Fuzzy-search RBA F-tables by name and topic.

Use this when you don't know the exact table ID. The 5 curated F-tables (F1.1, F4, F6, F11, F11.1) cover the most-asked indicators: cash rate, money-market rates, household lending rates, FX rates.

Examples: # Find the F-table that publishes the cash rate results = await search_tables("cash rate") # → [{id: 'F1.1', name: 'Interest Rates and Yields - Money Market', ...}]

# Discover what's available on FX
results = await search_tables("aud usd", limit=5)
# → top 5 FX-related tables, curated F11/F11.1 first

When to use: - You have a natural-language question and need to identify the table - You want to discover what RBA publishes on a topic - You're enumerating the F-table catalog programmatically

Returns: List of TableSummary (id, name, frequency, description), ranked by relevance. Curated tables surface above the rest.

Describe an RBA F-table's series, units, and frequency.

For curated F-tables (F1.1, F4, F6, F11, F11.1), returns plain-English series keys (like 'cash_rate_target', 'aud_usd') with descriptions and units. For other F-tables, fetches the CSV and returns the raw RBA series IDs from the header along with start dates.

Examples: # Curated table — plain-English keys detail = await describe_table("F1.1") # detail.series[0]: key='cash_rate_target', series_id='FIRMMCRT', # unit='Per cent per annum', frequency='Daily'

# Curated FX table
detail = await describe_table("F11.1")
# detail.series has 'aud_usd', 'aud_eur', 'aud_jpy', 'aud_cny', etc.

When to use: - Before calling get_data on a new table — to discover valid series keys - To get the canonical RBA source URL for citation - To distinguish curated (plain-English) tables from raw F-tables

Returns: TableDetail with id, name, description, is_curated flag, frequency, list of SeriesDetail (key, series_id, description, unit), and rba_url.

Query an RBA F-table and return observations.

Curated tables (F1.1, F4, F6, F11, F11.1) accept plain-English series
keys that map to canonical RBA series IDs server-side. Pass a list of
keys for a multi-series query, or omit `series` to get every curated
series in the table.

Examples:
    # Cash rate target since 2020
    resp = await get_data("F1.1", series="cash_rate_target", start_date="2020")
    # → resp.records[0]: period='2020-01-01', value=0.25, series='cash_rate_target'

    # All FX rates against AUD, last year
    resp = await get_data("F11.1", start_date="2024-01-01", end_date="2024-12-31")
    # → resp.records covers aud_usd, aud_eur, aud_jpy, aud_cny, ... daily

    # Mortgage rates as CSV
    resp = await get_data("F6", format="csv", start_date="2023")
    # → resp.csv = "date,series,value

2023-01-01,housing_standard_variable,..."

    # Raw (non-curated) F-table — pass raw RBA series IDs
    resp = await get_data("F1", series=["FIRMMCRTD", "FIRMMBAB30"])

When to use:
    - You want a time series of an RBA indicator (use latest() for current-only)
    - You want a multi-series comparison (e.g. all FX rates)
    - You want CSV for downstream charting

Returns:
    DataResponse with records, unit, period bounds, RBA source URL,
    and CC-BY 4.0 attribution.

Return the most recent observation for each series in an RBA F-table.

Wraps get_data with last_n=1 (and a shorter cache TTL). Use this for "what's the current X?" questions — it's a cheap, fast call.

Examples: # Current cash rate target resp = await latest("F1.1", series="cash_rate_target") # → resp.records[0]: period='2026-05-06', value=3.85, unit='Per cent per annum'

# All AUD FX rates in one call (curated dashboard pattern)
resp = await latest("F11.1")
# → resp.records: latest aud_usd, aud_eur, aud_jpy, aud_cny, etc.

# Latest standard variable mortgage rate
resp = await latest("F6", series="housing_standard_variable")

When to use: - You want the current value of an RBA indicator - You want a current-snapshot of multiple series in one call (e.g. latest("F11.1") returns every FX rate) - You want sub-50ms warm-cache latency for chat integration

Returns: DataResponse with one most-recent observation per series.

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.