cursor-usage

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 effectively communicates this is a read operation ('Get') with filtering capabilities, but doesn't mention pagination behavior (implied by page/pageSize parameters), rate limits, authentication requirements, or what happens when no filters are applied. It adds some context but leaves significant behavioral aspects unspecified.

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 perfectly concise with two sentences: the first states the core purpose and key data fields, the second specifies filtering capabilities. Every word earns its place with zero waste, and information is front-loaded appropriately.

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 moderate complexity (5 parameters, no output schema, no annotations), the description provides adequate but incomplete coverage. It clearly explains what data is retrieved and basic filtering, but doesn't address pagination behavior, response format, error conditions, or how unfiltered queries behave. For a tool with no output schema, more detail about return values would be helpful.

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?

Schema description coverage is 100%, so the schema already fully documents all 5 parameters. The description mentions filtering by 'user email and date range' which aligns with the email, startDate, and endDate parameters, but doesn't add meaningful semantic context beyond what the schema provides. The baseline score of 3 is appropriate when the schema does the heavy lifting.

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 specific verb ('Get') and resource ('granular per-request usage events'), listing key data fields (model, token counts, costs, chargeable status). It distinguishes from siblings like get_daily_usage or get_model_usage by emphasizing per-request granularity rather than aggregated views.

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 clear context for when to use this tool ('Supports filtering by user email and date range'), indicating it's for detailed event-level analysis. However, it doesn't explicitly state when NOT to use it or name specific alternatives among the many sibling tools, missing full comparative guidance.

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