fastf1-mcp-server

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 key behavioral traits: data source and coverage constraints, filtering logic (excluding certain laps), minimum lap requirements, and output format. It also explains the SC/VSC filtering mechanism ('track status "1" (green flag only)'). The main gap is lack of information about performance characteristics, error conditions, or authentication requirements.

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 (purpose, data source, args, returns, example, notes) and every sentence adds value. It's appropriately sized for a tool with 6 parameters and complex filtering logic. Minor deduction because the example could be slightly more concise, but overall it's efficiently organized.

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 with filtering logic), no annotations, and the presence of an output schema, the description provides excellent completeness. It covers purpose, data constraints, parameter semantics, return format with example, and important behavioral notes about filtering logic. The output schema handles return structure details, allowing the description to focus on operational context.

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 providing detailed semantic explanations for all 6 parameters. Each parameter gets clear meaning beyond type information: 'year' is explained as 'Season year (2018+)', 'event' as 'Race name or round number', and each filtering parameter gets operational context with defaults. The description adds substantial 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 specific action ('Calculate average race pace for all drivers'), identifies the resource ('drivers'), and distinguishes from siblings by focusing on race pace analysis rather than standings, results, or telemetry. It explicitly mentions the data source (FastF1 Live Timing) and coverage period (2018-present), providing clear differentiation.

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 about when to use this tool (for calculating average race pace with specific filtering options) and implicitly distinguishes it from siblings like get_race_results_historical or get_fastest_laps by focusing on aggregated pace metrics. However, it doesn't explicitly state when NOT to use it or name specific alternatives among siblings.

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