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Surya96t

fastf1-mcp-server

compare_telemetry

Compare telemetry data between two Formula 1 drivers in the same session to analyze speed differences, time gaps, and sector performance.

Instructions

Compare telemetry between two drivers on the same session.

Data source: FastF1 Live Timing Coverage: 2018-present

Set export_path=True when the user wants the comparison data for analysis (notebook, pandas, ML, "plot where one driver gains time", "save the comparison"). Comparisons at the default 200 sample size also auto-export.

Args: year: Season year (2018+) event: Race name or round number session: Session type (R, Q, S, FP1, FP2, FP3) driver1: First driver code (e.g., "VER") driver2: Second driver code (e.g., "LEC") lap: Lap number or "fastest" — applied independently to each driver sample_size: Telemetry points per driver (default 200, max 500) export_path: If True, write the per-distance comparison array to a CSV in the configured export directory (default ./fastf1-exports/, override via FASTF1_MCP_EXPORT_DIR) and omit comparison from the response. Pass a string for a custom directory or .csv file path.

Returns: { "driver1": {"code": "VER", "lapNumber": 18, "lapTime": "1:10.123"}, "driver2": {"code": "LEC", "lapNumber": 20, "lapTime": "1:10.456"}, "comparison": [ {"distance": 0.0, "speed1": 280.0, "speed2": 275.0, "speedDelta": 5.0, "timeDelta": 0.0}, ... ], "summary": { "lapTimeDeltaSec": 0.333, "maxSpeedDelta": 8.2, "sectors": { "S1": {"driver1": "0:00:28.123", "driver2": "0:00:28.456", "deltaSec": -0.333}, "S2": {...}, "S3": {...} }, "driver1Telemetry": {"maxSpeedKph": 325.0, "brakingZones": 7, ...}, "driver2Telemetry": {"maxSpeedKph": 320.5, "brakingZones": 8, ...} } }

Example: compare_telemetry(2024, "Monaco", "Q", "VER", "LEC")

Note: timeDelta is the cumulative time gap at each distance point, computed from speed integration. Positive = driver1 is ahead. Comparison is aligned to driver1's distance axis.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
yearYes
eventYes
sessionYes
driver1Yes
driver2Yes
lapNofastest
sample_sizeNo
export_pathNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations, the description covers data source, coverage, timeDelta calculation, alignment to driver1, and export behavior. Lacks discussion of error handling or performance characteristics.

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?

Well-organized with intro, usage, parameter doc, returns, example, and note. Slightly verbose but appropriate for the complexity.

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?

Covers purpose, parameters, return structure, and includes example. Lacks error handling or data availability information, but sufficient for an experienced agent.

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 Args section provides detailed meaning, defaults, and options for all 8 parameters, including the export_path's custom path feature.

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?

Clearly states it compares telemetry between two drivers on the same session, specifies data source and coverage, and distinguishes from siblings like get_lap_telemetry.

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?

Provides explicit guidance on when to use export_path and mentions auto-export at default sample size. Could be improved by stating when NOT to use or comparing to siblings.

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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