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Swissgroceries MCP

search_products

Search for products across Swiss grocery chains by keyword and filter by price, size, and tags to compare offers and find the best deals.

Instructions

Search for products across configured Swiss grocery chains (Migros, Coop, Aldi, Denner, Lidl) by keyword. Supports optional filters for price, size range, and product tags (organic, vegan, budget, etc.). Returns results grouped by chain with normalised price, unit price, size, and promotion info. Use for "find organic milk under 2 CHF", "compare pasta prices", or "search for gluten-free bread".

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesSearch term in any language, e.g. "Milch", "pâtes", "Bier". At least 1 character.
chainsNoRestrict search to specific chains. Omit to search all configured chains in parallel.
storeIdsNoFilter results to products available in these store IDs (chain-specific internal IDs).
filtersNoOptional product filters applied after search.
limitNoMaximum number of results per chain (1–50). Defaults to chain-specific limit.
offsetNoSkip the first N results per chain. Use with `limit` to paginate. Default 0.
Behavior4/5

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

With no annotations, the description must disclose behavioral traits. It reveals that results are grouped by chain and include normalized price, unit price, size, and promotion info. It also implies parallel search across chains. However, it does not explicitly state read-only behavior or potential latency.

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 concise at three sentences, with the main action front-loaded. Every sentence adds useful information without redundancy. It efficiently covers the tool's scope, examples, and result structure.

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?

Given the lack of an output schema, the description adequately describes the return format (grouped by chain with price, unit price, size, promotion info). It covers key features but omits details on pagination behavior or error handling, which are partially in the schema.

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?

Although schema coverage is 100%, the description adds value by providing example queries for the 'query' parameter, clarifying that omitting 'chains' searches all, and giving concrete examples for filters (maxPrice, sizeRange). This enhances understanding beyond the schema.

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 the tool's purpose: searching for products across configured Swiss grocery chains by keyword. It lists the specific chains and mentions optional filters, making it distinct from sibling tools like get_product (single product) or find_stock (stock search).

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 provides concrete example queries ('find organic milk under 2 CHF', 'compare pasta prices') that illustrate when to use the tool. It also implies when to use it vs. siblings, but does not explicitly state exclusions or alternatives.

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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