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

With annotations already covering readOnly/openWorld/idempotent, the description goes well beyond them: refresh interval, the base-vs-reward APY split, 30-day mean, IL risk and prediction fields, the $0.003/call price with 10 free/day and x402 payment-required fallback, and error semantics (isError, errors not charged). This is unusually rich operational context.

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?

Dense and front-loaded with scope, filters and sort first, then output semantics, then pricing/errors. It is long and the pricing/error tail is somewhat run-on, but nearly every clause carries information an agent needs.

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?

Output schema exists so return shape need not be re-explained, and the description still covers data provenance, freshness, cost model, error behavior and all filtering/sorting dimensions. Nothing material is missing for correct invocation.

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 the baseline is 3, but the description adds conceptual meaning the schema lacks, e.g. that base APY is organic fees/interest while reward APY is token emissions, and what IL risk and single/multi exposure imply. That aids interpretation of the enum and filter values.

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 ('Search ~19,000 DeFi yield pools across all chains') plus the filtering and sorting axes, which cleanly separates it from siblings like chain_tvl, defi_rankings and defi_protocol. The data source (DefiLlama yields) and refresh cadence add further specificity.

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 filtering dimensions imply when the tool is useful, and it hints at a use case ('spot unsustainable spikes'), but it never states when to prefer this over sibling tools such as defi_protocol, chain_tvl or dex_volumes, nor any explicit exclusions. Usage is inferable rather than stated.

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