get_race_pace

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

With no annotations, the description effectively discloses data source, coverage, and filter behavior (e.g., SC/VSC using track status '1', driver exclusion). It adds value beyond the bare parameters.

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 and front-loaded with purpose, but the Args section repeats defaults already in the schema. Still, every sentence adds value, and it is not overly verbose.

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 complexity (6 parameters, various filters) and lack of output schema, the description covers purpose, parameters, output structure, and behavioral notes comprehensively. The Returns block compensates for the missing output 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 has 0% description coverage, but the description includes an Args section that explains each parameter with defaults and meaning, fully compensating for the lack of schema descriptions.

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 'Calculate average race pace for all drivers,' specifying the verb, resource, and scope. It distinguishes from siblings like get_lap_times or get_fastest_laps by focusing on average pace and listing unique filtering options.

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 some usage context through the Note and Returns block, but lacks explicit guidance on when to use this tool versus alternatives (e.g., get_lap_times, get_stint_analysis).

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