get_generation_status

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

Annotations already declare readOnlyHint and idempotentHint, so safety is covered. The description adds that this is a polling operation against a previously started job, but says nothing about what progress data comes back, whether terminal states are reached, or rate/interval expectations for polling.

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?

One sentence, front-loaded with the action and resource, with zero filler. 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?

With no output schema, the description should describe what progress information is returned (state enum, percentage, completion flag) so the agent can interpret results. Combined with the undocumented dataset_id, this leaves a real gap despite adequate safety coverage from annotations.

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 single parameter has 0% schema description coverage, so the description carries the full burden. It implies dataset_id identifies the job, but it is genuinely ambiguous whether it is the dataset identifier, a job identifier returned by start_generation, or the source dataset — a meaningful risk of wrong invocation.

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?

States a specific verb (poll) and resource (dataset generation job) and ties it to the originating sibling, start_generation. That distinguishes it from get_experiment_status and get_dataset, though the description never explicitly contrasts those siblings.

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 word "poll" implies repeated invocation after start_generation, which gives implicit usage context. However, it doesn't say when to stop polling, what to do instead (e.g., cancel_generation, or get_dataset once complete), or whether polling is required at all.

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