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

With no annotations, the description carries the load and does well: it discloses cost ($0.002 per call), that no API key is required, the upstream source, and that it returns rates plus a last-update timestamp. It omits rate limits and error behavior, but the cost and auth disclosures are meaningful context an agent would not otherwise have.

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?

A single dense sentence, front-loaded with the cost signal, then source, then params, then return shape. No filler; every clause carries information.

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?

There is no output schema, and the description compensates by naming what is returned (rates + last-update timestamp). For a 2-param read tool this is nearly complete; only error/rate-limit behavior is unaddressed.

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 both parameters are already documented, and the description largely repeats that (defaults, comma list, ISO code). It adds only minor meaning (ISO code framing), so the baseline 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?

States a specific verb and resource ('Live fiat exchange rates'), names the data source (open.er-api.com), and scopes it (~200 currencies, no key). This clearly separates it from siblings like stock_quote or sec_edgar_search without needing to open a schema.

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 is implied by the purpose ('fiat exchange rates') but there is no explicit when-to-use, when-not-to-use, or named alternative among the siblings. An agent can infer conversion use cases, but nothing routes it away from the tool when inappropriate.

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