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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so the safety profile is fully covered by structured data. The description adds content-level context (it surfaces a run 'held waiting for a confirmation' and a dashboard_url), but says nothing about permissions, scope limits, or behavior beyond what annotations provide. With annotations carrying the safety burden, this is adequate but not rich.

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 purpose and usage routing are front-loaded in the first two sentences, and the return-field enumeration is compact and skimmable. It is dense but every clause carries information; the example object is the only mildly redundant element.

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?

There is no output schema, so the description must carry the return contract — and it does so explicitly, listing dataset fields, nested table fields, latest_run, held_run and dashboard_url. Combined with annotations covering safety and a clearly stated usage trigger, an agent has everything needed to call and interpret this tool.

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 single parameter carries no schema description, so the description is the only source of parameter meaning. It offers only an example invocation shape ({"dataset_id": "…"}) which restates the parameter name without explaining format, where to obtain the ID, or its relationship to siblings like list_my_datasets. It partially compensates for the coverage gap but does not close 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 states a specific verb and resource ('One workspace dataset in build terms') and enumerates exactly what is returned: name, description, status, tables with build/promotion/live version state, latest run, held run. It explicitly differentiates itself from the sibling get_dataset ('the public get_dataset, which reads the published catalog'). An agent can route between the two without opening either schema.

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?

It gives an explicit usage condition — 'the tool to call after a run finishes to see what it produced' — and names the alternative tool it should not be confused with. Both when-to-use and the sibling distinction are stated outright rather than left to inference.

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