Get a time series of exchange rates for a base currency over a date range (max ~1 year), useful for trend analysis. Provide start and end as YYYY-MM-DD and one or more target currencies.
| Name | Required | Description | Default |
|---|---|---|---|
| end | Yes | YYYY-MM-DD | |
| base | No | 3-letter base (default USD) | |
| start | Yes | YYYY-MM-DD | |
| symbols | Yes | Comma-separated targets, e.g. EUR,GBP |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description carries full burden for behavioral traits. It mentions a max ~1 year date range but omits details on rate limits, authentication, error conditions, or what happens if range is exceeded. Insufficient disclosure for a financial API.
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 concise sentences: first states purpose and constraint, second gives parameter instructions. No redundant 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?
No output schema and description does not explain return format (e.g., array of objects with dates and rates). Given complexity of time series data, this lack of return structure information reduces completeness.
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% with parameter descriptions. Description adds context by reiterating date format and clarifying 'one or more target currencies' and default base. Adds moderate value beyond schema.
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?
Description clearly defines the tool as retrieving a time series of exchange rates over a date range for trend analysis, specifying verb, resource, and constraints. It implies distinction from sibling tools (e.g., fx_convert for single conversion) but does not explicitly differentiate.
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?
Description hints at use case ('useful for trend analysis') but lacks explicit when-to-use vs alternatives, such as noting that fx_historical might be better for a single date. No exclusions or prerequisites mentioned.
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.
Each tool targets a distinct operation: one-off conversion, currency listing, latest rates, historical rates, and time-series analysis. There is no meaningful overlap between any pair.
All tools share the fx_ prefix, but naming style is inconsistent: fx_convert is a verb, while fx_currencies, fx_rates, fx_historical, and fx_timeseries are nouns/adjectives. Consistent verb_noun names such as list_currencies or get_rates would improve predictability.
Five tools is well-scoped for an FX reference-rate server: one converter, one metadata endpoint, and three rate-lookup variants. Each tool serves a distinct, useful purpose with no bloat.
The surface covers the core FX use cases: listing supported currencies, latest rates, historical rates, time series, and amount conversion. No obvious missing operation is needed for the stated domain.