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earnings-analysis

Generate equity research earnings update reports with beat/miss analysis and source citations.

1|Updated Mar 5, 2026
Search Tags:#report generation#financial analysis#investor relations#valuation#earnings#equity research
One-click install
npx skills add https://github.com/smrik/ai-fund --skill earnings-analysis-smrik
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: earnings-analysis
Source: https://github.com/smrik/ai-fund/tree/main/skills/equity-research/skills/earnings-analysis
Command: npx skills add https://github.com/smrik/ai-fund --skill earnings-analysis-smrik

SYSTEM DOCUMENTATION & REQUIREMENTS

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

What problem does it solve?

This skill solves the challenge of rapidly synthesizing complex quarterly earnings data into professional, institutional-grade research reports that meet strict formatting and citation standards.

Core Features & Use Cases

  • Automated Report Generation: Produces 8-12 page earnings updates following industry-standard formats.
  • Beat/Miss Analysis: Quantifies revenue and EPS variances against consensus estimates with precision.
  • Source Verification: Ensures every figure and table is backed by mandatory, clickable hyperlinks to SEC filings and earnings materials.
  • Use Case: Use this when a company under coverage releases quarterly results to generate a comprehensive update including beat/miss analysis, updated financial estimates, and a revised investment thesis.

Quick Start

Use the earnings-analysis skill to generate a comprehensive quarterly update report for Apple based on the latest earnings release and transcript.

Frequently Asked Questions about earnings-analysis

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

FAQPage Schema
How do I generate an institutional equity research earnings update report?▼

To generate an equity research report, synthesize quarterly financial results and management commentary to produce an 8-12 page institutional-grade earnings update featuring beat/miss assessments, estimate revisions, and an updated investment thesis.

What is a beat/miss analysis in quarterly earnings reports?▼

A beat/miss analysis quantifies revenue and EPS variances against consensus estimates with precision. It evaluates whether quarterly financial results exceeded or fell short of market expectations within an institutional equity research report.

Does generating professional financial analysis reports require clickable hyperlinks to SEC filings?▼

Yes, generating professional financial analysis reports requires mandatory source verification with clickable hyperlinks. Every figure and table in the earnings update must be backed by direct links to SEC filings and earnings materials.

Can I use pandas and seaborn for investor relations report generation?▼

Yes, you can use pandas and seaborn for investor relations report generation. These dependencies support the data manipulation and visualization required to synthesize quarterly financial results into professional equity research reports.

What is the best way to structure an investment thesis after quarterly earnings?▼

The best way to structure an updated investment thesis is by synthesizing beat/miss assessments and revised financial estimates from quarterly earnings. This ensures the thesis reflects current management commentary and verified SEC filing data.

Are there limitations when automating valuation and estimate revisions for equity research?▼

A key limitation when automating valuation and estimate revisions is the strict requirement for data timeliness verification. The equity research process mandates that every synthesized figure must be validated against current SEC filings.

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