation hint.
gtinNoExact GTIN/barcode to look up.
nearNo'lat,lng' string, e.g. '32.078,34.774', to find stores near a point.
brandNoFilter by brand name, partial match.
limitNoMax results, default 20.
queryNoFree text search, Hebrew or English, e.g. 'חלב תנובה' or 'olive oil'.
categoryNoFilter by internal category slug (l1 or l2), e.g. 'dairy'.
locationNoFree-text neighborhood or address in Israel, e.g. 'נווה עמל, הרצליה'. Resolved to coordinates via cached Nominatim. Do not combine with near.
store_idNoOptional store UUID to prefer locally stocked products.
radius_kmNoSearch radius in km around the resolved point. Defaults to 10km when near or location is set. Ignored without a point.
in_stock_onlyNoWhen location is set, return only products with a local price. Default false.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed4 schema fields changed
    • addedInput schema / properties / brand / maxLength
      Added value: +100
    • addedInput schema / properties / category / maxLength
      Added value: +100
    • addedInput schema / properties / gtin / maxLength
      Added value: +64
    • addedInput schema / properties / query / maxLength
      Added value: +200
  2. Changed2 schema fields changed
    • addedInput schema / properties / city / maxLength
      Added value: +100
    • addedInput schema / properties / near / maxLength
      Added value: +100
  3. First observed

TDQS

A4.8/5.0
Behavior5/5

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

Even though annotations indicate read-only and non-destructive behavior, the description adds extensive behavioral context: without location prices are absent, fromPrice is not a national price, pricedAtStorefronts=1 indicates a single store, and prices exclude loyalty discounts. It also explains that results are sorted by cheapest unit price first, going beyond what annotations provide.

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 long but information-dense, covering many critical behavioral nuances. It front-loads the main purpose and pricing rule, then packs in workflow guidance. While every sentence earns its place, the length may make it slightly less skimmable, but the structure is logical and no fluff.

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 the tool's complexity (11 parameters, pricing semantics, location dependence, cross-store considerations), the description is remarkably complete. It covers how to quote prices, how to compare unit prices, and when to use alternatives. The absence of an output schema is compensated by describing key output fields (pricedAtStorefronts, normalizedUnitPrice) and their interpretation.

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% and descriptions in the schema are quite detailed (e.g., location resolution, aliases, radius_km defaults). The description adds critical meaning to the city/location/price interaction (without location no pricing), and clarifies how fromPrice and normalizedUnitPrice should be used, which enhances parameter understanding beyond schema alone.

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 clearly states that the tool searches the canonical product catalog by free text, brand, category, or GTIN and answers 'how much is X' for a single item. It distinguishes itself from sibling tools like get_product (which returns listings) and optimize_delivery (for whole lists), and explains its unique pricing behavior.

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

Usage Guidelines5/5

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

Provides explicit when-to-use guidance: for single-item price queries, and explicitly says not to use for a whole shopping list (use optimize_delivery instead). It also gives a specific workflow for handling wrong pricing via suggest_similar_products followed by optimize_delivery again, and warns against comparing on fromPrice or summing prices.

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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