favorite_performance

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

No annotations provided, and the description only mentions performance analysis and filtering. It does not disclose output format, data scope, or behavior of filters (e.g., exact match vs. range).

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?

Short and front-loaded with the main purpose, but lacks detail. Every sentence is necessary but not sufficient for full understanding.

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 no annotations, no output schema, and 5 parameters with zero schema coverage, the description is incomplete. Agent cannot determine how to set filter parameters or interpret 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?

Schema coverage is 0%, and the description does not explain individual parameters. For example, 'ninki' (popularity rank) and 'year_from' are not described; only generic filtering terms are used.

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 it analyzes horse performance by popularity rank, with filtering options. However, it does not explicitly differentiate from sibling tools like nar_favorite_performance, though naming suggests context.

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?

No guidance on when to use this tool vs. alternatives, nor when not to use it. Sibling tools exist (e.g., nar_favorite_performance) but no differentiation is provided.

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