describe_dataset

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 lists some output content but does not explicitly state that the operation is read-only, whether it has side effects, what permissions are needed, or how warnings are triggered.

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 a single tight fragment with no filler; every listed item is meaningful and the main output categories are front-loaded. It could be improved by making it a complete sentence and clarifying 'weight choice', but it is efficient.

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 simple schema with one required parameter and no output schema, listing the five output categories is a reasonable starting point. However, the description omits usage guidance, parameter semantics, and any behavioral caveats, so it is not fully complete for an agent deciding when and how to invoke it.

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 only parameter, dataset_id, has no description in the schema and coverage is 0%. The tool description adds no explanation of how to obtain or format dataset_id, although the parameter name is self-explanatory enough to reduce the risk of misuse.

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 states the tool's output categories—columns, non-missing counts, weight choice, derived-variable definitions, and warnings—so an agent can infer it produces a dataset-level metadata summary. It lacks an explicit verb and does not distinguish itself from siblings like describe_variable, but the resource and contents are clear.

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 no guidance on when to use this tool versus alternatives such as describe_variable or search_variables. There are no exclusions, prerequisites, or context cues beyond the tool's name.

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