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

Beyond the readOnlyHint annotation, the description discloses return shape, units ('apyPct is a percent'), averaging behavior, sampling-interval widening, and the caveat that the series is not comparable to instantaneous rates. This gives the agent a clear mental model of what the data means and how it behaves.

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?

The description is dense but every sentence earns its place: purpose, return format, sampling semantics, prerequisite, and a practical comparison use case. It is front-loaded with the core definition and avoids filler or redundancy.

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 covers the return format and units. It explains version-specific parameter sourcing, the sampling behavior, and the relationship to get_reserve_details. Combined with the 100%-covered input schema, an agent has everything needed to select and invoke the tool correctly.

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 the baseline is 3. The description adds value beyond the schema by explaining how to obtain parameter values ('Use get_markets first for the reserveId (v4) or market+token (v3)') and by tying the window parameter to sampling intervals. It doesn't describe every parameter, but the schema already covers those details.

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 opens with a specific verb and resource: 'Historical supply or borrow APY for a reserve over time, on v3 or v4.' It clearly identifies what data is returned, distinguishes itself from get_reserve_details by contrasting historical averages with instantaneous rates, and is unambiguous about scope (supply/borrow, reserve, v3/v4).

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 description explicitly tells the agent when to use this tool vs alternatives: 'so a series is not directly comparable to the instantaneous rate from get_reserve_details' names the alternative and the exclusion. It also gives prerequisite usage ('Use get_markets first') and a concrete decision scenario ('When comparing v3 against v4 for the same asset... read the history on both sides').

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