register_dataset

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

With no annotations, the description carries the full behavioral burden. It discloses important behavior by saying file inputs are imported and by describing the returned content-derived id as pinning the exact data, but it does not address permissions, idempotency, overwrite behavior, or other side effects of registration.

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 front-loaded with the action and then gives the dataset structure in a single dense sentence. It avoids filler, though the nested brace notation is harder to parse than a more structured presentation would be.

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 whose only parameter is a complex nested object, the description supplies substantial structural detail and an output schema covers return values. However, it omits the string alternative permitted by the schema, does not clarify usage relative to siblings, and provides no annotation-level safety 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 coverage is 0%, so the description must compensate, and it does so extensively by spelling out the nested dataset object: name, sessions, subject, attributes, and inputs with artifact-id or file-path forms. The main gap is that the schema also allows a string dataset, and the description does not explain what that string represents or when to use it.

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 gives a specific verb and resource: register an experiment/dataset, and outlines the expected object shape. It does not explicitly distinguish this tool from siblings such as import_data or get_dataset, so it is clear but lacks sibling differentiation.

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 explains what the dataset structure looks like, but gives no guidance on when to use register_dataset versus import_data, get_dataset, or other siblings. The note about file inputs and import_data options is structural context, not usage guidance.

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