post-skybox-upscale360-inferences

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions 'trigger the upscaling,' implying a processing or mutation operation, but fails to detail critical aspects like permissions required, rate limits, side effects, or what the output entails (e.g., a job ID, asset, or error handling). This leaves significant gaps for safe and effective use.

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, efficient sentence that directly states the tool's purpose without unnecessary words. It is front-loaded and wastes no space, making it easy to parse quickly.

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?

For a complex tool with 15 parameters, no annotations, and no output schema, the description is inadequate. It doesn't explain the behavioral context, output format, or usage scenarios, leaving the agent with insufficient information to operate the tool effectively despite the detailed input 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?

The schema description coverage is high at 87%, meaning most parameters are documented in the schema itself. The description adds no additional parameter semantics beyond what the schema provides, such as explaining interactions between parameters like 'styleImages' and 'styleFidelity.' Given the high coverage, a baseline score of 3 is appropriate, as the description doesn't compensate but also doesn't detract.

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 action ('Trigger the upscaling') and resource ('an image matching the 360 skyboxes specific geometry'), making the purpose understandable. However, it doesn't explicitly differentiate from sibling tools like 'post-upscale-inferences' or 'post-skybox-base360-inferences', which might handle similar operations, so it falls short of a perfect score.

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 no guidance on when to use this tool versus alternatives, such as other upscaling or skybox-related tools in the sibling list. It lacks context about prerequisites, typical use cases, or exclusions, leaving the agent with minimal direction.

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