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DanielTomaro13

sportsdata-mcp

jolpicaf1_races

Read-onlyIdempotent

Retrieve Formula 1 race calendar for any season. Get race dates, circuits, and session times for each round, including practice, qualifying, and sprint sessions.

Instructions

A season's race calendar with dates, circuits and (from 2021) each session's date/time.

Returns: {MRData:{RaceTable:{season, Races:[{season, round, raceName, date, time, url, Circuit:{circuitId, circuitName, Location}, FirstPractice, Qualifying, Sprint}]}}} — round is what the result tools take

Example: 2024 calendar {"season": "2024", "format": "json"}

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPage size (max 100).
formatNoLeave as json.json
seasonYesSeason year, or 'current'. Required — part of the URL path.
Behavior4/5

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

Annotations already cover read-only, idempotent, and open-world hints. The description adds that no authentication is needed and specifies the exact return structure, which is useful. It also notes data availability from 2021 for session times, providing extra context beyond 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?

The description is front-loaded with the core purpose and includes a compact return structure and example. The return schema is somewhat verbose but adds value in the absence of an output schema. No redundant sentences.

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?

For a simple list tool with good annotations and full schema coverage, the description is complete: it states the purpose, shows the output shape, gives a concrete example, and notes authentication. Minor gaps like pagination behavior are not critical given the tool's simplicity.

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 coverage is 100% for all three parameters. The description does not add meaningful parameter details beyond the schema, as the example merely repeats the season and format values. The baseline of 3 applies because the schema fully documents each parameter.

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?

The description clearly states it returns a season's race calendar with dates, circuits, and session times. This distinguishes it from sibling tools like jolpicaf1_results and jolpicaf1_qualifying, though it lacks an explicit verb like 'list' or 'get'.

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

Usage Guidelines3/5

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

The example and the note that 'round is what the result tools take' imply this is a precursor to result/qualifying/sprint tools, but there is no explicit statement about when to use this tool versus alternatives. The usage context is implied rather than directly stated.

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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