Fetch World Bank time-series data and export as JSON or CSV.
npx skills add https://github.com/joshuaroll/research-skills --skill stat-data-fetcher
Please help me install this Agent Skill. Skill: stat-data-fetcher Source: https://github.com/joshuaroll/research-skills/tree/main/skills/stat-data-fetcher Command: npx skills add https://github.com/joshuaroll/research-skills --skill stat-data-fetcher
This skill lets researchers retrieve accurate World Bank time-series data directly from the official API, eliminating manual data collection and the risk of misreporting.
Run the script to fetch GDP per capita for the US and FR in CSV format: python3 fetch_worldbank.py --indicator NY.GDP.PCAP.CD --country "US;FR" --date "2020:2022" --format csv
Also, search for indicators by keyword: python3 fetch_worldbank.py --search "inflation"
High-intent search queries and answers about installing and using this skill.
You can fetch World Bank time-series data by running a Python script with the requests library, specifying the indicator ID, country names or ISO3 codes, and a date range to retrieve verifiable economic metrics.
Yes, you can export World Bank statistical data to CSV or JSON formats. By specifying the desired output format in your script execution, the tool outputs structured records containing country, iso3, year, value, indicator, and unit.
To find the correct World Bank indicator ID for inflation, use the search functionality within the script. Passing the keyword "inflation" queries the World Bank API and returns matching indicator IDs for your data retrieval.
Yes, the World Bank data fetcher supports fuzzy country resolution. It accepts standard country names like France or USA, resolves them to their corresponding ISO3 codes, and retrieves the accurate country-level time-series data.
The best way to get verifiable economic metrics is to fetch time-series data directly from the official World Bank API. This approach eliminates manual data collection and the risk of misreporting from secondary sources.
Yes, you need the Python requests library installed in your environment. The solution relies on it to handle API queries, resolve fuzzy country names, and retrieve structured statistical data records over a specified date range.
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