get_resource_info

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes what the tool returns (comprehensive metadata including format, size, MIME type, URL, dataset information, and Tabular API availability status) and its role in determining subsequent actions. However, it doesn't mention potential limitations like rate limits or authentication requirements.

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 with clear sections for purpose, usage guidelines, workflow, arguments, and returns. Every sentence adds value, though it could be slightly more concise by integrating the workflow into the usage guidelines rather than as a separate section.

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 complexity (single parameter but with important decision-making role), no annotations, and the presence of an output schema, the description is complete. It explains the tool's purpose, usage context, parameter semantics, return value implications, and relationship to sibling tools, providing everything needed for an agent to use it effectively.

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?

With 0% schema description coverage for the single parameter, the description compensates by explaining the semantics of resource_id: 'The ID of the resource to get information about (obtained from list_dataset_resources)'. This provides crucial context about where to obtain the parameter value, though it doesn't specify format constraints or validation rules.

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 specific action ('Get detailed information about a specific resource (file)') and distinguishes it from siblings by specifying it returns comprehensive metadata and checks Tabular API availability. It explicitly differentiates from query_resource_data and download_and_parse_resource by explaining its role in determining which of those tools to use.

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 explicit guidance on when to use this tool vs alternatives, stating 'Use this tool to determine which data querying tool to use' and listing specific conditions for using query_resource_data or download_and_parse_resource. It also provides a typical workflow showing its position in a sequence with list_dataset_resources.

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