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f1_tyre_degradation

Read-onlyIdempotent

Fit a degradation model to a Formula 1 driver's tyre compound during a session, returning slope and residual standard deviation to quantify wear rate.

Instructions

Fit a tyre degradation model for a driver + compound in a session.

Args: session_key: OpenF1 session identifier. driver_number: Driver's race number. compound: Tyre compound (SOFT, MEDIUM, HARD, INTER, WET).

Returns: data: {intercept, slope, residual_std, sample_count}. meta.estimated: true — model output, not telemetry oracle.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
compoundYesTyre compound (SOFT, MEDIUM, HARD, INTER, WET).
session_keyYesOpenF1 session identifier.
driver_numberYesDriver's race number.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
dataNo
metaNo
errorNo
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint. Description adds valuable context: 'meta.estimated: true — model output, not telemetry oracle.' This clarifies the tool returns a fitted model, not raw data.

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?

Description is concise (5 lines), well-structured with 'Args:' and 'Returns:' sections. Every sentence adds value; no fluff.

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 the tool's moderate complexity and the presence of both annotations and output schema description, the description fully explains what the tool does, its parameters, and what it returns. No gaps.

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

Parameters3/5

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

Schema description coverage is 100%, so baseline is 3. The description repeats parameter names and types but adds no new semantic detail beyond what the schema already provides.

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 uses specific verb 'Fit' and identifies resource 'tyre degradation model' with clear scope 'driver + compound in session'. It distinguishes from sibling F1 tools like f1_get_lap_times which return raw data.

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

Usage Guidelines2/5

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

No explicit guidance on when to use this tool versus alternatives. The description does not mention when not to use it or provide context for choosing among sibling tools.

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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