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Horse Truth Machine Intelligence

horse_intelligence

Read-only

PAID: US$0.02 per successful autonomous x402 call, or 1 Horse Truth direct credit. Return derived intelligence for one horse. Raw provider records are not exposed. Use this tool when you need the full derived state of one horse, including race history and every read. Use horse_snapshot instead for a short summary, horse_explanation for the reasons only, and horse_changes for what changed.

Input Schema

NameRequiredDescriptionDefault
horseYesHorse name as printed in an Australian form guide, e.g. 'Chance With Wolves'. Case and country suffixes like (NZ) are ignored. If unsure of the exact name, call resolve_horse first.

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changed
    • addedInput schema / properties / horse / description
      Added value: +"Horse name as printed in an Australian form guide, e.g. 'Chance With Wolves'. Case and country suffixes like (NZ) are ignored. If unsure of the exact name, call resolve_horse first."
  2. First observed

TDQS

A4.5/5.0
Behavior4/5

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

Annotations already cover read-only/no-destruction safety. The description adds non-obvious behavioral context: pricing (US$0.02 per x402 call or 1 credit) and that raw provider records are withheld. It doesn't state return shape or failure behavior, but the pricing disclosure is meaningful context beyond 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 pricing and purpose, followed by scoping and alternatives. Every sentence earns its place, though the pricing and credit phrasing adds some density.

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?

Covers purpose, routing, cost, and data exposure for a single-param read tool with annotations. No output schema exists, so a brief return-value note would help, but the essential call information is present.

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

Parameters4/5

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

Schema coverage is 100%, so the schema already documents the horse param fully. The description adds routing value by pointing to resolve_horse when the name is uncertain, which slightly exceeds baseline but doesn't add syntax detail beyond 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?

Specific verb+resource: returns 'derived intelligence' for one horse, with scope defined (race history, every read). Explicitly distinguishes from siblings horse_snapshot, horse_explanation, and horse_changes, so an agent can route correctly without reading schemas.

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

Usage Guidelines5/5

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

States when to use ('when you need the full derived state of one horse') and names three specific alternatives with their differing purposes. Nothing left to inference for tool selection.

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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