inference_create_serverless_inference

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

No annotations are provided, so the description must carry the full burden of behavioral disclosure. It states that it returns a created subscription with ID, API key, and configuration details, but does not disclose any side effects (e.g., cost implications, whether it might require billing setup) or prerequisites (e.g., authenticated user). The description is brief but indicates a creation operation, which is inherently mutating. However, it doesn't explain potential failure modes or authorization needs.

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 (one short paragraph) and includes an Args section and Returns section. It is front-loaded with the main purpose. No fluff, but the Returns section is somewhat redundant with what is already known from the output schema. Overall efficient.

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 has a single parameter, an output schema exists, and the description explains the return value. However, since no annotations are provided, the description should cover behavioral aspects like side effects or prerequisites. It does not mention any potential costs or billing implications of creating a serverless inference subscription, which could be important for an agent to decide. But for a simple create operation, the description is reasonably complete for basic usage.

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 has only one parameter 'label' with 0% schema coverage. The description provides an example label ('production-chatbot') but does not explain the semantics of the label beyond 'A descriptive label'. This does not add significant meaning beyond the schema, as the schema says it's a string. The description could have mentioned that the label must be unique or follow certain constraints, but it doesn't.

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 purpose: 'Create a new serverless inference subscription' with a specific verb 'Create' and resource 'serverless inference subscription'. It also provides a label example that disambiguates it from sibling tools like 'inference_get_serverless_inference' or 'inference_update_serverless_inference'.

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 (create a subscription) but does not explicitly state when to use this tool versus alternatives, such as 'inference_list_serverless_inference' or 'inference_update_serverless_inference'. There is no mention of when not to use it, but the context is clear enough for simple creation.

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