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

Beyond the readOnly/destructive annotations, it discloses real runtime behavior: newest-first ordering, that still-training entries are refreshed on read, that failed trainings appear while deleted ones do not, and that the call costs nothing. These are exactly the traits an agent needs and cannot infer from annotations.

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 tight sentences, front-loaded with purpose and scope, then the field list, then the inclusion/exclusion and cost rules. No sentence is filler.

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 and no parameters, the description needs only to convey scope, ordering, filtering rules, and cost, all of which it covers. Nothing an agent needs to call it correctly is missing.

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?

There are zero parameters, so there is nothing for the description to disambiguate; the baseline is 4. It even goes slightly beyond by describing output fields, though the output schema already carries that.

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 ('List') and resource ('this account's trained Paint Lab styles'), and the word 'trained' distinguishes it from the sibling list_paint_lab_styles that enumerates base styles. It also enumerates the exact fields returned, so an agent knows precisely what it gets.

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 scope ('this account's', 'trained') implies when it applies, but the description never names an alternative or a when-not condition (e.g. use get_paint_lab_trained_style for a single style). Usage is only implied, which is the definition of a 3.

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