PAID: US$0.02 per successful autonomous x402 call, or 1 Horse Truth direct credit. Return current derived Horse Truth rankings from the already-warmed canonical model cache. Use this tool when you want the current ranked list of horses in the Horse Truth model. Use horse_snapshot or horse_compare instead for named horses.
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | Maximum number of ranked horses to return, from 1 to 500. Default 100, e.g. 20. |
Changes observed during successful MCP inspections.
Input schema / properties / limit / descriptionPrevious value: -"Maximum number of items to return."New value: +"Maximum number of ranked horses to return, from 1 to 500. Default 100, e.g. 20."Input schema / properties / limit / descriptionAdded value: +"Maximum number of items to return."Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, destructiveHint=false and a closed-world scope, so safety is covered. The description adds genuinely new behavior beyond the structured fields: the call is paid (US$0.02 per successful x402 call or 1 direct credit) and the data comes from an already-warmed canonical model cache, implying low latency and no recomputation. It stops short of describing ordering direction or result shape, so not a 5.
Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.
Is the description appropriately sized, front-loaded, and free of redundancy?
Front-loads the most decision-relevant fact (pricing) and then the purpose and routing. The third sentence largely restates the purpose sentence ('current ranked list' vs 'current derived ... rankings'), which is mild redundancy but not enough to hurt readability.
Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.
Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?
For a one-parameter read tool with no output schema, the description covers cost, data source, and alternative tools. It omits ranking order/ties semantics and any hint about the returned record shape, which are minor gaps given the simple contract.
Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.
Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?
Schema description coverage is 100% and the single 'limit' parameter is fully documented in the schema with range and default. The description adds no meaning about the limit or its interaction with the ranking set, so the baseline 3 applies.
Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.
Does the description clearly state what the tool does and how it differs from similar tools?
States a specific verb and resource ('Return current derived Horse Truth rankings') and explicitly scopes it to the current ranked list of horses in the Horse Truth model, distinguishing it from named-horse tools. An agent can identify the tool without opening the schema.
Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.
Does the description explain when to use this tool, when not to, or what alternatives exist?
Gives an explicit when-to-use ('when you want the current ranked list of horses') and names two concrete alternatives for a different need ('Use horse_snapshot or horse_compare instead for named horses'). Routing between siblings is unambiguous.
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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