get_shop_infoOeffentliche Shop-/Kontaktdaten aus den Sonderseiten (Impressum, AGB, Zahlungsbedingungen, Versand ...). Ohne 'thema' wird die Seitenliste zurueckgegeben.
| Name | Required | Description | Default |
|---|---|---|---|
| thema | No | z.B. impressum, agb, zahlungsbedingungen, versand, kontakt. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Without annotations, the description carries the burden and effectively discloses that omitting the 'thema' parameter returns a list of pages, while providing it returns specific data. This adds value beyond the input schema.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Two concise sentences front-load the purpose and conditionally explain the parameter behavior. Every word earns its place with no redundancy.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
Given the tool's low complexity (one optional parameter, no output schema), the description covers both use cases adequately. However, the response format is not described, which could be helpful.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
The input schema has 100% coverage with examples, and the description adds the key behavioral distinction for the optional parameter. However, it does not detail format or constraints beyond the schema.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
The description clearly states the tool retrieves public shop/contact data from specific special pages like imprint and terms. It distinguishes itself from sibling tools (e.g., get_guide, get_product) by targeting legal/contact info.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
The description implies the tool should be used for obtaining public shop information, but it does not explicitly state when to use it versus alternatives or provide exclusion criteria. The context is clear but lacks direct guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool targets a distinct function: inventory checks, cart creation, product search, order management, loyalty, support. No overlap among search_products, list_products, and get_product; similarly, list_orders and request_address_change are unique.
All tools follow a verb_noun pattern (e.g., check_availability, create_cart, link_account) with consistent snake_case and English verbs, even though the shop is German. No mix of conventions.
19 tools is slightly above the typical 3-15 range for a focused server, but the number is justified by the breadth of shop functionality (product browsing, orders, cart, loyalty, guides, support). Not excessive.
Covers core shopping flows: product discovery, cart creation, order tracking, and account linking. However, missing tools for cart modification (add/remove items), order cancellation/returns, and checkout. These gaps may cause agent failures.