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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the bar is lower. The description still adds real behavioral context: the computation is simple-interest, it compares against the highest-yielding liquid tokenized treasury, it returns arithmetic and assumptions only, and it gives no recommendation.

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 sentences, zero filler, with the computation stated first and the output disclaimer second. 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?

For a 4-parameter computational read tool with no output schema and full annotation coverage, the description is sufficient: it explains the inputs' meaning, the method, and the character of the result. It could say slightly more about the returned arithmetic structure, but nothing essential to correct invocation is missing.

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% with defaults documented for all four parameters, so the baseline is 3. The description reinforces currentApyPercent and horizon and hints at the liquidity floor via 'highest-yielding liquid', but adds no format or default detail beyond the schema, and never mentions amountUsd.

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 states a precise verb and computation: 'computes the simple-interest difference versus the highest-yielding liquid tokenized treasury over a horizon.' That clearly separates it from listing siblings like list_rwa_yields or stablecoin_yield_summary, which enumerate data rather than compute a comparison.

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 a concrete trigger scenario ('an APY the user currently earns, e.g. a bank savings rate') and a scope exclusion ('does not recommend'), which tells the agent when the tool is appropriate. It stops short of naming an alternative tool or an explicit when-not-to-use condition, so it is clear context without routing.

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