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

No annotations are provided, so the description carries the full burden. It describes the tool as returning aggregated data facets and states the default for 'in_stock_only'. While it doesn't explicitly say it is read-only, the context makes it clear. It could mention that no modifications occur.

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?

Three sentences that are front-loaded with purpose, followed by usage guidance and a default note. 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?

With no output schema, the description provides a thorough list of returned facets (producers, countries, regions, etc.) and their counts, which is sufficient for an agent to understand the output. It could detail the response structure more, but it is overall complete.

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 adds limited value beyond the schema. It reinforces the default for 'in_stock_only' and implicitly mentions locale when referring to 'in CHF', but does not add new parameter details.

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 provides an 'aggregated map of the ARVI catalog' with specific facets like producers, countries, regions, categories, etc. It differentiates itself from sibling tools by explicitly advising to call it first for broad or vague requests.

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 gives explicit when-to-use ('broad or vague', 'something as a gift') and when-to-skip ('user already named a specific wine or producer') instructions, and explains how the output can inform subsequent searches.

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