imf-ra-catalog

Translate natural language research requests into confirmed dataset and indicator identifiers.

Updated Apr 30, 2026
One-click install
npx skills add https://github.com/johnsonice/RA-Skills --skill imf-ra-catalog
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: imf-ra-catalog
Source: https://github.com/johnsonice/RA-Skills/tree/main/skills/imf-ra-catalog
Command: npx skills add https://github.com/johnsonice/RA-Skills --skill imf-ra-catalog

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) components.

What problem does it solve?

This Skill eliminates the guesswork and manual effort of finding the correct IMF, World Bank, Bloomberg, WTO, or Haver Analytics dataset, dimension, and indicator codes for natural language research requests, ensuring accurate, validated identifiers for data retrieval.

Core Features & Use Cases

  • Plain English to Identifier Mapping: Translates natural language requests like "current account balance for advanced economies, quarterly" into exact (database, dimension_name, code) identifiers for iData sources, or CODE@DB formats for Haver sources.
  • Ambiguity Resolution: Distinguishes between similar indicators, units, transformations, and database families, asking for clarification when requests are unclear instead of inventing incorrect codes.
  • Multi-Source Routing: Automatically routes requests to the correct source family (WEO Live, WDI, Bloomberg, WTO, Haver, etc.) based on request context, including handling legacy IFS requests by routing to replacement iData topic databases.
  • Use Case: A researcher asking for "2024 US weekly jobless claims" will be routed to the Haver USECON database, presented with matching series variants, and given a confirmed handoff identifier for data retrieval, without needing to know internal Haver database structure.

Quick Start

Use this skill to translate your plain English data request, such as "annual fiscal balance for emerging markets", into a confirmed dataset identifier ready for data retrieval.

Frequently Asked Questions about imf-ra-catalog

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I find the correct IMF dataset code from a natural language research request?

This Skill translates natural language research requests into exact, confirmed dataset and indicator identifiers for IMF iData, World Bank, Bloomberg, WTO, and Haver Analytics sources. It routes your request to the correct database and returns validated codes.

What is the best way to map plain English economic concepts to Haver Analytics series codes?

Mapping plain English concepts to Haver Analytics codes is done by translating requests into CODE@DB formats while distinguishing between similar indicators and units. It asks for clarification on ambiguous requests instead of guessing incorrect series variants.

Can I route legacy IFS data requests to replacement IMF iData topic databases?

Yes, you can route legacy IFS requests to replacement iData topic databases. The Skill automatically routes requests to the correct source family, including handling legacy IMF requests by directing them to their replacement iData topic databases.

How does indicator lookup handle ambiguity between similar economic indicators and units?

Indicator lookup handles ambiguity by asking for clarification when requests are unclear. It distinguishes between similar indicators, units, transformations, and database families to ensure accurate, non-guessing identifier mapping and dimension preservation.

Does this identifier lookup approach support World Bank WDI and WTO data discovery?

Yes, this identifier lookup approach supports World Bank WDI and WTO data discovery. It applies multi-source routing to automatically direct requests to the correct source family based on the context of your research data discovery needs.