inference_get_inference_usage

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

No annotations are provided, so the description carries the behavioral disclosure burden. It clearly describes the return data and units, but it does not explicitly state that the operation is read-only, whether any permissions are needed, or how the usage data is aggregated.

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 well-structured with a concise purpose statement followed by Args and Returns sections. The bullet list of returned fields is relevant and informative without excessive padding.

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 simple get-usage tool, the description adequately covers what the tool does, what parameter is required, and what output to expect. It lacks guidance on edge cases or differentiation from sibling analytics tools, but it is otherwise complete.

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 has 0% description coverage and only defines subscription_id as a string. The description adds meaning by stating it is 'The inference subscription ID or label', which helps an agent supply an acceptable value. It could include format examples, but for a single-parameter tool this is adequate compensation.

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 states a specific verb and resource: 'Get usage statistics for a serverless inference subscription.' It enumerates the categories of usage returned, which makes it clear and distinguishes it from related inference tools like inference_get_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 this tool is for retrieving usage statistics for a serverless inference subscription, but it does not explicitly say when to choose it over alternatives such as inference_analyze_inference_usage or inference_monitor_inference_performance. No exclusions or selection criteria are provided.

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