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

With no annotations, the description fully carries the burden of behavioral disclosure. It covers cost (44 sats per image), payment method (Bitcoin Lightning, no API key), model stability (upgrades automatically), and output format (transparent PNG). It also notes the required payment flow. This is substantial transparency for a simple image operation.

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 concise and front-loaded with the core purpose. It includes additional context on model quality, pricing, and payment prerequisites, all relevant to an agent's decision-making. Each sentence adds value, though the model benchmark could be considered non-essential; it is not verbose.

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 tool is simple, but with no output schema, the description should clarify how the transparent PNG is returned (e.g., base64 string, URL). It only says 'returning transparent PNG' without specifying the structure. The payment prerequisite is well-covered, but the lack of return-value encoding details leaves a moderate gap.

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 input schema already provides full descriptions for both parameters: paymentId and imageBase64, achieving 100% coverage. The description adds no additional parameter-level details beyond restating the payment requirement and image flexibility. With full schema coverage, the baseline of 3 is appropriate.

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 starts with a clear and specific statement: 'Remove background from any image, returning transparent PNG.' This verb-resource pair is unambiguous and differentiates it from sibling tools like remove_object or edit_image. The additional detail about handling complex edges further solidifies its purpose.

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 provides clear context for when to use the tool: any time you need background removal, especially for complex subjects like hair or glass. It also states the prerequisite of calling create_payment with toolName='remove_background'. However, it does not explicitly mention alternatives or when not to use it, only giving implied guidance.

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