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

The annotations already declare the tool as read-only, idempotent, and non-destructive, so the description does not need to repeat that. It adds some useful context by noting the scope of the 16 stadiums in the US, Mexico, and Canada and the fields city, capacity, and matches. Still, it does not describe filter semantics when both parameters are passed or how invalid values are handled.

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 a single, compact sentence that front-loads the core subject, then provides filtering instructions. Every phrase adds useful information: the 16 venues, the countries involved, the relevant fields, and the optional filters. There is no unnecessary repetition or filler.

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 that this is a read-only venue query tool with no required parameters and no output schema, the description covers the important return content: city, capacity, and matches per venue. It is probably enough for an agent to decide whether and how to call the tool. Minor gaps remain around exact output shape and filtering edge cases, but the overall context is adequate.

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 includes only `city` and `venue` without descriptions, so the description adds value by saying these are filters. However, it stops short of explaining accepted value formats, whether the filters are exclusive or combinable, or whether partial names are valid. This is enough to imply usage but not enough to fully compensate for the lack of schema documentation.

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 identifies the resource as World Cup host stadiums and says the data includes city, capacity, and each venue's matches. It distinguishes this tool from siblings like worldcup_teams and worldcup_matches by focusing on venues. However, it lacks an explicit operative verb such as 'lists' or 'returns,' so it stops short of the highest clarity standard.

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 tells the user to pass `city` or `venue` to filter, which gives practical guidance for using the filter parameters. It does not explicitly compare this tool to sibling tools or state when to prefer it over worldcup_matches, worldcup_schedule, or worldcup_teams. Thus usage context is present but alternatives are not addressed.

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