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Australian Economic Data (ABS, RBA & APRA)

by io.github.AnthonyPuggs
OverviewDiscussionsAdmin

Describe Dataset

describe_dataset
Read-onlyIdempotent

Describe a source-native ABS, RBA, or APRA dataset without hiding native IDs.

Tool call template

Replace each placeholder with a value matching the input schema. Only required parameters are included; add optional parameters as needed.

{
  "id": 1,
  "jsonrpc": "2.0",
  "method": "tools/call",
  "params": {
    "arguments": {
      "source": "<source>",
      "identifier": "<identifier>"
    },
    "name": "describe_dataset"
  }
}

Input Schema

NameRequiredDescriptionDefault
sourceYesSource selector. Use abs for Australian Bureau of Statistics, rba for Reserve Bank of Australia, or apra for Australian Prudential Regulation Authority.
table_idNoNon-empty dataset or table id.
identifierYesNon-empty dataset or table id.
include_structureNoWhether ABS descriptions should include source-native structure details.

Output Schema

NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already disclose readOnlyHint=true, idempotentHint=true, and destructiveHint=false, covering safety. The description adds valuable behavioral context by emphasizing 'source-native' and 'without hiding native IDs', which signals output representation nuances beyond the structured annotations. No contradiction with 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 sentence, front-loaded with the verb and resource scope, and every word contributes meaning. No filler or redundant phrasing.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The existence of an output schema covers return-value expectations. The main gap is the unresolved ambiguity between table_id and identifier, which the description does not address. For a moderately complex tool with four parameters, a bit more clarification on parameter usage would improve completeness.

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 description coverage is 100%, with each parameter (source, table_id, identifier, include_structure) already described in the schema. The tool description adds no parameter-specific meaning and does not clarify the ambiguous relationship between table_id and identifier, so the baseline score of 3 applies.

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 identifies a specific verb ('Describe') and resource ('dataset'), scoped to ABS, RBA, and APRA sources, and adds a distinctive detail ('without hiding native IDs') that differentiates it from sibling tools. It doesn't enumerate what the description includes, which keeps it from a perfect 5.

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?

There is no explicit guidance on when to use this tool versus alternatives like get_abs_dataset_structure or get_rba_table. The description only states what it does, not the context for using it or exclusions. The agent is left without clear selection criteria.

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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