list_offersAktuell reduzierte Artikel (aktive Sonderpreise), nach Beliebtheit sortiert. Preise sind bereits die Angebotspreise.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Max. Artikel (1-30, Default 12). |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description provides key behavioral context: it lists reduced items, sorted by popularity, and explicitly states that prices are already the offer prices. No contradictions.
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-loaded with the core purpose and sort order, no wasted words.
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 simple schema and no output schema, the description covers purpose, sort order, and price nature. Could mention that it only shows active offers, but it does say 'aktuelle'.
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?
Schema coverage is 100% and the schema already describes the limit parameter well (range and default). The description adds no extra detail about the parameter, so baseline score applies.
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 lists currently reduced items (active special prices) sorted by popularity, which distinguishes it from sibling tools like list_bestsellers or search_products.
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 usage for current offers but lacks explicit when-to-use or when-not-to-use guidance compared to alternatives like list_bestsellers.
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.