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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable behavioral context beyond annotations: it is a 'cheap call,' it omits column schemas, and it returns a specific shape with dataset_slug and an array of table objects.

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, no filler. The key scoping statement is front-loaded, followed by a concrete example, the return shape, and the sibling alternative. Every sentence contributes distinct information.

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, single-parameter read-only list operation with no output schema, the description is complete: it gives usage context, a valid example, the exact return structure, and an explicit routing rule to get_dataset. Nothing essential is missing for correct invocation.

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 0%, so the description must compensate. It provides a concrete example value ('kden-metar-hourly') and shows dataset_slug as part of the return shape. For a single, self-describing parameter, this is sufficient practical guidance even though it does not formally define the slug format.

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 verb and resource: 'The tables in one dataset,' and clearly distinguishes it from siblings by noting it omits full column schemas and returns only lightweight fields like table ids and titles. It also names get_dataset as the alternative when columns are needed, so an agent can tell the tools apart.

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 explicitly says when to use this tool: when you only need table ids and titles, and explicitly tells the agent to 'Use get_dataset instead when you also want columns.' This is direct, actionable guidance with a clear alternative.

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