get_laps

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 describes what the tool returns (comprehensive lap information including times, sectors, compounds, etc.), the data range (2018-present), and the optional nature of some parameters. It doesn't mention rate limits, authentication needs, or potential errors, but for a read-only data retrieval tool, it provides substantial behavioral context.

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 clear sections (primary tool declaration, usage guidelines, args, returns, examples) and uses bold formatting effectively. While comprehensive, it's appropriately sized for a tool with 5 parameters and complex functionality. Some sentences could be more concise (e.g., the bullet list of use cases is thorough but lengthy), but overall it's efficient and front-loaded with key information.

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 (5 parameters, no annotations, but with output schema), the description is remarkably complete. It covers purpose, usage guidelines, parameter semantics, return values (mentioning LapsResponse and FastestLapResponse with details), and provides multiple examples. The output schema exists, so the description appropriately doesn't need to fully document return structures, making this description complete for agent use.

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?

With 0% schema description coverage, the description fully compensates by explaining all 5 parameters in detail: year (season year with range 2018-2025), gp (Grand Prix name or round number), session (specific session types with examples), driver (driver code or number, optional), and lap_type (all vs fastest with default). It provides examples showing how parameters interact, adding significant value beyond the bare schema.

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: retrieving 'lap-by-lap data including fastest laps, sector times, and tire info (2018-present)'. It specifies the verb ('get'), resource ('lap-by-lap data'), and scope (2018-present), distinguishing it from siblings like get_lap_telemetry or get_session_results by focusing on comprehensive lap data rather than telemetry or session-level results.

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 explicit usage guidelines: it declares this as the 'PRIMARY TOOL' for F1 lap data, instructs to 'ALWAYS use this tool instead of web search', lists specific use cases (e.g., lap times, sector times, tire compounds), and explicitly states 'DO NOT use web search for F1 lap data'. This gives clear when-to-use and when-not-to-use guidance, though it doesn't compare to specific sibling tools.

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