get_dataset

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

No annotations exist, so the description must carry the full burden of behavioral disclosure. It only says 'get metadata' and fails to mention whether the operation is read-only, requires specific permissions, what happens if the dataset does not exist, or what the metadata encompasses. This leaves the agent uncertain about side effects and error handling.

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 concise sentence that is easy to parse and front-loads the core purpose. It is appropriately sized for a simple getter, though it could afford a bit more context without becoming bloated.

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 simple metadata retrieval tool with an output schema present, the description provides the minimum viable purpose. However, it omits context about the optional project parameter and when this tool is preferred over siblings, making it incomplete for fully guiding an agent. Lack of annotations further limits behavioral context.

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?

Schema description coverage is 0%, and the description does not explain the purpose of the two parameters. 'project' (optional, default null) and 'dataset_name' (required) are left entirely to their names, which is insufficient for an agent to correctly construct calls, especially the optional 'project' parameter.

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 action ('Get') and the resource ('metadata for a specific dataset'). It distinguishes from siblings like list_datasets by specifying 'a specific dataset' rather than listing all, and from get_dataset_item by targeting the dataset itself, not an item.

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 list_datasets or get_dataset_item. There is no mention of prerequisites, exclusions, or preferred scenarios, so the agent is left to infer usage from the name alone.

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