dataset_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 merely says 'Get detailed information' which implies a read-only operation but does not disclose any behavioral traits such as permission requirements, error handling, response format, or whether the dataset may be modified. This is similar to the 'update_drive' example where the description implied mutation but lacked details on reversibility or permissions. The description is minimal and does not add meaningful transparency beyond what the name suggests.

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 sentence with no unnecessary words. It is front-loaded and directly communicates the action and resource. Although it is very brief, it earns its place with zero waste, aligning with the highest level of conciseness seen in the calibration example.

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 and no output schema, the description needs to provide more context to be complete. It does not specify what 'detailed information' includes, how the tool behaves (e.g., errors if dataset not found), or why to use it instead of dataset_list or query_dataset_info. The one-liner is insufficient for the agent to correctly select and invoke the tool in a broader 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?

The input schema fully covers the only parameter, 'dataset_id', with the description 'ID of the dataset'. Since schema coverage is 100%, the baseline is 3. The tool description does not add any additional meaning beyond what the schema already provides, but it also does not conflict or omit anything.

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 uses the specific verb 'Get' and identifies the resource as 'a dataset', with 'detailed information' as the object. This clearly states the tool's purpose and distinguishes it from dataset creation or upload tools. However, it does not differentiate it from sibling tools like dataset_list or query_dataset_info, which may both retrieve dataset information.

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. It is a single sentence with no mention of prerequisites, exclusions, or which scenarios call for this tool over dataset_list or query_dataset_info. The presence of sibling tools that perform similar lookup functions makes this lack of guidance a significant gap.

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