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

Annotations only cover the safety profile (not read-only, not destructive). The description adds substantial behavior beyond them: it consumes the monthly generation allowance, returns immediately with status submitting/queued, takes a few minutes, is idempotent per quoteId (never charges twice), and refunds the allowance on failure.

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?

Every sentence earns its place: action, cost, immediate return, next step, latency, idempotency, and refund are each stated once and front-loaded. No filler or repetition.

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 an output schema present, return shape need not be detailed, yet the description still explains the immediate response status and the polling loop. Billing, retry, and failure behavior are all covered, so an agent has everything needed to call and follow up correctly.

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%, so the baseline is 3, but the description adds meaningful semantics the schema does not: the quoteId is single-use and reusing it returns the same style rather than starting a new training. That is real guidance beyond the raw field definitions.

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 (train) and resource (Paint Lab style) and the precondition (from a quote). It is clearly distinguishable from quote_paint_lab_style_training, which only prices the training, and from get_paint_lab_trained_style, which is the poll target.

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?

Explicitly names the follow-up flow: poll get_paint_lab_trained_style until status is ready or failed, and states retry semantics for the same quoteId. It does not spell out when NOT to use this tool (e.g. versus list_paint_lab_trained_styles), so it falls short of a full 5.

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