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Timmy6942025
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earnings-analysis

Generate equity research earnings update reports from earnings releases, 10-Q filings, and call transcripts.

3|Updated May 30, 2026
Search Tags:#report generation#financial modeling#data analysis#equity research#earnings analysis
One-click install
npx skills add https://github.com/Timmy6942025/open-financial-agents --skill earnings-analysis-timmy6942025
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-analysis
Source: https://github.com/Timmy6942025/open-financial-agents/tree/main/src/agent-skills/earnings-reviewer/skills/earnings-analysis
Command: npx skills add https://github.com/Timmy6942025/open-financial-agents --skill earnings-analysis-timmy6942025

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This Skill automates the creation of professional equity research earnings update reports, significantly reducing the time and effort required to produce detailed analyses.

Core Features & Use Cases

  • Automated Report Generation: Quickly generate 8-12 page earnings update reports based on quarterly results.
  • Customizable Output: Customize the report length, word count, tables, and figures to fit specific requirements.
  • Use Case: Imagine you need an earnings update for a covered company. Use this Skill to create a comprehensive analysis, including beat/miss analysis, key metrics, updated estimates, and revised thesis in just a few steps.

Quick Start

Use the earnings-analysis skill to generate an earnings update report for [Company] Q3 2024.

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 update reports after a quarterly release?▼

Automating equity research earnings update reports requires processing data from 10-Q filings, earnings releases, and call transcripts. This Skill generates 8-12 page institutional-standard reports within 24-48 hours of an earnings release using Python and DOCX.

What data do I need to generate an earnings analysis report with beat/miss metrics?▼

Earnings analysis report generation requires data from earnings releases, 10-Q filings, and earnings call transcripts. It uses this data to produce comprehensive analyses including beat/miss analysis, key metrics, updated estimates, and revised thesis.

Can I customize the length and charts of an automated earnings update report?▼

Customizing earnings update reports is supported by this Skill, allowing you to adjust the report length, word count, tables, and figures. It utilizes Python libraries like pandas, matplotlib, and seaborn for data analysis and chart generation.

Does the report generation process require Python dependencies like pandas and matplotlib?▼

Report generation requires Python dependencies including pandas, matplotlib, and seaborn for chart generation, alongside python-docx for creating the final document. These libraries automate the financial modeling and data analysis visualization tasks.

What is the best way to create institutional-standard earnings reports for covered companies?▼

Creating institutional-standard earnings reports for companies already under coverage is best achieved by automating the creation process. This Skill leverages Python and DOCX capabilities to produce professional financial modeling and equity research outputs quickly.

Are there limitations when generating earnings update reports for companies not under coverage?▼

Earnings update report generation is specifically designed for companies already under coverage. Attempting to generate reports for uncovered companies may limit the accuracy of updated estimates and revised thesis components due to missing baseline financial modeling data.

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