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earnings-analysis

Generate multi-page equity research earnings update reports with hyperlinked citations.

34.1k|5.1k|Updated Feb 23, 2026
Search Tags:#report generation#financial analysis#earnings#SEC filings#equity research#data citation
One-click install
npx skills add https://github.com/anthropics/financial-services-plugins --skill earnings-analysis-anthropics
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-analysis
Source: https://github.com/anthropics/financial-services-plugins/tree/main/equity-research/skills/earnings-analysis
Command: npx skills add https://github.com/anthropics/financial-services-plugins --skill earnings-analysis-anthropics

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires python-docx, pandas, matplotlib, seaborn, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill automates the creation of detailed, professional equity research earnings update reports for companies already under coverage, significantly reducing the time and effort required for post-earnings analysis.

Core Features & Use Cases

  • Automated Report Generation: Creates 8-12 page reports analyzing quarterly results, focusing on beat/miss analysis, key metrics, updated estimates, and thesis impact.
  • Institutional Standards: Follows formats used by top financial institutions (JPMorgan, Goldman Sachs, Morgan Stanley).
  • Data Integration: Incorporates data from earnings releases, SEC filings, call transcripts, and consensus estimates.
  • Mandatory Citations: Ensures all data is properly cited with clickable hyperlinks to original sources.
  • Use Case: When a company like Apple releases its quarterly earnings, use this Skill to quickly generate a comprehensive update report for clients, highlighting key performance indicators, management commentary, and revised financial outlook.

Quick Start

Use the earnings-analysis skill to create an earnings update report for Microsoft's Q3 2024 results.

Frequently Asked Questions about earnings-analysis

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

FAQPage Schema
How do I automate equity research earnings report generation for quarterly results?▼

Automate equity research earnings report generation by processing quarterly results, beat/miss assessments, and key performance indicators to output a multi-page professional report with hyperlinked citations.

What is the best way to format an earnings update report to match institutional equity research standards?▼

To format an earnings update report to institutional equity research standards, this Skill applies formatting conventions used by top financial institutions like JPMorgan, Goldman Sachs, and Morgan Stanley to generate consistent 8-12 page reports.

How do I add hyperlinked citations to SEC filings and earnings call transcripts in a financial analysis report?▼

Add hyperlinked citations to SEC filings and call transcripts in a financial analysis report through the Skill's mandatory citation feature, which automatically embeds clickable links to original data sources like earnings releases and consensus estimates.

Does this earnings analysis tool require SEC filings and consensus estimates as input data?▼

This earnings analysis tool integrates data from SEC filings, earnings releases, call transcripts, and consensus estimates to comprehensively analyze quarterly results and their impact on the investment thesis.

Can I use Python data libraries like pandas and matplotlib for equity research report generation?▼

Yes, the equity research report generation process is built on Python data libraries including pandas, matplotlib, seaborn, and python-docx to process financial data and render visualizations within the report.

What are the limitations of using automated financial analysis for post-earnings update reports?▼

A limitation of automated financial analysis for post-earnings reports is that it is designed exclusively for companies already under coverage, focusing on quarterly updates rather than initiating new equity research coverage from scratch.

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