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DanielTomaro13

sportsdata-mcp

openf1_session_result

Read-onlyIdempotent

Retrieve final Formula 1 session classifications, including per-driver position, laps, points, gap, and DNF/DNS/DSQ flags. Filter by session, meeting, driver, or finishing position to get precise race results.

Instructions

Final classification of a session — per-driver position, laps, points, gap, DNF/DNS/DSQ flags.

Returns: [{position, driver_number, number_of_laps, points, dnf, dns, dsq, duration, gap_to_leader, session_key}] (top-level array)

Auth: none needed.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
positionNoFilter to one finishing position.
meeting_keyNoMeeting key, or 'latest'.
session_keyYesSession key, or 'latest'.
driver_numberNoFilter to one driver.
Behavior4/5

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

Annotations already declare this as read-only, idempotent, and open-world. The description adds valuable context: the exact return shape (array of objects with named fields), the auth requirement ('none needed'), and the presence of DNF/DNS/DSQ flags, which go beyond the annotation safety profile.

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?

The description is tightly composed: one main clause, a return-type line, and an auth note. Every sentence earns its place, and the most important information (what it returns) is front-loaded.

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 read-only data fetch with rich annotations and a fully described schema, this is nearly complete. It covers purpose, return shape, and auth. It does not mention rate limits or pagination, but these are not essential given the annotations and the tool's simple output shape.

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% with clear descriptions for all four parameters, so the schema does the heavy lifting. The description contributes little beyond stating the return fields and does not add meaning to the parameters (e.g., behavior of 'latest' or filtering semantics) that isn't already in the 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 opens with 'Final classification of a session' — a specific verb+resource that clearly identifies the tool's function. It enumerates the key data (position, laps, points, DNF/DNS/DSQ flags) and distinguishes it from sibling tools like openf1_starting_grid.

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 makes it clear this is for final session results and implies you need a session_key. It does not explicitly state when not to use it or name alternatives, but the context is unambiguous enough for an agent to select it for session classification data.

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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