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

With no annotations provided, the description carries the full burden. It discloses several behavioral traits: adjustable fidelity, background enhancement, upsampling, stable endpoint with automatic model upgrades, and pricing. However, it does not mention the output format (e.g., base64 image, URL) or potential failure modes, which is a notable gap.

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 a compact paragraph that front-loads purpose and then provides model info, adjustment options, and payment details. It is efficient, though the technical FID score and model citation add slightly more detail than strictly needed for agent selection.

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?

The description covers purpose, key parameters, payment requirement, and model stability, which is good. However, with no output schema, it omits return value details (e.g., output image format or how to retrieve the result), which is essential for a tool that returns data.

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?

The schema already covers all 6 parameters with clear descriptions (100% coverage). The description adds some high-level context for fidelity ('balance between quality enhancement and identity preservation') and mentions background/upscaling, but the schema already explains each parameter in detail, so the added value is marginal.

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 opens with a specific verb+resource: 'Restore blurry, damaged, or AI-generated faces to sharp, natural quality.' This clearly distinguishes it from sibling tools like deblur_image (general deblurring) and upscale_image (general upscaling) by emphasizing face-specific restoration.

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 provides clear context for when to use the tool (face restoration, background enhancement, upscaling) and the required payment flow via create_payment. However, it does not explicitly mention when not to use it or name alternatives, so it lacks exclusions.

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