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Bigred97

Reserve Bank of Australia

release_calendar

Fetch upcoming RBA publication schedule for data releases, statements, and events. Returns a chronological feed with release dates, titles, and event types.

Instructions

Upcoming RBA publication schedule (data + statements + events).

Scrapes https://www.rba.gov.au/schedules-events/ and merges the two schedule tables into a single chronological feed. Each entry reports release_at (Sydney local with UTC offset), title, event_type, dataset_id (curated F-table key when the release refreshes one, else null), publication_id, and source_url.

Event types: - data_release — regular statistical publication (Financial Aggregates, Retail Payments, Index of Commodity Prices, etc.) - statement — narrative release (Statement on Monetary Policy, Minutes of Monetary Policy Meeting, Financial Stability Review, Bulletin, Chart Pack) - policy_decision — cash-rate decisions are NOT exposed here; they appear on a separate RBA page. The Statement on Monetary Policy and Minutes that follow ~24h and ~2 weeks later DO appear, tagged as statement.

Returns the same envelope shape as abs-mcp.release_calendar so a gateway poller can dispatch both feeds through the same code path.

Cached at 24h TTL with stale-fallback on 5xx (per portfolio graceful-degradation policy). The gateway should poll on its own schedule rather than hitting the live HTML.

Examples: cal = await release_calendar(7) for r in cal.releases: print(r.release_at, r.event_type, r.title, r.publication_id)

cal = await release_calendar(60)
statements = [r for r in cal.releases if r.event_type == "statement"]

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
days_aheadNoHorizon in days. Returns RBA publications + events scheduled to release between now and `now + days_ahead`. Default 30 covers the typical monthly cadence.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
staleNo
sourceNoReserve Bank of Australia
releasesNo
row_countYes
source_urlNohttps://www.rba.gov.au/schedules-events/
attributionNoData sourced from the Reserve Bank of Australia and licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). https://www.rba.gov.au/copyright/
horizon_daysYes
retrieved_atYes
stale_reasonNo
server_versionNo
Behavior5/5

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

With no annotations provided, the description fully bears the burden. It discloses scraping behavior, caching policy, event types, limitations (cash-rate not included), and the output shape. This is comprehensive and transparent.

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 well-structured with clear sections (purpose, source, event types, caching, examples). Every sentence adds value, and it is appropriately sized for the tool's complexity.

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?

Given the tool's complexity (scraping, caching, multiple event types) and the presence of an output schema, the description covers all necessary aspects: behavior, limitations, caching, and usage. It is fully complete.

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?

Schema coverage is 100%, so baseline is 3. The description adds value through usage examples and context (e.g., default covers monthly cadence).

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 the tool's purpose as fetching the upcoming RBA publication schedule, specifying the verb 'scrapes' and the resource 'RBA publication schedule'. It distinguishes from sibling tools (data retrieval tools) by focusing on a live calendar scrape.

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

Usage Guidelines4/5

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

The description provides usage context: it is cached with 24h TTL, should not be hit live, and cash-rate decisions are not included. However, it does not explicitly name alternative tools or provide a when-not-to-use beyond the cash-rate exclusion.

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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