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

Annotations already establish read-only, idempotent, open-world, non-destructive behavior. The description adds useful behavioral context—the complete list scope and the two specific fields returned—which compensates for the absence of an output schema.

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?

One concise sentence with no filler, front-loaded with the verb and scope. Every word adds value: 'every', 'reference-rate coverage', 'central bank', and 'peg classification' are all informative.

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 is low-complexity (no params, safe read-only operation, no output schema). The description tells the agent what the response contains and the scope of the list, which is sufficient to select and 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?

There are zero parameters, so there is nothing for the description to add over the input schema. The 0-param baseline of 4 applies; mentioning parameters would be redundant.

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 precise verb ('List') and resource ('every currency Ready APIs has reference-rate coverage for'), and names the output fields (issuing central bank, peg classification). This makes it easy to distinguish from sibling FX tools like fx_rates or fx_convert without needing their schemas.

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 clearly communicates when to call it: when an agent needs the universe of currencies with reference-rate coverage, including central bank and peg details. It does not explicitly name sibling alternatives or when-not-to-use conditions, so it stops short of a 5.

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