List teams

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

Annotations already cover read-only, idempotent, non-destructive behavior. The description adds meaningful behavioral detail beyond that: it states the response shape, documents pagination via limit/offset, mentions that offset is converted to a page number, and explains the response_format choices. This gives the agent a solid model of what will happen.

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 well-structured with a concise summary, explicit argument documentation, return shape, and an example. It is slightly repetitive with the input schema, but the structured format makes key details easy to parse without being bloated.

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?

For a simple, read-only, parameterless-required tool, the description is complete: it explains what is returned, the JSON shape, default values, format options, and a sample invocation. Since there is no output schema, including the return shape in the description is especially valuable.

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%, so the schema already documents all three parameters. The description still adds value by clarifying the offset behavior ('converted to a page number') and showing a concrete example with no arguments. This is a modest but real contribution beyond the schema.

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 uses a specific verb and resource: 'List every team on this Umami account, with member and website counts.' It clearly communicates the scope and the included aggregate data, and it is easy to distinguish from sibling tools like umami_list_websites and umami_list_users.

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 establishes clear context: it is for enumerating teams in the account and even provides a natural-language example ('What teams do we have set up?'). It does not explicitly name alternative tools or state when not to use it, but the purpose is specific enough that an agent can infer appropriate usage.

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