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

Annotations already declare readOnlyHint=true and openWorldHint=true, so the safety profile is covered. The description adds real behavioral context: the output is a catalog of institutions with frequency categories (daily, weekly, monthly, quarterly) and coverage date ranges, and that omitting a provider yields a blend. No mention of ordering or whether results are cached.

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 sentences, no filler. The catalog contents come first and the cross-tool usage note follows, which is the right order for an agent scanning for relevance.

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 input parameters and no output schema, the description carries the return-value burden and largely discharges it by naming the fields returned. A little more on the response shape (e.g. a flat array vs. object) would make it fully self-sufficient.

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?

The tool takes no parameters, so the baseline applies and the description correctly spends no space on argument docs. It instead explains the semantic meaning of the returned `key` field as an input to sibling tools, which is the relevant 'parameter' knowledge here.

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 ('List the institutions whose rates Frankfurter relays') and enumerates what each entry carries: key, rate type, frequency, coverage dates. This clearly distinguishes it from list_currencies and from the rate-fetching siblings convert/get_rates.

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?

Explicitly says to take a returned key and pass it as `provider` to `convert` or `get_rates` for single-institution rates instead of the default blend. That is strong routing guidance, though it explains downstream use rather than stating when this tool itself should be chosen over an alternative.

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