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

The description goes far beyond simple annotations by detailing critical system behaviors: cost implications ('five times the cheapest look's per-image price'), required workflow change (re-quote with `estimate_only`), and strict output formatting (max 3, markdown images, never dump the list).

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 very long and dense. While it could benefit from structural formatting (like bullet points) to improve readability, every sentence in the text provides necessary, unique information that would be missing from structured fields alone.

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?

Given the complexity—involving unique error codes (503), significant cost changes, and specific UI presentation requirements—the description is maximally complete. It leaves virtually no ambiguity for the AI agent.

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?

Since the input schema has zero parameters (0% coverage applies), the description cannot add semantic meaning beyond the baseline score. The comprehensive coverage means the description's ability to help with parameters is irrelevant here.

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 provides a highly specific definition, distinguishing 'styles' as 'named looks (a character, a rendering treatment, an art direction)' for image-story videos. It is far more specific than a generic image generation tool.

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?

It offers explicit conditions for use: call it when the user asks what looks exist or wants a consistent stylised world. It also implicitly guides usage by contrasting the expensive styles with the 'ordinary photorealistic look' default.

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