dataset_details

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

With no annotations provided, the description carries the full behavioral burden, but 'via REST API' is an implementation detail rather than behavioral disclosure. It does not state whether the operation is read-only, whether authentication is required, or what happens for an invalid ref.

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 definition is brief and front-loaded, but it is a fragment rather than a complete sentence and is under-specified. The brevity reflects missing crucial details rather than effective conciseness.

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 tool with no annotations, no output schema, and one undocumented required parameter, the description is inadequate. It omits what 'ref' means, what the metadata response contains, and how this tool differs from the near-duplicate sibling get_dataset_metadata.

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 schema has zero description coverage and the description never explains the required 'ref' parameter. An agent must guess that 'ref' identifies a dataset, with no confirmation from any source.

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 identifies the resource (dataset) and general subject (metadata), so an agent can infer it retrieves dataset metadata. However, it has no explicit verb and does not distinguish this tool from the similarly named sibling get_dataset_metadata, which appears to serve the same purpose.

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?

There is no guidance on when to use this tool instead of overlapping siblings like get_dataset_metadata, list_my_datasets, or search_datasets. The description provides no selection criteria, exclusions, or contextual triggers.

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