get_dataset_meta_v1_datasets__provider___dataset__meta_get

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

No annotations are provided, so the description carries the full burden. It discloses it is a public GET request and returns metadata about schema, views, and query capabilities. However, it lacks details on error handling, authentication, or side effects. Since it is a read-only operation, the description is adequate but not rich.

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 extremely concise: two sentences that efficiently convey the endpoint type, public status, what it returns, and how to use it. No redundant information.

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 absence of an output schema, the description partially compensates by mentioning what metadata is returned (schema, views, query capabilities). However, it does not describe the response structure or format, leaving some ambiguity for an agent.

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 input schema has two string parameters (provider, dataset) with 0% description coverage. The tool description does not explain the meaning or format of these parameters beyond the URL path pattern. This is insufficient for an agent to know how to provide valid values.

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 it gets dataset metadata without data, listing specific return values (schema, views, query capabilities). It distinguishes itself from sibling tools that fetch actual data (e.g., get_dataset_by_path) or specific components (e.g., get_dataset_columns), making the purpose unmistakable.

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?

Explicitly says to use this endpoint to understand dataset structure before fetching data, providing clear context. However, it does not explicitly state when not to use it or mention alternatives, though the usage hint is strong.

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