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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive), and the description adds genuine return-behavior context: providers the bench does not measure arrive in `missing`, and below-floor providers return rank null and must not be reported as losses. That is non-obvious and useful beyond the structured fields.

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 core purpose, then usage, then edge-case handling in short paragraphs. The examples and missing/rank-null notes each earn their place; the description is a touch long but stays focused.

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?

With no output schema, the description compensates by explaining the shape of results (rank, value, success rate) and the two ambiguous edge cases (missing providers, null rank). An agent can call and interpret this correctly without further information.

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 100%, so every parameter (including tier, chain, region, benchmark, providers) is fully documented in the schema itself. The description adds the recommendation to source the benchmark slug from search_benchmarks but no syntax beyond what the schema provides, so 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 precise verb and resource ('puts two or more named providers side by side on one benchmark') and enumerates the returned fields (rank, measured value, success rate). It is clearly separable from siblings like recommend_provider, which the 'user names the candidates themselves' framing implicitly contrasts against.

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 concrete when-to-use conditions with user-phrasing examples ('Alchemy or QuickNode?') and tells the agent to call search_benchmarks first for the slug. It stops short of explicitly naming recommend_provider as the alternative for unspecified candidates.

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