Bank Savings Gap

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is covered. The description adds genuinely non-structured context: comparisonApy is the average of the top three tracked rates rather than a market-wide average, bankCount bounds that set, and the result is explicitly a hypothetical estimate requiring the user to verify eligibility, fees and provider terms. That methodology disclosure is exactly the kind of value annotations cannot carry.

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 purpose is front-loaded in the first clause, followed by methodology and then caveats — a sensible ordering. Four sentences is defensible, but the enumeration of return fields ('annualGap, APYs, observation date, freshness and methodology') duplicates the output schema and is the one sentence that does not earn its place.

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 an output schema present, describing return values was optional, and the annotations already carry the safety profile, so the description's remaining job is purpose, metric semantics and caveats — all present. The one real hole is routing: an agent cannot tell from this text when to prefer it over get_bank_gap_index or compare_switch_savings.

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 only 50% — the bank parameter is documented, balance is not. The description compensates by clarifying that bank is optional and, more importantly, that omitting it swaps baselineApy from the named bank's APY to the national savings benchmark, which is real semantic meaning the schema does not convey. It still says nothing about balance units, though the number type plus the 10,000,000 maximum makes dollars the obvious reading.

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?

States a specific verb and resource: 'Estimate annual savings interest forgone for a supplied balance and optional bank name,' which tells the agent exactly what question the tool answers. It defines the headline metric (annual savings interest forgone) concretely enough to separate it from rate-listing siblings like get_top_hysa_rates. It does not, however, address the closely named sibling get_bank_gap_index, so full differentiation is left to inference.

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 never says when to reach for this tool rather than get_bank_gap_index, compare_switch_savings, or get_top_rates; only a caveat ('hypothetical estimate, not an account recommendation') is given. The 'optional bank name' phrasing implies a no-bank vs named-bank use case, but that is inference rather than stated guidance. No exclusions, prerequisites, or alternatives are named.

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