nar_favorite_performance

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

No annotations provided, so description must carry the burden. It mentions analyzing and checking win rates, but does not disclose any behavioral traits: no mention of read-only nature, data source, update frequency, or limitations. For a tool with no annotations, this is insufficient.

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?

Two concise sentences, front-loaded with purpose. No unnecessary words. However, the brevity sacrifices completeness; a slightly longer description could add needed parameter context without becoming verbose.

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 complexity (4 parameters, no output schema, no annotations), the description is far from complete. It does not explain input parameters, return format, or filtering capabilities. The agent would lack context to invoke the tool correctly for most use cases.

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 description does not explain any of the four parameters. The term 'ninki' (popularity) is hinted but not defined; venue, year_from, and distance are not mentioned at all. The description adds no meaningful information beyond what the schema provides.

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?

Description clearly states it analyzes performance by popularity for NAR local horse racing, listing example venues (Oi, Funabashi, etc.). It distinguishes from the sibling 'favorite_performance' which likely covers JRA central racing, but does not explicitly differentiate.

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 versus alternatives like 'favorite_performance'. The description implies NAR local context, but does not state when to choose this over other racing analysis tools.

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