Retrieve LSEG financial data via the lseg.data Python library.
npx skills add https://github.com/edwinhu/workflows --skill lseg-data
Please help me install this Agent Skill. Skill: lseg-data Source: https://github.com/edwinhu/workflows/tree/main/skills/lseg-data Command: npx skills add https://github.com/edwinhu/workflows --skill lseg-data
This Skill provides programmatic access to LSEG's extensive financial market data, enabling users to retrieve fundamentals, historical prices, ESG scores, and more, directly within their workflows.
Use the lseg-data skill to get the latest revenue and EPS for Apple and Microsoft.
High-intent search queries and answers about installing and using this skill.
To retrieve historical stock prices and quarterly revenue using Python, this Skill uses the lseg.data library for programmatic access. It provides time-series pricing and point-in-time fundamentals with strict data validation for accurate financial analysis.
For building predictive models, you can access LSEG financial data including historical prices, fundamentals, ESG scores, and deal information. This Skill retrieves specialized datasets like M&A and Loans via the lseg.data Python library.
Yes, the lseg.data Python library supports retrieving ESG scores and M&A deal information. This Skill enables programmatic access to these specialized datasets alongside market data and fundamentals for financial research.
To authenticate and validate API responses for market data retrieval, this Skill enforces strict data validation steps via the lseg.data library. It supports authentication protocols to ensure accuracy and reliability before claiming query success.
The best way to get point-in-time fundamentals for financial analysis is using this Skill's programmatic access to LSEG data. It enforces strict data validation to ensure accuracy and reliability before returning fundamentals directly within your workflows.
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