Describe available Catence datasets

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It explicitly marks the operation as 'Read-only,' which is a critical safety signal, and clarifies the expected output content. It does not discuss possible errors or result size, but for a metadata-listing tool this is reasonably transparent.

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?

Two sentences carry distinct, high-value information: the tool's output scope and its prerequisite. There is no filler or repetition; the most important purpose statement is front-loaded and the read-only/usage clarifiers follow compactly.

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 tool's simplicity — one required parameter, no output schema, and a data-cataloging purpose — the description covers the essential content and prerequisite. It could improve by directly addressing how this tool differs from `describe_dataset`, but for most calling scenarios the agent has enough to invoke it correctly.

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 has 0% description coverage and only documents `athleteId` with a pattern, so the description is responsible for parameter meaning. It adds that the ID comes from `list_athletes`, which is useful provenance, but it does not explain that the parameter identifies whose datasets are being described or any additional constraints. This is adequate but not rich.

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 states a specific action ('List cataloged datasets') and enumerates meaningful content dimensions: fields, units, permitted filters/groupings, providers, and time coverage. It is clear about what the tool returns, though it does not explicitly differentiate itself from the sibling `describe_dataset`, so it stops short of a 5.

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 provides a direct usage precondition: 'Requires athleteId from list_athletes.' This tells the agent when in the workflow this tool can be invoked. It does not discuss exclusions or mention alternative tools for similar metadata needs, but the provided context is clear and actionable.

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