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 the tool's behavior by specifying the data source (Ergast API via FastF1), coverage range (1950-present), and return format with example data, though it doesn't mention potential limitations like rate limits 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 (Args, Returns, Example, Note), front-loaded with the core purpose, and every sentence adds value without redundancy. The example is particularly helpful for understanding output format.

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 simplicity (one parameter), presence of an output schema (though not shown here), and the description's comprehensive coverage of purpose, usage, parameters, returns with example, and behavioral context, this description is complete and provides all necessary information for an agent to use the tool effectively.

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 input schema has 0% description coverage, but the description compensates well by explaining the single parameter 'year' as 'Season year (1950-present)', adding meaningful context about valid range that isn't in the schema. Since there's only one parameter, this provides good semantic understanding.

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 with a specific verb ('List') and resource ('all events in a season'), and explicitly distinguishes it from its sibling tool 'get_schedule' by calling it a 'minimal version' and noting its utility for discovering event names for other tools.

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 guidance on when to use this tool versus alternatives, stating it's 'useful for discovering valid event names to pass to other tools' and comparing it to 'get_schedule' as a minimal version, which helps the agent understand its specific use case.

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