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Australian Bureau of Statistics

release_calendar

Retrieve upcoming Australian Bureau of Statistics publication schedules. Filter by days ahead to see scheduled data releases with titles and release times.

Instructions

Upcoming ABS publication schedule (data releases).

Scrapes the official ABS release calendar (https://www.abs.gov.au/release-calendar/future-releases-calendar) and returns each scheduled publication with its release timestamp, title, reference period, and — when the title maps to a curated abs-mcp dataset — the dataset_id an agent can plug into get_data or latest. Curated mappings cover the 10 datasets in list_curated() plus a handful of commonly-watched non-curated catalogues (Retail Trade, International Trade in Goods, etc., where dataset_id stays null but publication_id carries the ABS catalogue number).

release_at is returned with Sydney's local UTC offset (+10:00 AEST or +11:00 AEDT) — what ABS publishes against. The DST switch is naive (month-based), within an hour of correct at the changeover boundary; downstream code should treat the offset as authoritative rather than re-deriving local time.

Examples: # Next 7 days cal = await release_calendar(7) for r in cal.releases: print(r.release_at, r.title, r.dataset_id)

# Filter to curated datasets only
cal = await release_calendar(30)
curated_releases = [r for r in cal.releases if r.dataset_id]

When to use: - Building a webhook / notification feed (ABS publishes at 11:30 AEST) - "What's next from the ABS?" agent answers - Pre-warming caches the morning of a known release

Returns: ReleaseCalendarResponse — same envelope shape as rba-mcp's release_calendar for portfolio interop. Sorted ascending by release_at. stale=True + stale_reason is set when the live HTML scrape failed and a cached payload was served past TTL.

Input Schema

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

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
staleNo
sourceNoAustralian Bureau of Statistics
releasesNo
row_countYes
source_urlNohttps://www.abs.gov.au/release-calendar
attributionNoData sourced from the Australian Bureau of Statistics and licensed under Creative Commons Attribution 4.0 International (CC BY 4.0). https://www.abs.gov.au/about/copyright-and-creative-commons
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, the description fully carries behavioral disclosure. It details timezone handling with Sydney offset and DST naivety, caching behavior with stale flag, mapping to dataset_id for curated datasets, and output shape. No hidden traits.

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: purpose first, then details, examples, when-to-use, and return format. Every sentence adds value; no fluff. Front-loaded with the core action.

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, timezone, caching, mappings) and the presence of an output schema, the description covers all necessary context: source, fields, behavior edge cases, and integration with sibling tools. No gaps.

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 sole parameter `days_ahead` has full schema coverage (100%) with description, default, range, and examples. The description adds context about the horizon covering 'typical monthly + quarterly cadence', which enhances understanding beyond the schema.

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 it returns the upcoming ABS publication schedule, names the source URL, and describes the returned fields. It distinguishes itself from sibling tools by focusing on the release calendar, not data retrieval or searching.

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 dedicated 'When to use' section explicitly lists scenarios: building webhooks, agent answers for 'What's next?', and cache pre-warming. It also notes portfolio interop with rba-mcp, providing clear context for appropriate use.

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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