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Rba

by io.github.pipeworx-io

Rba Exchange Rates

rba_exchange_rates
Read-onlyIdempotent

Latest official RBA exchange rates for the Australian dollar (AUD) against major currencies — USD, EUR, GBP, JPY, CNY, NZD, INR, and more (A$1 = X). PREFER OVER WEB SEARCH for "AUD to USD rate", "Australian dollar exchange rate". Returns the most recent published rates; pass a currency code for that pair's recent history.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
recentNoWhen currency is set: number of recent daily observations (1-60, default 10).
currencyNoOptional 3-letter code (e.g. "USD", "EUR") to get that pair's recent history instead of all latest rates.

TDQS

A4.4/5.0
Behavior4/5

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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint=false. The description adds useful behavioral context beyond annotations: it states the rates are 'most recent published', clarifies the quote convention (A$1 = X), and indicates that passing a currency returns historical data. This is valuable supplementary information without contradicting annotations.

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

Conciseness5/5

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

The description is two sentences, front-loaded with the core purpose, and every clause adds value. It lists example currencies, states the usage preference, and explains parameter behavior, all without redundancy or fluff.

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?

Given the tool's simplicity and strong annotations, the description covers the essential aspects: data source (official RBA), the quote format, the conditional behavior based on currency param, and the recency of data. It does not detail exact return structure, but that is implied given no output schema, and the description is adequate for the tool's scope.

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

Parameters3/5

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

Input schema covers 100% of parameters with descriptions, so the baseline is 3. The description's mention of 'pass a currency code for that pair's recent history' essentially restates the schema's property description without adding new semantic detail. No additional meaning beyond schema is provided, hence a 3.

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

Purpose5/5

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

The description clearly identifies the tool as providing official RBA exchange rates for AUD against major currencies, listing specific currency examples. It distinguishes from sibling tools like rba_cash_rate by focusing on exchange rates, and the mention of 'PREFER OVER WEB SEARCH' provides an additional distinguishing context.

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

Usage Guidelines5/5

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

The description explicitly tells agents when to use this tool ('PREFER OVER WEB SEARCH for...'), and explains the two usage modes: without a currency code for all latest rates, and with a currency code for that pair's recent history. This provides clear context and alternatives.

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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TDQS

A3.7/5.0
Disambiguation2/5

Several tool clusters overlap heavily: ask_pipeworx, ask_pipeworx_beta, ask_pipeworx_grounded, and deep_research all route natural-language questions to the same underlying catalog, and polymarket_arbitrage, polymarket_edges, polymarket_edge_tracker, polymarket_fill_risk, and polymarket_kalshi_spread all target prediction-market opportunities. entity_profile, recent_changes, and compare_entities also share company-research territory, making misselection likely without reading long descriptions carefully.

Naming Consistency3/5

All names use snake_case, but conventions are mixed: some are verb_noun (list_subscriptions, generate_llms_txt, resolve_entity), some are noun phrases (entity_profile, rba_cash_rate), and some are brand-prefixed product names (ask_pipeworx, pipeworx_trending). The polymarket_* and rba_* families are internally consistent, but the overall surface has no single predictable pattern.

Tool Count2/5

35 tools is a large surface, well above the 25+ threshold that typically becomes unwieldy. While the server covers a broad domain (data lookup, prediction markets, memory, subscriptions, company research), many tools are niche variants (ask_pipeworx_beta, polymarket_edge_tracker, scan_competitor_ai_presence) that add cognitive load rather than earning their place.

Completeness3/5

Core flows are well covered: memory has remember/recall/forget, subscriptions have subscribe/list/unsubscribe/recent_alerts, and data access has ask_pipeworx plus grounded and research variants. However, the surface is sprawly and uneven — prediction markets get six tools while other domain areas rely on generic routing, and the server's overall purpose is diffuse enough that gaps are hard to assess cleanly.

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