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

With annotations already indicating this is not read-only and not destructive, the description adds valuable context: it 'saves the quote but does not spend or generate' and produces a 'short-lived' quote. This clarifies the side-effect boundary beyond what the annotations alone convey, though it does not cover rate limits or auth requirements.

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 description is four dense sentences, with the trigger condition front-loaded and the side-effect boundary stated immediately. Every sentence contributes distinct operational guidance, with 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?

For a complex tool with no output schema, the description covers the key decision boundary, side effects, and a critical parameter pitfall. However, it does not explain the shape of the returned quote, how validation failures are communicated, or explicitly name get_model_details as the prerequisite source for the selected mode's live details, leaving some operational gaps.

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 only 13%, so the description must compensate, but it only provides two parameter-specific rules: optional fields should be sent as null when not required, and video duration must be settings.durationSec, never settings.duration. It offers no guidance on references, outputCount, schemaVersion, or the meaning of the required parameters, leaving a significant semantic gap.

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 names a specific verb (prepare/validate + quote) and resource (a MaxVideoAI generation), lists the supported workflows, and clearly distinguishes itself from confirm_generation by stating it 'does not spend or generate.' This lets an agent understand the tool's role without opening the 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?

The description explicitly states when to use the tool ('when the user has selected an image model or a supported video workflow... needs validation plus an exact short-lived quote') and gives a clear when-not ('Do not use it as confirmation or skip the selected mode's live model details'). It does not explicitly name the alternative sibling tool, such as confirm_generation, so it falls just short of full alternative routing.

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