get_dataset_info

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves 'detailed metadata and download links', which is helpful, but it doesn't mention important behavioral traits such as whether this is a read-only operation, potential rate limits, authentication needs, or error handling. For a tool with no annotation coverage, this leaves significant gaps in understanding its behavior.

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 well-structured and concise, with a clear purpose statement followed by brief sections for 'Args' and 'Returns'. Every sentence adds value without unnecessary elaboration, making it easy to scan and understand 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?

Given that there's an output schema (which handles return values), the description doesn't need to detail outputs. However, for a tool with no annotations and a simple input schema, the description adequately covers the basics but could be more complete by addressing behavioral aspects like read-only nature or error conditions, which are important for safe and effective use.

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 description adds meaningful context for the single parameter 'dataset_id' by specifying it should come 'from search results', which clarifies its source and usage beyond the schema's basic type definition. Since there's only one parameter and schema description coverage is 0%, this additional semantic information is valuable and compensates well for the lack of schema descriptions.

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 tool's purpose with a specific verb ('Get') and resource ('detailed information about a specific Data.gov dataset'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'query_datagov' or 'search_datasets', which might have overlapping functionality.

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 implies usage by mentioning 'dataset_id (from search results)', suggesting it should be used after searching for datasets. However, it doesn't provide explicit guidance on when to use this tool versus alternatives like 'query_datagov' or 'search_datasets', leaving some ambiguity about the best context for its application.

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