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racehooks

@racehooks/mcp

Official

Get Race Insights

get_race_insights
Read-onlyIdempotent

Retrieve post-race ML analytics for a race, including per-lap pit stop, safety car, overtake, undercut, tyre health, win probability, and championship points predictions to analyze strategy.

Instructions

Get the full post-race ML analytics bundle for a race. Includes per-driver per-lap outputs: pit stop probability, safety car probability, overtake probability, undercut probability, tyre health, cliff risk and lap prediction, fuel-corrected lap time (LTOE), win probability, expected championship points. Also includes pit stops, tyre stints, lap times, and safety-car lap list. Output depends on plan: Free receives the descriptive data plus tyre state only (compound, tyre life, tyre health); the strategic predictions require Developer or higher.

Input Schema

NameRequiredDescriptionDefault
raceIdYesRace ID slug, e.g. '2026-bahrain-r1'.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already declare readOnly, idempotent and openWorld, so the safety profile is covered. The description adds genuinely non-obvious behaviour: the response is plan-dependent, with free tiers receiving only descriptive data plus tyre state while strategic predictions require Developer or higher. Missing are cost/latency or error behaviour on invalid race IDs.

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 with the bundle summary, then the output inventory, then the plan constraint last. The long enumeration of metrics is dense but each item is substantive for a tool with no output schema; the two-part 'also includes' clause is slightly redundant but not wasteful.

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?

With no output schema, the description carries the return-value burden and does so thoroughly, listing every metric category plus the auxiliary datasets. The plan-tier caveat is essential and included; only the boundary to overlapping race/session tools remains unaddressed.

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?

Only one parameter and schema coverage is 100%, so the schema already documents raceId including the slug example. The description adds nothing about the ID format or validity, so it sits at the baseline.

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 the full post-race ML analytics bundle for a race') and enumerates the exact artefacts returned. It does not name which sibling to use instead (e.g. get_race_summary or get_session_analytics), so an agent must infer the boundary itself.

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?

Usage is implied by 'post-race' and the plan-tier note, but there is no explicit when-to-use/when-not guidance and no routing against the many adjacent race endpoints in the sibling list. The plan gating is the only conditional context offered.

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