wolaptop.de Preisvergleich

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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint. The description adds that the operation is read-only and mentions returned data (best price, 30-day stats, offer link), which is consistent and adds value.

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?

The description is somewhat lengthy due to bilingual text (German and English), but the key information is front-loaded and each sentence adds value. Could be slightly more concise.

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 presence of an output schema and annotations, the description captures essential behavioral and usage details. It covers what the tool does, its inputs, and outputs, making it complete for a simple lookup tool.

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 schema already describes both parameters (id and url). The description adds that exactly one field must be used and explains that externalId comes from search_offers, enhancing understanding beyond schema definitions.

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 specifies the tool looks up a product by ID or Amazon URL, and distinguishes it from the sibling tool 'search_offers' which is likely a broader search. The verb 'look up' and resource 'product' are explicit.

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 states that exactly one of 'id' or 'url' must be provided, which is a clear usage rule. However, it does not explicitly say when to use this tool over the sibling 'search_offers' or mention exclusions, though the context implies it.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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

Annotations already carry readOnly/idempotent/non-destructive; the description reinforces this with 'Read-only' and adds the affiliate detail that purchase occurs at the linked merchant with unchanged price. It also discloses catalog size (several hundred products) and the availability of facets for refinement. No contradiction with annotations.

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?

The main purpose and trigger conditions are front-loaded, and the German body is information-dense. The final English summary largely duplicates the German text, adding length without new information, so it is not perfectly concise.

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?

Combined with a full output schema, read-only annotations, and a detailed description of return fields (title, best price, brand, image, trend, attributes, urls, facets), an agent has everything needed to select and invoke the tool. It could name the sibling alternative, but that gap is minor.

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 description coverage is 100%, and schema already documents default/max limit, brand values from facets.marke, and max/min price. The description only restates filtering by keyword, brand, price range, adding no new parameter-level syntax or semantics. Baseline 3 is appropriate.

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?

States a specific verb ('Findet') and exact resource scope ('Laptops zum guenstigsten aktuellen Preis in Deutschland ... ueber Amazon, eBay und AliExpress'), and lists the output payload. This is clearly a search/compare tool and distinct from sibling lookup_product, which implies a single-item lookup.

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?

Explicitly names trigger queries: 'wenn ein Nutzer nach Preis, Angebot, "guenstig", "wo kaufen" oder einem konkreten Laptop fragt.' This gives clear when-to-use guidance. It does not explicitly state when not to use it or mention lookup_product as the alternative, so it stops short of a full routing rule.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.