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

Annotations already cover the safety profile (readOnlyHint, idempotentHint, destructiveHint=false), so the description only needs to add context. It does: the data is authoritative government reporting rates and is 'Published quarterly', which tells the agent how fresh results are and that this is not real-time market data. It does not describe pagination or default behavior when no filter is applied.

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?

Three short, front-loaded sentences that lead with the source and nature of the data before the optional filter instruction. The example values slightly duplicate the schema's own examples, but nothing is padded or wasted.

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?

For a simple two-optional-parameter lookup with no output schema, the description supplies the essentials: what the data is, its official origin, its quarterly cadence, and how to filter. Missing only edge behavior such as the default result set when no query is given and how limit interacts with large result sets.

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 100%, so the schema already documents both the query matcher and the limit, including its min/max. The description repeats the query examples ('Canada', 'Euro', 'Yen') that the schema already provides and says nothing about the limit parameter, so it adds little beyond structured data.

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 and its provenance: 'Official US Treasury Reporting Rates of Exchange (the rates US government agencies use to convert foreign currency balances to dollars).' It clearly distinguishes this data from market/spot FX rates available via sibling tools like fred_* or worldbank_*, though it never names an alternative directly.

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?

It gives a filtering hint ('Provide a country or currency to filter, e.g. Canada, Euro, Yen') but no explicit when-to-use vs. when-not, no statement of what happens when no query is supplied, and no routing to alternative rate sources. Usage is implied rather than stated.

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