Retrieve Argentine macroeconomic time series from the BCRA Monetary Statistics API.
npx skills add https://github.com/gauss314/skills --skill bcra-macro
Please help me install this Agent Skill. Skill: bcra-macro Source: https://github.com/gauss314/skills/tree/main/skills/bcra-macro Command: npx skills add https://github.com/gauss314/skills --skill bcra-macro
This Skill solves the difficulty of manually tracking and aggregating hundreds of official Argentine macroeconomic series, providing a programmatic interface to the BCRA's monetary statistics.
Use the bcra-macro skill to fetch the historical daily data for the international reserves variable with ID 1 from 2020 to the present.
High-intent search queries and answers about installing and using this skill.
You can retrieve historical Argentine macroeconomic data using this Skill by querying the BCRA API to fetch daily time series for 638 national variables, including international reserves, exchange rates, and inflation, directly into pandas DataFrames.
Available indicators include interest rates, exchange rates, international reserves, and monetary aggregates. The Skill queries the BCRA API catalog of 638 national variables, supporting economic research and forecasting by providing paginated historical time series extraction.
Yes, this Skill automates cataloging and extraction of BCRA monetary statistics by querying the full catalog of 638 national variables and retrieving paginated historical time series, outputting cleaned data ready for pandas economic analysis.
Yes, this Skill supports long-term historical data retrieval for Base Monetaria analysis by fetching time series from the BCRA API over custom date ranges, automating the retrieval and cleaning of these specific monetary series for economic modeling.
The best way is using this Skill to programmatically fetch and clean official BCRA time series, retrieving specific variables like the IPC and Base Monetaria over your analysis period to analyze their correlation directly within your Python environment.
Limitations include the need to handle paginated data extraction for large historical requests and identifying the correct series ID among 638 available national variables to ensure accurate retrieval of the desired monetary statistics from the API.
jaechang-hitsQueries bioRxiv and medXxiv preprint servers REST API for metadata and PDFs.
KaranKathur06Convert raw tabular and time-series data into modeling-ready datasets with statistical analysis.
gauss314Retrieve macroeconomic time series data from the FRED API.
nferrer-devQuery the Federal Reserve Economic Data API for macroeconomic time series.
