upscale_image

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

No annotations provided, so the description carries full burden. It discloses the workflow building, local GPU execution, and asynchronous return (prompt_id immediately, asset_id later). It does not detail potential side effects like GPU memory usage or concurrency limits, which would improve transparency.

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 single paragraph that efficiently conveys necessary information without superfluous words. It could be slightly more structured with bullet points, but it remains concise and readable.

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 no output schema, the description adequately explains the asynchronous return values. It covers prerequisites, workflow construction, and error handling. The information is sufficient for an agent to understand the tool's operation and expected results.

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 coverage is 100%, but the description adds meaningful context: explains the image prerequisite, model auto-selection, and scale default. This goes beyond the schema's basic type/description, providing actionable guidance.

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 tool's action ('Upscale an image with an ESRGAN super-resolution model') and identifies it as the high-level entry point. It distinguishes itself from related tools by focusing on upscaling, though it does not explicitly differentiate from all siblings like 'convert_image'.

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 prerequisites: upload the source image first or stage prior output, and ensures an upscale model is available. It mentions error handling for missing models. However, it does not explicitly state when NOT to use this tool or suggest alternatives.

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