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Surya96t

fastf1-mcp-server

get_driver_standings

Retrieve Formula 1 driver standings for any season from 1950 to present, with optional round filter to view standings after specific races.

Instructions

Get driver championship standings.

Data source: Ergast API (via FastF1) Coverage: 1950-present

Args: year: Season year after_round: Standings after specific round (default: latest)

Returns: Ordered list of drivers with: position, driver code, full name, team, points, wins

Example: get_driver_standings(2024) → [ {"position": 1, "code": "VER", "name": "Max Verstappen", "team": "Red Bull", "points": 575, "wins": 19}, ... ]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
after_roundNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior3/5

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

No annotations provided, so description must cover behavior. It reveals data source and coverage, but does not address error handling, data freshness, or potential side effects (though likely none). Adequate but not exhaustive.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise, well-structured with headings for Args, Returns, and Example. No unnecessary words, every sentence provides value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (2 params, no nested objects) and presence of an output schema, the description covers purpose, parameters, and output adequately. Lacks some behavioral details but overall complete for the context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 0%, and the description compensates with clear Args explanations ('year: Season year', 'after_round: Standings after specific round (default: latest)') and an example. Adds meaning beyond the schema's types.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states 'Get driver championship standings', specifies the data source and coverage (1950-present), and distinguishes from sibling tools like 'get_constructor_standings' and 'get_driver_info' by focusing on standings.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides parameter details and an example, making it clear when to use (for driver standings). It lacks explicit when-not-to-use or alternatives, but the context with sibling tools allows inference.

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

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