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AnthonyPuggs

AusEcon MCP for ABS | RBA | APRA data

Get Derived Series

get_derived_series
Read-onlyIdempotent

Retrieve derived economic series from ABS, RBA, and APRA data by concept name, with optional start/end dates and last N observations for precise analysis.

Instructions

Read-only retrieval for the narrow transparent derived series layer.

Date bounds accept YYYY, YYYY-QN, YYYY-SN, YYYY-MM, or YYYY-MM-DD and are normalised to the derived series frequency.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
conceptYesDerived concept name.
startNoOptional analyst-friendly bound for a derived series: YYYY, YYYY-QN, YYYY-SN, YYYY-MM, or YYYY-MM-DD. Bounds are normalised to the derived series frequency.
endNoOptional analyst-friendly bound for a derived series: YYYY, YYYY-QN, YYYY-SN, YYYY-MM, or YYYY-MM-DD. Bounds are normalised to the derived series frequency.
last_nNoOptional limit returning only the most recent N observations per series; metadata.truncated is true when older observations were dropped.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
metadataYesSource, provenance, cache, and retrieval metadata for this response.
seriesYesSeries descriptors keyed by series_id.
observationsYesLong-form observations keyed by date and series_id.
Behavior4/5

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

Annotations already provide readOnlyHint, destructiveHint, idempotentHint, openWorldHint. The description adds that date bounds accept specific formats and are normalized to frequency, offering meaningful behavioral context beyond 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?

Two concise sentences: first states purpose, second explains date bounds. No wasted words, front-loaded with key information.

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?

With output schema present, the description covers the main purpose and date handling. It does not mention the last_n parameter's truncated behavior, which is in schema but missing from description. Mostly complete for a tool with these features.

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%, so parameters are well-documented. The description adds a clarification about date format normalization, but overall does not significantly enhance what the schema already provides.

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 clearly states 'read-only retrieval for the narrow transparent derived series layer', specifying the verb and resource. However, it does not explicitly differentiate from siblings like get_economic_series, limiting its clarity.

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?

No guidance on when to use this tool versus alternatives. The description implies usage for derived series retrieval but provides no contextual or exclusionary information.

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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