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Novarithm Agent Hub: trust and commerce checks

fx_xof_brl

[PAID $0.002 USDC/call, x402, eip155:8453] Official XOF/BRL reference rate: latest European Central Bank fixing (or the official peg when BRL is pegged), with the rate date, the method (direct, cross via EUR or peg-derived) and the source attribution. Deterministic, sourced, no estimate.

Tool call template

This tool declares no required parameters. Add optional parameters from the input schema as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {},
    "name": "fx_xof_brl"
  }
}

Input Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. Added

TDQS

A3.8/5.0
Behavior4/5

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

With no annotations supplied, the description carries the full burden and does a solid job: it discloses the commercial model ([PAID $0.002 USDC/call, x402, eip155:8453]), the data source (ECB fixing), a fallback path (official peg when BRL is pegged), the provenance fields returned (rate date, method, source attribution), and the guarantee that the value is deterministic and not an estimate. What it does not cover is the concrete invocation mechanics of the x402 payment flow (e.g., whether a balance or verification step is a prerequisite, given the usdc_balance/verify_usdc_payment siblings) or the response envelope.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

It is a single dense sentence with the payment terms front-loaded in brackets, followed by source, fallback, and output fields — every clause adds information. Minor cost is that "eip155:8453" and "x402" are unexpanded jargon an agent may need to decode, but they are standard identifiers for this payment scheme.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a zero-parameter tool that returns a single rate with provenance and has no output schema, the description covers what matters: what the number is, where it comes from, the peg fallback, the fields bundled with it, and that it costs money. The remaining gap is the payment precondition and the shape of the returned payload, but neither is required to select the tool correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The input schema is an empty object with zero parameters, so there is no parameter semantics to explain and the baseline 4 applies. The description correctly implies a parameterless, fixed-pair call with no date argument, consistent with the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific resource ("Official XOF/BRL reference rate") and pins down the exact nature of the value: the latest European Central Bank fixing, or the official peg when BRL is pegged. That is far more precise than the bare tool name, whose meaning among hundreds of fx_* siblings would otherwise be ambiguous. It does not explicitly contrast itself with fx_convert, fx_latest, or fx_timeseries, which keeps it from a 5.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Usage is implied rather than stated: naming it a "reference rate" and asserting "no estimate" signals this is the authoritative figure rather than a converted or market-derived one, which indirectly separates it from fx_convert. However, no sibling is named and there is no explicit when-to-use/when-not statement, so an agent must infer that historical series belong to fx_timeseries and arithmetic conversion to fx_convert.

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

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