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economic-data-collector

Aggregate macroeconomic data from FRED, yield curves, central-bank rates, and the economic calendar into a SQLite database.

5|Updated Apr 8, 2026
Search Tags:#data-analysis#data-collection#central-banks#fred#economic-data#yield-curves
One-click install
npx skills add https://github.com/JansenAnalytics/claudex --skill economic-data-collector
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: economic-data-collector
Source: https://github.com/JansenAnalytics/claudex/tree/main/skills/economic-data-collector
Command: npx skills add https://github.com/JansenAnalytics/claudex --skill economic-data-collector

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, beautifulsoup4, cloudscraper, yfinance, tvdatafeed, and includes scripts (resource) components.

What problem does it solve?

Collects and queries macroeconomic data — yield curves, central bank policy rates, forex rate differentials, FRED US economic indicators (CPI, GDP, NFP, unemployment), and the economic calendar. Use when fetching, storing, or querying interest rates, bond yields, rate diffs, or economic releases for trading and forex analysis.

Core Features & Use Cases

  • Collects macroeconomic data from FRED, yield curves, central-bank rates, and the economic calendar into a centralized store for consistent analysis.
  • Provides queryable access to latest and historical indicators, rates, yields, and events to support trading, research, and dashboarding workflows.
  • Use Case: A trader pulls CPI, GDP, unemployment, and yield data to assess macro backdrop and inform position sizing and risk.

Quick Start

Ask Claudex to fetch macroeconomic data from FRED, yields, central-bank rates, and the calendar sources and load it into the local economic database.

Frequently Asked Questions about economic-data-collector

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

FAQPage Schema
How do I collect macroeconomic data like FRED indicators and yield curves into a single database?▼

You can collect macroeconomic data by aggregating FRED indicators, yield curves, and central-bank rates into a centralized SQLite-backed store. This provides consistent ingestion, queryable access, and optional data exports for analysis.

What is the best way to centralize central bank policy rates and economic calendar data for trading analysis?▼

Centralizing central bank policy rates and economic calendar data involves fetching series from multiple sources and storing them in a local database. This approach enables fast querying of historical indicators and upcoming events to inform trading workflows.

Can I query historical CPI and unemployment data alongside forex rate differentials using Python?▼

Yes, you can query historical CPI, unemployment data, and forex rate differentials using Python. The data collection framework supports retrieving these specific FRED economic indicators and storing them for contextual macroeconomic analysis.

Do I need to manually export macroeconomic data from yfinance and tvdatafeed to analyze rate differentials?▼

No, manual export is unnecessary. The framework uses yfinance and tvdatafeed to automatically ingest rate differentials and yield data directly into a local database, providing a consistent retrieval interface that eliminates manual extraction steps.

What macroeconomic data sources are supported for fetching bond yields and economic releases?▼

Supported macroeconomic data sources include FRED for US economic indicators, yield curves for bond yields, central-bank rates for policy decisions, and the economic calendar for tracking upcoming economic releases and market events.

How does error handling work when fetching economic data from multiple sources like FRED and yield curves?▼

Error handling during economic data fetching ensures that ingestion failures from sources like FRED or yield curves are caught and managed gracefully. This maintains database integrity and prevents incomplete data series from disrupting the retrieval interface.

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