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Bigred97

Reserve Bank of Australia

list_curated

Retrieve the list of RBA F-table IDs with plain-English support for querying cash rate, exchange rates, and lending rates.

Instructions

List the 5 RBA F-table IDs with hand-curated plain-English support.

These are the tables where get_data and latest accept plain-English series keys (like 'cash_rate_target', 'aud_usd'). Other F-tables are still queryable via raw RBA series IDs.

The 5 curated F-tables: - F1.1 — Interest Rates and Yields: Money Market (incl. cash rate target) - F4 — Money Market Operations - F6 — Housing Lending Rates (standard variable, fixed, etc.) - F11 — Exchange Rates (AUD vs major currencies, daily) - F11.1 — Exchange Rate Indices (TWI, real TWI)

Example: ids = list_curated() # → ['F1.1', 'F11', 'F11.1', 'F4', 'F6']

When to use: - You want to know which tables have plain-English support - You're building a UI / agent that needs the supported set up front - You want to plan which F-tables to call without inspecting each

Returns: Sorted list of F-table IDs. Always 5 entries today.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

No annotations provided, so description carries full burden. It describes return format (sorted list of 5 entries) and explicitly states 'Always 5 entries today', but could mention if list is static or dynamic.

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?

Well-structured with summary, list, example, usage guidance, and return description. Every sentence adds value; no wasted words.

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

Completeness5/5

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

Completely covers all necessary information for a zero-parameter tool: purpose, use cases, return format, and example. No gaps given the simplicity.

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?

No parameters, baseline 4. Description adds value by explaining the meaning of the return values and context of the 5 tables, such as their names and example usage.

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 states 'List the 5 RBA F-table IDs with hand-curated plain-English support', using specific verbs and resource, and distinguishes from siblings like get_data or describe_table.

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?

Explicitly outlines when to use: when needing the set of curated tables for UI/agent planning, and implies alternatives like search_tables for non-curated tables.

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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