get_speed_trap_data

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

No annotations are provided, so the description carries full burden. It thoroughly discloses data sources, coverage, fallback logic (from results to laps when columns are empty), and defines all returned fields. This is highly transparent.

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 sections: intro, data source, args list, returns with JSON example, and a note. Every sentence adds value; no fluff or redundancy. Length is appropriate for the complexity.

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 presence of an output schema (JSON example effectively serves that role) and detailed behavioral notes, the description covers all necessary aspects: what it does, parameters, return structure, data sources, and edge cases (fallback). No gaps identified.

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?

Input schema describes parameters but none have descriptions (0% coverage). The description compensates by listing each parameter with context: year (2018+), event (race name or round number), session (R, Q, etc.). An example is provided, but additional guidance on valid string formats for event would improve clarity.

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 'Get speed trap and top-speed data for all drivers in a session', which is a specific verb+resource combination. It distinguishes itself from sibling tools like get_lap_times or get_sector_times by focusing on speed trap and top-speed data.

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 context about data source (FastF1 Live Timing), coverage (2018-present), and includes an example call. It does not explicitly state when to use or when not to use, but the detail is sufficient for most use cases.

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