upscale_image

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

With no annotations provided, the description carries full burden. It discloses the algorithm (Real-ESRGAN), model version (ICCV 2021), performance metric (PSNR 32.73dB), optional face enhancement, pricing (5 sats), payment method (Bitcoin Lightning), and that the endpoint is 'stable' with automatic model upgrades. It does not detail error handling or async behavior, but the disclosure is substantial for an API tool.

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 five sentences, each adding distinct value: purpose, technical credibility, differentiation from interpolation, optional feature, stability, pricing, and prerequisite. There is no fluff; every sentence earns its place. The structure front-loads the core action and then provides essential details.

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 lacks explicit mention of the output format (e.g., base64 image) or whether the operation is synchronous/asynchronous. Given no output schema, the agent must infer the return type. While the tool's behavior is well-described, the missing output details reduce completeness for a tool with moderate complexity and no output schema.

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?

Input schema has 100% coverage with descriptions for all 4 parameters. The description adds context (e.g., 'optional face enhancement' for face_enhance, '2x or 4x' for scale, and payment context for paymentId). However, it largely mirrors the schema information; the added value is moderate. Thus a baseline 3 is appropriate given high schema coverage.

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 clearly states the primary function: 'Upscale images 2x or 4x with neural super-resolution'. It specifies the resource (images), verb (upscale), and scope (2x or 4x), and distinguishes from 'interpolation' and other image operations. Among siblings like colorize_image or deblur_image, the purpose is distinct and unmistakable.

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 includes explicit prerequisite guidance: 'Requires create_payment with toolName="upscale_image"'. It also explains the payment model and no signup needed. However, it does not explicitly compare to alternative tools (e.g., when to use upscaling vs. other image enhancements), though the context of 'neural super-resolution recovering real detail' implies it is for low-resolution images.

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