get_latest_fiat_ratesReturns latest Arzbin fiat currency rates in Toman. Data is indicative market data, not financial advice.
| Name | Required | Description | Default |
|---|---|---|---|
| codes | No | Optional fiat currency codes such as USD, EUR, AED, GBP. Omit for all available fiat rates. |
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| source | Yes | ||
| disclaimer | Yes | ||
| generatedAtUtc | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
The description adds a data quality caveat ('indicative market data, not financial advice') beyond the annotations, providing useful context about data reliability. It does not disclose rate limits or error behavior, but annotations already cover the read-only and idempotent safety profile.
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 fluff, front-loads the key function and then a caveat. Every word earns its place.
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?
The tool is simple with one optional parameter and an output schema. The description adequately covers purpose and data quality; the schema handles filtering details. It only lacks explicit usage alternatives, already accounted for in the usage dimension.
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% for the single parameter (codes), including examples and default behavior. The description does not add parameter semantics, but the baseline of 3 is appropriate when the schema fully documents the parameters.
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 states the tool returns the latest fiat currency rates in Toman, with a specific resource (Arzbin fiat rates) and scope (latest, in Toman). It distinguishes from siblings like crypto/gold rates and market history by explicitly focusing on fiat currency.
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?
The description does not explicitly mention alternatives or exclusions, such as when to use convert_to_toman or get_market_history. Usage is implied from the tool name and mention of 'fiat rates,' but lacks clear guidance on when not to use this tool.
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 aspect of the market data domain: converting amounts, fetching current rates for different asset classes, retrieving historical data, and accessing rate sources. The clear differentiation between crypto, fiat, gold, and conversion prevents ambiguity.
All tools follow a consistent get_/convert_ verb-noun snake_case pattern. The only deviation is convert_to_toman, which still fits the verb_object style and is distinguishable from the get_ family.
With 6 tools, the server is well-scoped for its purpose of providing Toman-denominated market data. Each tool covers a necessary function—rates for various asset classes, conversion, history, and source info—without unnecessary bloat.
The tool surface comprehensively covers the domain: current rates for crypto, fiat, and gold, conversion to Toman, historical OHLC data, and source comparison. No obvious gaps exist for a market data server focused on Iranian exchange rates.