horse_intelligence
Return Horse Truth derived intelligence for one horse. Raw provider records are not exposed.
Input Schema
| Name | Required | Description | Default |
|---|---|---|---|
| horse | Yes |
Return Horse Truth derived intelligence for one horse. Raw provider records are not exposed.
| Name | Required | Description | Default |
|---|---|---|---|
| horse | Yes |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations, the description carries the full burden of disclosing behavior. It does state that raw provider records are not exposed, which hints at a read operation with data restriction. However, it omits other important behaviors such as authentication requirements, rate limits, side effects, or the shape of the returned intelligence. The single note is minimal and does not sufficiently inform the agent about side effects or permissions.
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?
The description is extremely concise, using only two sentences with no filler. It front-loads the core purpose and adds a relevant caveat. While it is under-specified, the structure itself is efficient and clear, earning a high score for conciseness rather than completeness.
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?
Given the tool has no output schema and no annotations, the description should explain what 'intelligence' entails and what the return value looks like. It only states that raw records are not exposed, which is a negative constraint but does not describe the positive content of the response. For a single-parameter tool, the description is incomplete for correct invocation and interpretation of results.
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?
The schema defines a single required parameter 'horse' as a string, but the description does not explain what this parameter represents (e.g., an ID, name, or alias). Schema description coverage is 0%, so the description must compensate for the missing parameter documentation. It fails to do so, leaving the agent to guess the format and meaning of 'horse'.
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?
The description clearly states the verb (Return) and resource (Horse Truth derived intelligence for one horse). It is specific about the scope (single horse) and adds a note that raw records are not exposed, which clarifies what is returned. However, it does not differentiate from sibling tools like horse_changes or horse_rankings, so the purpose is clear but not fully contextualized.
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?
The description gives no guidance on when to use this tool versus the sibling tools. It does not mention any conditions, prerequisites, or alternatives. An agent would have to infer from the name alone, which is insufficient for correct 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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