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

Annotations already declare readOnly, idempotent, openWorld, and non-destructive behavior. The description adds useful context beyond annotations: results are 'so far' (time-bound), tied to the 'latest' hike, one source per bank, and each row carries source type and observation dates. No contradiction with annotations.

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 dense sentences front-load the primary result and list the returned fields without filler. Every sentence contributes either scope, measurement semantics, or row-level details.

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?

The tool has only one optional parameter, an output schema is present, and annotations cover safety and side-effect profile. The description adds the needed row semantics and source-uniqueness detail, so nothing critical 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% and already documents the single optional parameter, including the id format and default behavior when omitted. The top-level description only restates the optional institution filter, adding no new parameter meaning beyond the schema, so the baseline of 3 applies.

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 uses a specific verb ('Return') and a precise resource: pass-through of the latest Federal Reserve rate hike for tracked savings accounts. It enumerates the computed fields and distinguishes this from sibling tools like get_bank_gap or get_top_hysa_rates by focusing on pass-through behavior.

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 establishes a clear context: use this tool when you need latest-Fed-hike pass-through data for savings accounts, optionally restricted to one institution. It does not explicitly name alternatives or when-not-to-use cases, but the purpose is specific enough to guide tool selection.

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