list_datasets

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

With no annotations provided, the description carries the behavioral burden. It states the tool lists datasets and exactly what fields are returned, and adds a critical usage rule about using keys instead of labels, which guards against misuse. However, it does not disclose potential limitations like pagination or sorting, but for a simple list tool this is adequate.

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 two sentences with no filler. It front-loads the purpose, then details the output content, and finishes with a practical tip. Every sentence earns its place.

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, no parameters, and existence of an output schema, the description covers everything an agent needs: what it lists, what fields are returned, and how to use the results with run_explore_query. Nothing essential is missing.

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 tool has zero parameters, so there is nothing to explain. The description correctly omits parameter details, and the baseline of 4 applies given no parameters exist.

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 verb 'List' and the resource 'datasets', scoped to 'the caller's identity can query'. It distinguishes itself from sibling tools like run_explore_query by being about enumeration, not query execution.

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 does not explicitly say when to use this tool vs alternatives, but by mentioning that column keys should be used in run_explore_query, it implies this is a precursor to querying. It lacks explicit exclusions or alternative conditions, so usage is implied rather than stated.

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