get_qualifying_sessions

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

With no annotations provided, the description carries the full burden. It discloses that the tool returns segmented lap data and specifies default behavior ('all' returns all segments), but lacks details on error handling, data freshness, rate limits, or authentication needs. It adequately describes core behavior but misses operational traits.

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: the first sentence states the purpose, followed by structured sections for Args, Returns, and Examples. Every sentence earns its place with no wasted words, making it easy to scan and understand.

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, no annotations, and an output schema (implied by 'Returns' section), the description is mostly complete. It covers purpose, parameters, returns, and examples, but could benefit from mentioning limitations (e.g., year range enforcement) or error cases to be fully comprehensive.

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 0%, so the description must compensate fully. It adds significant meaning beyond the schema: explains 'year' as 'Season year (2018+)', 'gp' as 'Grand Prix name or round', and 'segment' with allowed values and default behavior. This provides complete parameter semantics not in the 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: 'Split qualifying into Q1, Q2, Q3 segments with lap data for each.' It specifies the verb ('split'), resource ('qualifying'), and output structure ('segments with lap data'), distinguishing it from siblings like get_laps or get_session_results which handle different data types.

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 usage through examples and parameter explanations, showing when to use specific segment values. However, it does not explicitly state when to use this tool versus alternatives like get_laps or get_session_results, which might overlap in functionality for qualifying data.

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