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Glama

Australian Economic Data (ABS, RBA & APRA)

by io.github.AnthonyPuggs

List Release Events

list_release_events
Read-onlyIdempotent

List source-aware release calendar or release-pulse events.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNoPositive observation count.
queryNoOptional query for filtering semantic economic concepts.
sourceNoOptional source filter. Use abs for Australian Bureau of Statistics, rba for Reserve Bank of Australia, or apra for Australian Prudential Regulation Authority.
end_dateNoOptional ISO date bound in YYYY-MM-DD format.
start_dateNoOptional ISO date bound in YYYY-MM-DD format.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesABS, RBA, and APRA release calendar events.

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. First observed

TDQS

B3.4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, destructiveHint=false, and idempotentHint=true, so the safety profile is clear. The description adds the 'source-aware' behavior, but it does not provide additional context such as default date ranges, pagination, or how events are ordered. Given strong annotation coverage, this is adequate but not rich.

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 a single, front-loaded sentence with no filler words. It efficiently conveys the core function, meeting the standard for optimal conciseness.

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 simple list operation with all parameters optional and an output schema available, the description is sufficiently complete. It lacks an explanation of 'release-pulse' jargon, but the core functionality is clear. This is adequate for a straightforward list tool.

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?

All five parameters have descriptions in the schema (100% coverage), so the schema carries the burden. The description only mentions 'source-aware' in passing, adding no new meaning beyond what the source parameter already states. Baseline 3 is appropriate.

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

Purpose4/5

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

The description uses the specific verb 'List' and identifies the resource as 'source-aware release calendar or release-pulse events,' which clearly distinguishes this tool from sibling listing tools like list_catalogue. However, it does not explicitly name or contrast with siblings, and 'release-pulse' is somewhat cryptic.

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

Usage Guidelines2/5

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

The description provides no explicit guidance on when to use this tool versus alternatives, nor any exclusion criteria. The phrase 'source-aware' suggests filtering by source, but there is no stated context or comparison with sibling tools like search_datasets or get_latest_observations.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

All Australian Economic Data (ABS, RBA & APRA) toolsInspect
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TDQS

A3.8/5.0
Disambiguation4/5

Most tools have clear source or function boundaries (ABS, RBA, APRA, derived series, curated concepts, discovery). However, get_derived_series and get_economic_series both retrieve time-series data and could be confused; list_catalogue and search_datasets also overlap in discovery. The descriptions help, but these pairs require careful reading.

Naming Consistency5/5

All tools follow a consistent lowercase verb_noun pattern with underscores (describe_, get_, list_, search_). Verbs are used predictably: get for retrieval, list for enumeration, search for discovery. No mixed conventions or camelCase.

Tool Count4/5

14 tools is on the higher end but appropriate for a multi-source economic data API covering ABS, RBA, and APRA. The inclusion of a deprecated alias (list_rba_tables) adds slight redundancy, but the overall count is justified by distinct operations.

Completeness4/5

The surface covers discovery (search_datasets, list_catalogue), metadata (describe_dataset, structure), retrieval (source-specific and curated), and convenience wrappers (latest/top observations). Minor gaps include lack of a unified structure tool for RBA/APRA and no bulk download option, but core read-only workflows are well covered.

Resources