Official US Treasury exchange rates (fiscaldata.treasury.gov) — the US-side counterpart to ECB rates, used for US federal reporting.
| Name | Required | Description | Default |
|---|---|---|---|
| country | Yes | e.g. "Euro Zone" | |
| currency | Yes | e.g. "Euro" |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries the full burden. It mentions the source and use case but does not disclose behavior like data freshness, response format, or any access requirements. For a tool that will be called automatically, the agent is left to guess the output nature.
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 sentence, front-loaded with the resource identity and source, and a useful comparison. No redundancy. It loses a point for not leading with an action verb, but it is otherwise tight.
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 tool with no annotations and no output schema, the description omits how the rates are returned (e.g., daily vs historical), any date or qualification parameters, and what the response looks like. The intended federal-reporting use case is mentioned, but operational details are missing, leaving the agent under-informed.
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 provides descriptions for both required parameters (country, currency) with examples. The description adds no further meaning about the parameters. With 100% schema coverage, a baseline score of 3 is appropriate.
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 clearly identifies the resource (US Treasury exchange rates) and source (fiscaldata.treasury.gov), and contrasts it with the ECB counterpart. However, it is phrased as a noun phrase rather than an explicit verb+resource formulation like 'returns exchange rates', making the exact action slightly implicit.
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 provides context ('used for US federal reporting') and a comparison ('US-side counterpart to ECB rates'), which hints at when to prefer this tool, but there is no explicit statement of when to use vs. not use, nor any named alternative tool in the sibling list. The guidance 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.
Add one secure layer between your agents and this server.
Most tools are clearly distinct by resource or function, but fx_rates vs us_treasury_fx and entity_resolve vs lei_lookup could both be plausible choices for the same request. Descriptions generally make the boundaries clear, so the overlap is minor rather than systematic.
All names use lowercase_snake_case, but there is no single naming pattern: tools like btc_network, crypto_price, and weather_forecast are noun phrases, while eu_vat_validate, lei_lookup, and sanctions_screen follow an object+operation style. This mixed convention is readable but noticeably inconsistent.
14 tools is within a reasonable range for a multi-provider data server, and most tools cover a distinct data domain. However, kyb_verify_business heavily overlaps the individual VAT, LEI, sanctions, IBAN, and entity tools, and having two FX rate tools makes the set feel slightly broader than necessary.
The main KYB/entity workflow is well covered, but the set has notable gaps: sanctions screening covers only OFAC and UK OFSi, IBAN validation is structural only, and there are no UBO or adverse-media checks. For the broader data-lookup domain, the coverage is decent but not exhaustive.