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

Annotations already cover readOnlyHint, idempotentHint and destructiveHint=false, lowering the bar, yet the description adds useful state-dependent return detail: running returns stage and elapsed time, done returns dataset_id, verification, tables and certificate. It omits polling frequency or rate-limit behavior, which would complete the picture.

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?

Three telegraphic sentences, front-loaded with the core purpose and then the state-specific returns. Every sentence carries information; nothing is padded.

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 and no annotation-level return info, the description does the heavy lifting by describing what comes back in each state. It is nearly complete, missing only polling/rate guidance and explicit job_id provenance.

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% and the single job_id parameter is undescribed in the schema, so the description must compensate. It does so only indirectly, implying job_id identifies a job produced by start_generation, but gives no format or sourcing detail.

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 resource (a start_generation job) and what it reports ('Where a start_generation job is'), with the return shape spelled out per state. It also anchors itself to the start_generation sibling, so an agent can distinguish it from generate_dataset 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?

Implicitly establishes the polling pattern after start_generation and clarifies the two states (running vs done), noting that the done-case result matches generate_dataset. It never states an explicit 'use this when' or a 'do not call if' exclusion, so guidance is clear but not fully prescriptive.

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