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darshjoshi

Pitwall F1

by darshjoshi

Historical Results (1950+)

get_historical_results
Read-onlyIdempotent

Retrieve historical Formula 1 race results from 1950 onward, filtered by year, circuit, or driver, to analyze past performance and race outcomes.

Instructions

Get historical F1 race results from 1950 to present.

Args: year: Specific year (0 = current season) race: Circuit name (e.g. 'monza', 'monaco') driver: Driver ID (e.g. 'verstappen', 'hamilton')

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
raceNo
yearNo
driverNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.0.0

TDQS

B3.2/5.0
Behavior3/5

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

Annotations already declare readOnly, idempotent, non-destructive, and open-world traits, so the safety profile is covered. The description adds the useful 1950-to-present coverage range, but says nothing about result volume, pagination, or what happens when filters are combined. A 3 reflects modest added value on top of the annotations.

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?

Front-loaded purpose sentence followed by a tight parameter list, with no filler. The Args block mirrors schema ordering cleanly. It is appropriately sized for a three-parameter query tool.

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

Completeness3/5

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

An output schema exists, so return values need not be described. For a historical results query the description covers scope and parameters adequately, but the absence of any sibling differentiation against the many results/standings/history tools leaves a real decision gap for the agent.

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 0%, so the description carries the parameter burden and does partially compensate: it explains year and gives concrete examples for race ('monza', 'monaco') and driver ('verstappen', 'hamilton'), plus the 0 sentinel for current season. It does not explain what the empty-string defaults for race/driver mean (presumably all), so the compensation is incomplete.

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

Purpose4/5

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

States a specific verb and resource ('Get historical F1 race results') with a clear temporal scope (1950 to present), so an agent knows exactly what the tool returns. However, it does nothing to distinguish it from near-identical siblings like get_race_results, get_sprint_results, or get_race_winners_history.

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 when-to-use or when-not-to-use guidance. The parenthetical 'year: 0 = current season' hints that current-season data is reachable, but it never says how this differs from get_race_results, which is the most likely competing tool. The agent must guess which results tool to pick.

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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