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Earnings Analysis

Earnings Recap

Professional earnings report analysis skill for real-time analysis of publicly listed company quarterly financial data. Compare actual performance vs analyst expectations and assess investment value. Use when provided with financial data, earnings results, metric comparisons, or analysis requests for earnings quality, cash flow health, and debt risk. Suitable for investment analysts, fund managers, equity researchers, and investors interested in company fundamentals.

Reviewed by AlphioUpdated 26 days ago<1 min setup

Overview

Analyzes quarterly earnings across 6 dimensions — revenue quality, profitability, cash flow health, debt, shareholder returns, and market reaction — benchmarking actuals against analyst expectations with a structured beat/miss table.

Analyzes quarterly earnings across 6 dimensions — revenue quality, profitability, cash flow health, debt, shareholder returns, and market reaction — benchmarking actuals against analyst expectations with a structured beat/miss table.

Skill.md

How this skill works

Professional earnings report analysis skill for real-time analysis of publicly listed company quarterly financial data. Compare actual performance vs analyst expectations and assess investment value. Use when provided with financial data, earnings results, metric comparisons, or analysis requests for earnings quality, cash flow health, and debt risk. Suitable for investment analysts, fund managers, equity researchers, and investors interested in company fundamentals.

SKILL.mdALPHIO / VERIFIED

Earnings Recap - Professional Earnings Analysis Skill

This skill framework is designed for professional analysis of public company quarterly financial reports. Following standard financial analyst methodologies and dimensions, it performs in-depth analysis of financial data to generate structured investment analysis reports.

Analysis Framework

1. Revenue Analysis 💰

Analyze revenue quality and growth drivers

  • Year-over-year growth rate: Growth compared to the same period last year
  • Quarter-over-quarter growth: Growth trend compared to the previous quarter
  • Guidance changes: Whether management raised or lowered guidance for next quarter/full year
  • Revenue composition: Revenue breakdown and growth rates by product/geography/business line
  • vs. expectations: Actual revenue vs analyst consensus, calculate beat/miss magnitude

Key questions: Is growth sustainable? Does it come from core business or one-time items?


2. Profitability Analysis 📊

Gross Margin Trends

  • Gross margin YoY and QoQ changes
  • Reasons for margin improvement/deterioration (cost pressure, product mix, pricing power)
  • Comparison with industry average

Operating Profit

  • Operating margin YoY changes
  • Control of R&D and SG&A expenses
  • Operating leverage evidence

Net Income Quality

  • Net income vs operating profit: impact of non-recurring items
  • Profit growth vs revenue growth
  • Deviation analysis vs expectations

Key questions: Is profit growth sustainable? Does it depend on one-time items? Is gross margin under pressure?


3. Cash Flow Health 💧

Operating Cash Flow

  • Operating cash flow YoY growth
  • Operating cash flow vs net income comparison (quality metric)
  • Impact of receivables/payables changes on cash flow

Capital Expenditure

  • CapEx as a percentage of revenue
  • Free cash flow (FCF = Operating Cash Flow - CapEx) growth

Cash Conversion Cycle

  • Changes in inventory and accounts receivable cycles
  • Working capital increases/decreases

Key questions: Are profits converting to cash? Is free cash flow sufficient? Is the cash structure healthy?


4. Debt & Financial Health 🔒

  • Debt scale: Total debt and net debt YoY changes
  • Debt ratios:
    • Leverage ratio (Net Debt/EBITDA)
    • Debt-to-equity ratio
    • Interest coverage ratio
  • Debt quality: Short-term vs long-term debt, maturity profile
  • Cash position: Cash and equivalents vs short-term debt

Key questions: Is debt level manageable? Is debt repayment capacity sufficient? Any signs of deleveraging?


5. Shareholder Returns 📈

  • Earnings per share (EPS): Actual EPS vs expectations, YoY growth
  • Dividend situation: Payout ratio, dividend changes, sustainability
  • Share buybacks: Buyback amount, share count impact on EPS
  • Return on equity (ROE): Whether improving

Key questions: How is management allocating capital? Is the return policy shareholder-friendly?


6. Key Financial Metrics Benchmark 🎯

MetricActualExpectationYoYQoQAssessment
Revenue----Beat/In Line/Miss
Gross Margin----↑/→/↓
Operating Margin----↑/→/↓
Net Income----Beat/In Line/Miss
Operating Cash Flow-----
Free Cash Flow-----
Leverage Ratio----Improving/Deteriorating

7. Market Reaction & Investment Recommendation 🚀

Market Reaction Assessment

  • Stock price reaction (after-hours movement) is it reasonable?
  • Relative performance vs peers
  • Institutional investor sentiment changes

Catalyst Identification

  • Positive catalysts: What drives future growth
  • Risk factors: Key risk points
  • Guidance insight: Management's outlook on the future

Investment Conclusion

  • Valuation assessment: PE/PB vs historical and industry averages
  • Growth prospects: Expected growth for next 2-3 quarters
  • Recommendation level: Rationale for Buy/Hold/Sell

Analysis Framework Workflow

Step 1: Quick Data Summary (Executive Summary)

3-5 sentence quick summary of quarterly highlights: revenue performance, profit performance, cash flow, debt changes

Step 2: Detailed Financial Benchmark

Build a key metrics comparison table as shown above, clearly display Beat/Miss

Step 3: In-Depth Dimensional Analysis

Analyze each of the 6 dimensions sequentially, 1-2 paragraphs per dimension, including:

  • Key data points
  • YoY/QoQ changes
  • Root cause analysis
  • Trend assessment

Step 4: Market Reaction Assessment

  • After-hours reaction reasonableness
  • Peer comparison
  • Future driving factors

Step 5: Investment Recommendation

  • Clear Buy/Hold/Sell judgment
  • Key risk warnings
  • Target price (if sufficient data available)
  • Metrics to monitor

Output Guidelines

Do:

  • Use tables to clearly display data comparisons
  • Highlight key data points and inflection points
  • Provide objective cause analysis rather than subjective judgment
  • Clearly state data sustainability
  • Use symbols like "↑/→/↓" to quickly convey trends

Don't:

  • Pile up lengthy paragraphs; should be concise and efficient
  • Make unfounded emotional judgments
  • Overlook risk factors
  • Over-interpret single metrics
  • Miss YoY/QoQ comparisons

Analysis Template

When users provide financial data, output following this structure:

# [Company Name] Q[X] Earnings Analysis

## 📌 Executive Summary
[3-5 key points]

## 📊 Key Metrics Benchmark
[Table format]

## 💰 Revenue Analysis
[Specific data + trends + assessment]

## 📈 Profitability Analysis
[Gross margin / operating margin / net profit analysis]

## 💧 Cash Flow Analysis
[Operating / investing / free cash flow analysis]

## 🔒 Debt & Financial Health
[Debt data + repayment capacity analysis]

## 📈 Shareholder Returns
[EPS / dividend / buyback analysis]

## 🚀 Market Reaction & Outlook
[Stock reaction + future catalysts + investment recommendation]

## ⚠️ Key Risk Warnings
[Risk factors to monitor]

Skill Trigger Prompts

This skill is triggered when users provide scenarios like:

  • "Analyze company XX Q3 earnings"
  • "How is this company's quarterly report?"
  • "Revenue growth beat expectations, but profit declined, why?"
  • "Assess the investment value of this financial data"
  • "How are cash flow and debt levels?"
  • "Performance compared to last year same period?"
  • "What does this guidance change mean?"

Data Requirements Checklist

If user hasn't provided complete data, request by priority:

  1. Essential: Revenue, net income, EPS (need at least actual and expected values)
  2. Important: Gross margin, operating profit, operating cash flow, total debt
  3. Useful: Operating expenses, capital expenditure, dividend info, next quarter guidance
  4. Reference: Peer comparison data, historical trend data

Analysis Quality Indicators

A good Earnings Recap analysis should have:

Data Accuracy

  • All metrics in comparison tables are accurate
  • Beat/miss calculations are correct
  • Percentage changes are calculated correctly

Logical Coherence

  • Clear connections between data points (e.g., why margin decline affects profit growth)
  • Problem diagnosis is evidence-based, not speculative
  • Cause-effect relationships are explicit

Completeness

  • Covers all 6 dimensions (even if some data is missing)
  • Presents both strengths and risk warnings
  • Includes action items for follow-up

Actionability

  • Clear investment recommendation (Buy/Hold/Sell)
  • Key risks marked with ⭐ severity rating
  • Follow-up metrics to monitor are specific

Best used for

When to use it

Professional earnings report analysis skill for real-time analysis of publicly listed company quarterly financial data. Compare actual performance vs analyst expectations and assess investment value. Use when provided with financial data, earnings results, metric comparisons, or analysis requests for earnings quality, cash flow health, and debt risk. Suitable for investment analysts, fund managers, equity researchers, and investors interested in company fundamentals.

01 · PRE-MEETING

Prepare a decision brief

Post-earnings deep dives, comparing actual results vs consensus, assessing earnings quality and cash conversion, and turning a fresh earnings release into a clear Buy/Hold/Sell view.

02 · TEAM WORKFLOW

Standardize handoffs

Create consistent research outputs across analysts, portfolio managers, and agents.

03 · LIVE UPDATE

Refresh the thesis

Update scenarios after a new catalyst, KPI release, or earnings result.

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