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Surya96t

fastf1-mcp-server

get_stint_analysis

Analyze tire stint data for Formula 1 races, providing per-driver stint details, pace calculations, and strategy summaries. Export to CSV for data analysis.

Instructions

Analyze tire stints for a race.

Data source: FastF1 Live Timing Coverage: 2018-present

Set export_path=True when the user mentions data analysis, notebooks, pandas, ML, "save as CSV", "export the strategy data", or any downstream processing — the full per-stint array is written to CSV. Large responses (>50 stints, typical for full-grid races) also auto-export.

Args: year: Season year (2018+) event: Race name or round number driver: Optional driver code to filter (default: all drivers) export_path: If True, write the full per-stint array to a CSV in the configured export directory (default ./fastf1-exports/, override via FASTF1_MCP_EXPORT_DIR) and omit stints from the response. Pass a string for a custom directory or .csv file path. The server also auto-exports when the stint count exceeds FASTF1_MCP_AUTO_EXPORT_ROWS (default 50).

Returns: Default (no export): { "summary": {...}, "stints": [{"driver": "LEC", "stintNumber": 1, ...}, ...] }

With export_path:
{
    "summary": {...},
    "exportPath": "/abs/path/to/get_stint_analysis_<...>.csv",
    "rowCount": 45
}

Note: Only accurate laps are included in pace calculations. Stint numbers match FastF1's internal stint counter. Phantom lap-1 stints (single-lap entries with no recorded lap time, paired with the lap-1 pit-stop artifact) are filtered out. The summary.strategies array gives the 1-stop / 2-stop / compound sequence per driver in a compact form.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
eventYes
driverNo
export_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior5/5

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

With no annotations, the description fully discloses data source, coverage, auto-export behavior, phantom stint filtering, and accurate lap inclusion. It explains the side effects of export_path and directory configuration, leaving no ambiguity.

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

Conciseness4/5

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

The description is well-structured with sections (purpose, data source, params, returns, notes) and front-loaded with key info. While thorough, it is slightly verbose but still concise for the detail provided.

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

Completeness5/5

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

Given no annotations and an output schema (partially described), the description covers all necessary aspects: parameters, return structure, edge cases (auto-export, phantom laps), and usage context. It is complete for the tool's complexity.

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

Parameters5/5

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

Despite 0% schema description coverage, the description richly documents each parameter: year range, event flexibility, driver default, and export_path's boolean/string variants with detailed behavior. It adds significant value beyond the bare schema.

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 'Analyze tire stints for a race,' using a specific verb and resource. It distinguishes this tool from siblings like get_race_pace and get_lap_times by focusing on stint-level analysis.

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 explicit guidance on when to set export_path, including user intents like data analysis or large responses. However, it does not explicitly state when to prefer this tool over alternatives, though the purpose clarity implies it.

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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