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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the agent knows it is safe. The description adds valuable behavioral info: it is a read-only affiliate search, returns a 30-day price trend, facets for refinement, and direct purchase links. No contradictions 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 description is front-loaded with the core purpose and usage guidance. It is bilingual, which adds some length, but every sentence adds value. Could be slightly more concise, but overall efficient.

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 output schema exists, the description provides sufficient completeness: covers use case, filtering, return fields (title, best price, price trend, facets, URLs), and behavioral traits. No gaps remain.

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%, so the description does not need to fully explain parameters. It adds a bit of context (e.g., brand must be exact value from facets, query is optional) but not significantly beyond the schema. 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?

The description clearly states the tool finds the cheapest current price for Spielekonsolen in Germany across Amazon, eBay, and AliExpress. It specifies the resource (Spielekonsolen, price comparison) and the verb (finden / finds), distinguishing it from the sibling tool lookup_product which likely searches for product details.

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 explicitly lists when to use this tool: when a user asks for price, offer, cheap, where to buy, or a specific console name. It provides concrete triggers ('guenstig', 'wo kaufen'). It does not include explicit when-not-to-use or alternatives, but the context is clear enough.

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