fixfind.at – local offers in Austria

Produkte in Shops suchen

search_products

Read-onlyIdempotent

Search products that can be bought online from Austrian businesses using fixfind Shop (shops embedded in the merchants' own websites: farm shops, food, crafts, garden, pet supplies ...). Product data is German, so search with German words (e.g. "Honig", "Kürbiskernöl", "Teichfilter"); all words must match. Prices are gross in EUR incl. VAT ("from" = cheapest variant). Returns summaries with the product url; use get_product for description, variants, shipping and payment. Buying happens on the merchant's website: give the user the product url.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "search_products"
  }
}

Input Schema

Name	Required	Description
`limit`	No	Number of results to return (1-25).
`query`	No	German search words, e.g. "Waldhonig". Optional – without it all products are listed.
`offset`	No	For paging through results.
`max_price`	No	Maximum price in EUR. Optional.

Schema Changelog

Changes observed during successful MCP inspections.

Changed1 schema field changedNov 5, 2026
- addedInput schema / properties / limit / description
```
Added value: +"Number of results to return (1-25)."
```
AddedNov 4, 2026

TDQS

A4.6/5.0

Behavior5/5

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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds genuinely useful traits beyond them: the corpus is German-only, matching is AND across all terms, prices are gross EUR incl. VAT with 'from' meaning cheapest variant, and results are summaries pointing to merchant-hosted purchase. That is exactly the kind of context annotations cannot convey.

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?

Purpose is front-loaded in the first clause, followed by language, price, and return-value context in a logical order with no filler sentences. It is dense — parentheses and semicolons pack multiple facts per sentence — but nothing is redundant.

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?

With no output schema, the description correctly fills the gap by explaining that results are summaries containing the product url, and that full detail requires get_product. Language, matching, currency, and the checkout handoff are all covered, so an agent has everything needed to call and act on results.

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 schema already documents each parameter's type and range. The description still adds meaning the schema lacks: query terms must all match and must be German, and max_price is implicitly gross EUR incl. VAT, which affects how the agent phrases price filters.

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?

States a specific verb and resource (search products buyable online from Austrian businesses via fixfind Shop) and immediately scopes the domain with examples (farm shops, food, crafts, garden, pet supplies). It distinguishes itself from get_product by noting it returns summaries only, so an agent can separate the two without opening schemas.

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?

Gives clear when-to-use context (search in German, all words must match) and explicitly routes deeper detail work to get_product, plus tells the agent to hand the product url to the user for purchasing. The one gap is that the sibling search_offers and get_catalog_overview are never mentioned, so the choice between product search and offer search is left implicit.

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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