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

The annotations already establish that this is a safe, read-only, idempotent operation. The description adds useful behavioral context by explaining the data source scope, daily computation, and the specific return contents including latest value, changes over 1 week / 1 month / 3 months, institution and quote counts, and daily history. It does not discuss authentication, rate limits, or pagination, which keeps it from a 5.

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 front-loaded with the core capability and return contents, then closes with practical example queries. Every sentence contributes useful information without 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?

Although there is no output schema, the description explains the return values in sufficient detail: latest rate, change over multiple time windows, institution and quote counts, and daily history. Combined with fully documented parameters and read-only annotations, an agent has enough context to 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 input schema already documents all three parameters, including examples for keys and the national-default behavior for state. The description reinforces that the tool works at national or state level and mentions APY/APR distinctions, but it does not add parameter-level syntax or constraints beyond what the schema provides.

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 specific resource (national or state average rates), the metrics involved (APY for deposits, APR for loans), and how they are computed (daily from every published rate across 8,000+ banks and credit unions). This clearly distinguishes the tool from rate-search or best-rate siblings, even without naming them explicitly.

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 concrete example use cases such as 'what are CD rates doing', 'average mortgage rate in Texas', and 'are savings rates falling', which makes the intended context clear. It does not explicitly name when not to use it or point to sibling alternatives like get_best_rates, so it falls short of a full 5.

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