edgartools

Extract SEC EDGAR filings and financial data using the edgartools library.

Updated Feb 1, 2026

Search Tags:#analysis #investing #edgar #xbrl #financials #sec

Ready to run

npx skills add https://github.com/nferrer-dev/claude-dotfiles --skill edgartools-nferrer-dev

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: edgartools
Source: https://github.com/nferrer-dev/claude-dotfiles/tree/main/skills/edgartools
Command: npx skills add https://github.com/nferrer-dev/claude-dotfiles --skill edgartools-nferrer-dev

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires edgartools, and includes references (resource) components.

What problem does it solve?

This Skill solves the complexity of navigating the SEC EDGAR database by providing a structured, programmatic interface to access, analyze, and extract financial data from regulatory filings.

Core Features & Use Cases

Structured Data Extraction: Automatically parse 10-K, 10-Q, and 8-K filings into clean Python objects and DataFrames.
Financial Analysis: Perform multi-period financial statement analysis, including income statements, balance sheets, and cash flow statements.
Use Case: Quickly compare the revenue growth and operating margins of multiple companies over the last five years by stitching together XBRL data from their respective annual reports.

Quick Start

Use the edgartools skill to fetch the latest 10-K for Apple and extract its income statement as a dataframe.

Frequently Asked Questions about edgartools

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

FAQPage Schema

How do I extract structured financial data from SEC EDGAR filings?▼

SEC EDGAR XBRL data is parsed into structured Python objects and DataFrames, enabling automated extraction of financial statements, company profiles, and insider trading data across historical periods without manual HTML scraping.

What is the best way to analyze multi-period financial statements from SEC filings?▼

Multi-period financial statement analysis is performed by parsing XBRL data from 10-K and 10-Q filings into DataFrames, enabling direct comparison of income statements, balance sheets, and cash flows across historical periods.

Can I retrieve insider trading data and company profiles from SEC EDGAR programmatically?▼

Yes, SEC EDGAR insider trading data and company profiles can be retrieved programmatically using edgartools, which provides structured search operations to access historical filing data for financial analysis.

Does the edgartools library support parsing 8-K filings for financial analysis?▼

Yes, edgartools supports parsing 8-K filings alongside 10-K and 10-Q documents, converting these regulatory SEC filings into clean Python objects and DataFrames to facilitate structured financial data extraction and analysis.

How do I compare revenue growth across multiple companies using SEC XBRL data?▼

You compare revenue growth by stitching together XBRL data from multiple companies' annual reports, parsing 10-K filings into DataFrames to analyze income statements and operating margins across historical periods.

What are the limitations of using edgartools for SEC filing analysis?▼

Analysis using edgartools is constrained by the availability of structured XBRL data within the SEC EDGAR database, requiring the edgartools library for parsing operations and limiting retrieval to historical filing periods.