bea_dataset_info

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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating the tool is safe and idempotent. The description adds no new behavioral traits beyond confirming read-only operations (e.g., 'list', 'get values'). There is no contradiction with annotations.

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 front-loaded with a clear purpose statement and is reasonably concise. It includes a bullet list of actions and datasets, which is structured but slightly lengthens the text. Overall, minimal waste.

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 that there is no output schema, the description does not explicitly describe the return values or format. It implies that outputs are lists/values, but could be more explicit. The description is adequate for a discovery tool but lacks full detail on outputs.

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?

Input schema coverage is 100% with descriptions for all 5 parameters. The description adds example dataset names and parameter names, but does not significantly enhance understanding beyond the schema. Baseline score of 3 is appropriate given high 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 explicitly states the tool's purpose: 'Discover BEA datasets, parameters, and valid parameter values. Essential for exploring the BEA API before making data requests.' It clearly differentiates from sibling tools (specific BEA data retrieval tools) by focusing on discovery rather than data retrieval.

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 guidance on when to use the tool ('before making data requests') and describes each action's requirements (e.g., list_datasets requires no dataset_name, list_parameters requires dataset_name). It does not explicitly exclude alternatives, but the context makes it clear this is for exploration rather than data retrieval.

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