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Glama

Australian Economic Data (ABS, RBA & APRA)

by io.github.AnthonyPuggs

List Economic Concepts

list_economic_concepts
Read-onlyIdempotent

List analyst-friendly semantic economic concepts accepted by get_economic_series.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
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.
categoryNoOptional curated catalogue or semantic concept category filter.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYesCurated semantic economic concepts.

Schema Changelog

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

  1. First observed

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering the safety profile. The description adds the relationship to get_economic_series but does not elaborate on filtering behavior or response format, which is acceptable given the annotations.

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, focused sentence that delivers the essential information without any filler. Every word contributes to understanding the tool's purpose.

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?

For a read-only listing tool with three optional parameters and an output schema, the description provides sufficient context by linking to get_economic_series. It could mention the openWorldHint dynamic nature or filter usage, but these are already covered by annotations and schema.

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?

Schema coverage is 100% with meaningful descriptions for all three parameters (query, source, category). The description adds no additional parameter-specific meaning beyond what the schema provides, so the baseline 3 applies.

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 lists analyst-friendly semantic economic concepts accepted by get_economic_series. This specific verb-resource pairing distinguishes it from sibling tools that fetch data (e.g., get_economic_series) or list catalogue tables.

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 implies the tool is a reference for valid concepts to use with get_economic_series, providing clear context on when to use it. However, it does not explicitly contrast it with sibling tools like list_catalogue or search_datasets, nor mention exclusions.

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