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 adds useful context about the data source (Ergast API via FastF1) and coverage (1958-present), which helps the agent understand the tool's scope and limitations. However, it doesn't mention performance characteristics, rate limits, authentication needs, or error conditions that would be important for a data retrieval tool.

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 and appropriately sized. It begins with the core purpose, adds context about data source and coverage, then clearly documents parameters and return values in separate sections. Every sentence earns its place, and the information is front-loaded with the most important details first.

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 (2 parameters, data retrieval), no annotations, but with an output schema implied by the 'Returns' section, the description is reasonably complete. It covers purpose, data context, parameters, and return format. The main gap is the lack of behavioral details like performance, errors, or usage constraints that would be helpful despite the output schema covering return values.

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 schema description coverage is 0%, but the description compensates well by explaining both parameters in the 'Args' section. It clarifies that 'year' is the season year and 'after_round' is for standings after a specific round with a default of latest. This adds meaningful semantics beyond what the bare schema provides, though it doesn't specify format constraints or valid ranges.

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: 'Get constructor championship standings.' It specifies the resource (constructor championship standings) and verb (get), but doesn't explicitly distinguish it from its sibling 'get_driver_standings' beyond the resource name difference. The data source and coverage information add useful context but don't directly enhance purpose 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 implied usage context through the data source and coverage information, suggesting this is for historical F1 constructor standings. However, it doesn't explicitly state when to use this tool versus alternatives like 'get_driver_standings' or other standings-related tools, nor does it provide any exclusions or prerequisites for usage.

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