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Glama
Branuvg

mcp_f1_strategy

by Branuvg

get_race_state

Retrieve a lap-by-lap snapshot of the race, including each driver's position, gaps, tire compound, and tire age, to support pit-stop strategy decisions.

Instructions

Raw session snapshot at a given lap: position, gap to leader/car ahead, tire compound and tire age for every driver still classified.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
lapYes
seasonYes
circuitYes
sessionYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

C2.7/5.0
Behavior2/5

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

With no annotations, the description must carry the burden of disclosing side effects. It implies a read-only operation but never explicitly states that it does not modify data or that it is safe to call repeatedly. No mention of rate limits, authentication, or other behavioral traits.

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 concise and well-structured, conveying the essential information in two short sentences without unnecessary verbosity.

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

Completeness2/5

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

While the output schema exists (so return value details are not required), the description lacks sufficient context for correct usage: no parameter meanings, no usage differentiation, and no side-effect disclosure. The tool is simple but the description leaves too much unstated.

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

Parameters1/5

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

The schema has zero descriptions for the four parameters. The description only mentions 'given lap' but does not explain what 'circuit', 'season', or 'session' refer to (e.g., whether session is race/qualifying/practice). This leaves the agent guessing about required input semantics.

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 raw session snapshot with specific fields (position, gaps, tire compound/age). It is specific enough to understand the tool's core function, though it does not explicitly contrast with sibling tools.

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 guidance is provided on when to use this tool versus the analytical sibling tools (e.g., get_tire_degradation_curve, simulate_undercut_overcut). The implied use case (retrieving raw data) is not made explicit.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.