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

Annotations already declare readOnlyHint, idempotentHint, and destructiveHint, so the safety profile is covered. The description adds useful behavioral context beyond annotations: the search spans candidates not yet queryable and returns materialization state, which helps the agent predict results without assuming all matches are query-ready.

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 wasted words. It front-loads the core purpose, then adds return behavior and the key alternative, making it easy for an agent to parse quickly.

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 read-only search tool with no required parameters and no output schema, the description provides everything needed: purpose, scope, return content, and the alternative when query-ready data is required. The annotation set covers safety, so nothing critical 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 input schema covers all three parameters with meaningful descriptions, so the description does not need to repeat parameter details. The description adds no extra parameter semantics, which is acceptable given 100% schema coverage.

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 a specific action ('find datasets') on a specific resource ('all discovered official sources'), and clarifies the unique scope by including candidates not yet queryable. It also names what the tool returns ('catalog matches and materialization state'), distinguishing it from list_imported_datasets without needing to open the schema.

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 names the sibling tool list_imported_datasets and gives the exact condition for choosing it instead ('when only query-ready data is acceptable'). This directly tells an agent when to use this tool versus an alternative, leaving no ambiguity.

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