get_usage

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns usage statistics, which implies it's a read-only operation, but doesn't specify behavioral traits like authentication needs, rate limits, or whether it's real-time data. The description adds basic context but lacks details on how the tool behaves in practice, such as update frequency or error handling.

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 appropriately sized and front-loaded, starting with the core purpose in the first sentence. The bullet points for returns are structured and add clarity without redundancy. However, the second part could be slightly more integrated into the flow, but overall, it's efficient with minimal waste.

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 the tool's low complexity (0 parameters, no output schema, no annotations), the description is somewhat complete but has gaps. It explains what the tool does and what it returns, which is adequate for a simple read operation. However, without annotations or output schema, it could benefit from more context on usage scenarios or limitations, making it just minimally viable.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description doesn't add parameter details beyond the schema, but since there are no parameters, it appropriately focuses on the output. This meets the baseline for tools with no parameters, as it doesn't mislead or omit necessary information.

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 purpose: 'Get current API usage and token statistics.' It specifies the verb ('Get') and resource ('API usage and token statistics'), making the function immediately understandable. However, it doesn't explicitly differentiate from sibling tools like 'get_job_status' or 'batch_scrape,' which prevents 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. It doesn't mention context, prerequisites, or exclusions, such as whether it's for monitoring usage limits or checking after API calls. With sibling tools like 'scrape_url' or 'get_job_status,' there's no indication of how this tool fits into the workflow, leaving usage unclear.

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