data-fetcher
Fetch economic data from FRED, World Bank, BLS, OECD, and Yahoo Finance
Profile →npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-fetcher --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
What it does
Fetches data from major economic data APIs (FRED, World Bank, BLS, OECD, Yahoo Finance) and produces clean, documented Python code with error handling for data retrieval and formatting.
How it works
It guides the agent through API key setup checks, prompts the user for data needs, selects appropriate APIs, and then generates Python code that handles API keys from environment variables, includes error handling, data cleaning, and documentation of series definitions. It provides example functions for FRED and World Bank data, and includes sections for BLS, IMF, and other data fetchers with explicit function definitions and data processing steps. The code examples show how to fetch series, manage date ranges, join/merge results, and save outputs to CSV. The workflow emphasizes not hardcoding keys, using dotenv to load environment variables, and printing status messages during downloads.
When to use it
Useful for downloading macroeconomic indicators, building custom multi-source datasets, automating data updates, and fetching cross-country panel data.
What it can touch
The skill prescribes generating code that relies on environment variables for API keys (FRED_API_KEY, BLS_API_KEY) and uses libraries such as fredapi, wbdata, requests, imf-reader, pandas. It demonstrates data inputs like series_ids, indicators, and country lists, and outputs like DataFrames and CSV files. The exact function signatures and dependencies are shown in the examples.
Caveats
The skill includes optional keys (BLS) and notes about API limits (e.g., BLS 20-year window) and installation requirements (e.g., pip install fredapi, wbdata, imf-reader). It does not guarantee successful downloads for all series and relies on the user's environment for keys and network access.
# Data-Fetcher ## Purpose This skill helps economists fetch data from major economic data APIs including FRED (Federal Reserve Economic Data), World Bank, BLS (Bureau of Labor Statistics), OECD, and Yahoo Finance. It generates clean, documented Python code with proper error handling. ## When to Use - Downloading macroeconomic indicators - Building custom datasets from multiple sources - Automating
What does the data-fetcher skill do?
Fetch economic data from FRED, World Bank, BLS, OECD, and Yahoo Finance
How do I install it?
Run `npx skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill data-fetcher --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Auto-Empirical-Research-Skills, a repository with 3,244 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.