databutler-policy-rates

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

Annotations already establish read-only, idempotent, non-destructive behavior, so the description focuses on useful operational detail: the exact units (% per annum), that the latest decision may be a hold, and that unknown banks yield covered:false. It stops short of explaining freshness guarantees beyond the verifiedDate field.

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?

Purpose and per-bank definitions are front-loaded, and the return-field enumeration is dense but justified given there is no output schema. The single long sentence is information-rich but slightly list-heavy.

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 carries the full burden and does so: it enumerates every returned field (rate, effectiveFrom, decisionDate, prior level, latest decision, next decision date, source, press release, verifiedDate) and covers the all flag and unknown-bank behavior.

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%, so the baseline is 3, but the description adds real meaning: it explains that fed maps to a target range with lower and upper bounds and that ecb maps to deposit/refinancing/marginal lending facility rates, details the enum alone doesn't convey.

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 names a specific resource (central-bank policy rates) and scope (exactly three banks: boe, fed, ecb), and spells out what each code denotes. An agent can tell immediately what this tool returns and for which institutions.

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?

Usage context is clear: use this for these three banks, and `all: true` returns every bank, while other central banks return covered:false. There are no sibling tools, so no alternative routing is needed, but it never states prerequisites or when-not-to-use beyond the scope limitation.

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