imf-ra-catalog

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.