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

No annotations provided. The description indicates it retrieves data (schema and relationship metadata), implying a read-only operation. However, it does not explicitly state that it has no side effects or disclose any behavioral constraints beyond the basic get operation.

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, focused sentence of 14 words. It is front-loaded with the verb and resource, with no unnecessary words. Every word earns its place.

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 a single parameter and no output schema, the description adequately conveys what the tool returns (schema and relationship metadata). It could be slightly more complete by mentioning that it requires an existing dataset, but the parameter description hints at prerequisites.

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 coverage is 100% for the single parameter. The description adds context by noting that the dataset_id comes from connect_data or list_data, which is helpful beyond the type declaration. This adds value over the schema alone.

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 ('saved dataset plus its schema and relationship metadata'). It distinguishes from sibling tools like get_dataset_status (status only) and get_data_summary (summary info).

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 implies when to use: when you need schema and relationship metadata for a dataset. The parameter description specifies that the ID comes from connect_data or list_data, providing context. No explicit alternatives or exclusions, but clear enough.

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