get_dataset_info

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

With no annotations provided, the description carries full burden for behavioral disclosure. It effectively describes what the tool returns ('comprehensive metadata including title, description, organization...'), its role in a workflow, and that it provides 'detailed information' and 'formatted text'. However, it doesn't mention potential limitations like rate limits, authentication requirements, or error conditions.

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 front-loaded with the core purpose, followed by return details, usage guidance, workflow example, and parameter explanation. Every sentence adds value without redundancy. The bullet-point workflow is particularly efficient for conveying sequencing.

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 moderate complexity (single parameter, read-only operation), the description provides complete context. With an output schema present, it doesn't need to detail return values. It covers purpose, usage sequencing, parameter semantics, and behavioral expectations adequately for this type of metadata retrieval tool.

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 beyond the schema's 0% coverage. It explains that dataset_id is 'obtained from search_datasets', clarifying the parameter's origin and relationship to sibling tools. While it doesn't specify format constraints, it provides practical usage guidance that compensates for the schema's lack of description.

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 specific verb ('Get detailed information') and resource ('about a specific dataset'). It distinguishes from siblings like search_datasets (which finds datasets) and list_dataset_resources (which lists files within datasets) by focusing on comprehensive metadata retrieval for a single identified dataset.

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 ('after finding a dataset with search_datasets') and outlines a complete workflow with alternatives (search_datasets → get_dataset_info → list_dataset_resources). It clearly positions this tool in the sequence and distinguishes it from related operations.

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