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

Beyond the readOnly/openWorld annotations, it discloses the paid-call model ($0.002 USDC per successful call via x402 on Base, Solana or Arc) and that failed calls are not charged, which is critical pre-invocation context. It also warns that 'Small pools can show very high APR', flagging a data-quality pitfall the agent would otherwise misread as signal.

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?

One dense paragraph, front-loaded with the payload fields before caveats and pricing. Every sentence carries information, though the pricing clause is long and could be tightened.

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 only two optional parameters, an output schema present, and safety hints in annotations, the description covers everything an agent needs: scope, defaults, sort/limit behavior, exclusions, data-quality caveat, and the payment requirement.

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 description coverage is 100%, so both parameters (chain, limit) are already documented with defaults and ranges. The description adds the Ethereum default and the 1-50 bound, but that largely restates the schema rather than adding new semantics.

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 definition names the exact resource (Curve Finance gauges for a single chain) and enumerates the returned fields — CRV emission APR range, inflation rate per second, working supply, pool name and addresses. It also states the sort order and row cap, and explicitly excludes relative gauge weights and bribe yields, which separates it from the Curve pools sibling tool.

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?

It gives clear context (single chain, default Ethereum, sorted by CRV APR, top 1-50) and negative scoping ('Relative gauge weights and bribe yields are not in this source'), which tells an agent when this dataset is the wrong choice. It stops short of naming a concrete alternative sibling such as finance_curve_finance_pools for pool-level data.

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