kie_upscale

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

No annotations are provided, so the description carries full burden. It does not disclose whether the upscaling is synchronous or asynchronous, whether API credentials are needed, what happens to the file, or any error conditions. This makes the tool's behavior opaque beyond the basic 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 a single sentence of nine words, which is appropriately sized for a simple operation. It is front-loaded with the verb and resource, containing zero filler.

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?

With no output schema, no annotations, and four parameters, the description is too sparse. It fails to explain return values, execution semantics (e.g., whether the tool writes to output_dir or returns a URL), or any side effects. This is insufficient for a tool that likely calls an external AI service.

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 fully describes all four parameters with defaults and descriptions, so the description adds no additional parameter semantics. Per the rubric, baseline is 3 when schema coverage is high, and this is exactly that case.

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 uses a specific verb ('Upscale') and resource ('an image') with a clear subject ('AI models via kie.ai'), which distinguishes it from sibling generation tools. It clearly states the core function, earning a 5.

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 implies usage for image upscaling but provides no explicit guidance on when to use this tool versus alternatives like kie_generate_image, nor any exclusion criteria. It is a bare statement of function, leaving the agent to infer appropriate conditions.

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