# InvestSkill Cookbook Practical examples, setup guide, and core concepts for getting the most out of InvestSkill. > πŸ“– [English](COOKBOOK.md) | [繁體中文](COOKBOOK-zh-TW.md) --- ## Table of Contents 1. [Setup Guide](#1-setup-guide) 2. [Core Concepts](#2-core-concepts) 3. [Demo Examples & Sample Output](#3-demo-examples--sample-output) - [Stock Evaluation](#31-stock-evaluation) - [DCF Valuation](#32-dcf-valuation) - [Financial Report Analysis](#33-financial-report-analysis) - [Research Bundle](#34-research-bundle) - [Technical Analysis](#35-technical-analysis) - [Portfolio Review](#36-portfolio-review) - [Earnings Call Analysis](#37-earnings-call-analysis) - [Dividend Analysis](#38-dividend-analysis) - [Chart Master](#39-chart-master) - [Full Report](#310-full-report) - [Result Validator](#311-result-validator) 4. [Practical Workflows](#4-practical-workflows) 5. [Cross-AI Usage](#5-cross-ai-usage) 6. [Tips & Best Practices](#6-tips--best-practices) --- ## 1. Setup Guide ### Prerequisites - [Claude Code](https://code.claude.com) installed (`npm install -g @anthropic-ai/claude-code`) - An active Anthropic API key ### Install InvestSkill (2 minutes) ```bash # Step 1: Open Claude Code claude # Step 2: Add the marketplace /plugin marketplace add yennanliu/InvestSkill # Step 3: Install the plugin /plugin install us-stock-analysis@invest-skill # Step 4: Verify installation /plugin list ``` You should see `us-stock-analysis` in the list with 21 available skills. ### Quick Test ```bash # Test with a stock you know /us-stock-analysis:stock-eval AAPL ``` If you see analysis output with a BULLISH/NEUTRAL/BEARISH signal block, you're ready to go. ### Local Development Setup ```bash # Clone the repository git clone https://github.com/yennanliu/InvestSkill.git cd InvestSkill # Open Claude Code in the project directory claude # Add local marketplace (use your actual path) /plugin marketplace add /path/to/InvestSkill # Install from local source /plugin install us-stock-analysis@invest-skill ``` ### Updating to the Latest Version ```bash # Remove the existing installation /plugin uninstall us-stock-analysis # Re-add marketplace (refreshes to latest version) /plugin marketplace add yennanliu/InvestSkill # Re-install /plugin install us-stock-analysis@invest-skill ``` --- ## 2. Core Concepts ### What InvestSkill Is InvestSkill is a collection of **structured analysis prompt frameworks** packaged as a Claude Code plugin. Each skill is a detailed instruction set that tells Claude Code exactly how to analyze a stock, interpret financial data, and present findings in a consistent format. Think of each skill as a **specialized analyst** you can summon with a command: | Command | What it does | |---------|-------------| | `/stock-eval AAPL` | Holistic evaluation: quality, valuation, moat, risk | | `/dcf-valuation NVDA` | Rigorous intrinsic value model with 3 scenarios | | `/stock-valuation MSFT` | Multi-method valuation: DCF + comps + EV multiples | | `/financial-report-analyst GOOGL 10-K` | Deep-read an annual filing, find red flags | | `/research-bundle TSLA` | Run all skills in sequence, synthesize into one thesis | | `/portfolio-review` | Analyze allocation, performance, and rebalancing needs | | `/earnings-call-analysis AMZN` | Parse tone, guidance, and key themes from earnings calls | | `/dividend-analysis JNJ` | Check dividend safety, growth, and sustainability | | `/chart-master AAPL` | Generate financial charts in Mermaid, ASCII, or HTML | | `/full-report MSFT` | Orchestrate all 15 modules into one HTML report | | `/result-validator` | Audit any analysis output and produce a confidence score | ### How Skills Work Each skill is defined by a `SKILL.md` file containing: 1. **Description** (frontmatter): One-line summary used by the plugin system 2. **Methodology**: Step-by-step analysis framework with tables, scoring, and formulas 3. **Output format**: Standardized sections Claude Code follows 4. **Signal block**: Required at the end of every analysis ``` plugins/us-stock-analysis/skills/ β”œβ”€β”€ stock-eval/SKILL.md β”œβ”€β”€ dcf-valuation/SKILL.md β”œβ”€β”€ stock-valuation/SKILL.md β”œβ”€β”€ financial-report-analyst/SKILL.md β”œβ”€β”€ chart-master/SKILL.md ← v1.6.0 β”œβ”€β”€ full-report/SKILL.md ← v1.6.0 └── ... (21 skills total) ``` ### The Signal Block Every InvestSkill analysis ends with a standardized signal block for quick decision-making: ``` ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH / NEUTRAL / BEARISH β•‘ β•‘ Confidence: HIGH / MEDIUM / LOW β•‘ β•‘ Horizon: SHORT / MEDIUM / LONG-TERM β•‘ β•‘ Score: X.X / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY / HOLD / SELL β•‘ β•‘ Conviction: STRONG / MODERATE / WEAK β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` **Score guide:** - 8.0–10.0 β†’ Strongly Bullish - 6.0–7.9 β†’ Moderately Bullish - 4.0–5.9 β†’ Neutral - 2.0–3.9 β†’ Moderately Bearish - 0.0–1.9 β†’ Strongly Bearish ### Universal Prompts (Cross-AI) Every skill is also available as a standalone prompt file in the `prompts/` directory. These work with **any AI assistant** β€” not just Claude Code: ``` prompts/ β”œβ”€β”€ stock-eval.md β”œβ”€β”€ dcf-valuation.md β”œβ”€β”€ stock-valuation.md β”œβ”€β”€ financial-report-analyst.md β”œβ”€β”€ chart-master.md β”œβ”€β”€ full-report.md └── ... (21 files) ``` Use them by copying the file content into any AI chat as a system prompt. --- ## 3. Demo Examples & Sample Output > **Note**: The outputs below are representative examples showing the format and depth of analysis. Actual outputs use real-time data and will differ. ### 3.1 Stock Evaluation **Command:** ```bash /us-stock-analysis:stock-eval MSFT ``` **Sample Output:** ``` # US Stock Evaluation β€” MSFT (Microsoft Corporation) ## Company Overview Microsoft is a diversified technology company with three major segments: - Intelligent Cloud (Azure, server products): 43% of revenue, highest growth - Productivity & Business Processes (Office 365, LinkedIn, Dynamics): 32% - More Personal Computing (Windows, Xbox, Surface): 25% Dominant moat: Azure platform lock-in, Office 365 subscription stickiness, enterprise relationships. Switching costs are extremely high across all segments. ## Financial Health Revenue Growth (5-yr CAGR): 15.8% Gross Margin: 70.1% (expanding: +180 bps YoY) Operating Margin: 44.6% (expanding: +120 bps YoY) FCF Margin: 37.2% Net Cash Position: $27.4B (net cash β€” fortress balance sheet) ## Valuation Metrics | Metric | Current | 1Y Ago | 5Y Avg | Sector Avg | |--------------|---------|--------|--------|------------| | P/E (FWD) | 32.4x | 28.1x | 30.2x | 26.8x | | EV/EBITDA | 24.1x | 21.5x | 22.8x | 18.4x | | EV/FCF | 41.2x | 37.8x | 36.5x | 28.1x | | Price/Sales | 12.8x | 10.9x | 11.6x | 7.2x | Premium to sector justified by: superior margin profile, cloud growth trajectory, AI optionality (Copilot, Azure OpenAI). ## Quality Scoring Piotroski F-Score: 8/9 (Strong β€” failed only on DTC/shares outstanding) ROIC: 28.4% WACC (estimated): 8.9% ROIC βˆ’ WACC Spread: +1,950 bps (significant value creation) ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: MEDIUM β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.2 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.2 DCF Valuation **Command:** ```bash /us-stock-analysis:dcf-valuation NVDA --scenarios ``` **Sample Output (condensed):** ``` # DCF Valuation β€” NVDA (NVIDIA Corporation) ## Base Metrics (TTM) Revenue: $122.0B FCF: $60.8B FCF Margin: 49.8% Net Cash: $38.5B SBC (TTM): $3.5B True FCF*: $57.3B Shares Outstanding: 24.4B *SBC-adjusted ## WACC Calculation Cost of Equity: Rf 4.4% + Ξ² 1.72 Γ— ERP 5.5% = 13.9% WACC: 13.8% ## Scenario Assumptions | Scenario | Probability | Rev CAGR Y1-5 | Rev CAGR Y6-10 | FCF Margin Y10 | Terminal g | |----------|-------------|---------------|----------------|----------------|------------| | Bull | 20% | 42% | 18% | 48% | 3.0% | | Base | 60% | 28% | 10% | 40% | 2.5% | | Bear | 20% | 12% | 5% | 28% | 1.5% | ## Intrinsic Value Results | Scenario | IV per Share | vs. Current ($875) | MoS | |----------|--------------|--------------------|----------| | Bull | $1,240 | +41.7% | Discount | | Base | $785 | βˆ’10.3% | Premium | | Bear | $320 | βˆ’63.4% | Premium | | Weighted | $768 | βˆ’12.2% | Premium | ## Sensitivity Table (Base Scenario, $ per share) Terminal Growth Rate WACC 1.5% 2.0% 2.5% 3.0% 3.5% 11.0% $910 $960 $1,020 $1,090 $1,180 12.0% $830 $875 $920 $975 $1,040 13.8% $710 $745 $785 $825 $875 ← Base Case 15.0% $625 $655 $685 $720 $760 ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: NEUTRAL β•‘ β•‘ Confidence: MEDIUM β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 5.8 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: HOLD β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.3 Financial Report Analysis **Command:** ```bash /us-stock-analysis:financial-report-analyst AAPL 10-K --section md&a ``` **Sample Output (condensed):** ``` # Financial Report Analysis β€” AAPL 10-K (FY2024) ## Document Orientation Filing Type: 10-K Annual Report (FY ended September 28, 2024) Auditor: Ernst & Young LLP β€” Unqualified Opinion Filed: October 25, 2024 (on time) Restatements: None ## Financial Health Dashboard β”Œβ”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”¬β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β” β”‚ Revenue Growth β”‚ +2.0% YoY ($391.0B) β”‚ β”‚ Gross Margin β”‚ 46.2% (vs. prior 44.1%, +210 bps) β”‚ β”‚ FCF Margin β”‚ 27.8% (conversion: 108%) β”‚ β”‚ Filing Quality Score β”‚ 9.2 / 10 β”‚ β””β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”΄β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”€β”˜ ## Key Red Flags β€’ China revenue declined 8% YoY β€” geopolitical and local competition risk (RISK: HIGH) β€’ EU Digital Markets Act compliance costs β€” structural margin risk (RISK: MEDIUM) ## Accounting Quality Score: 19/21 β€” High quality filing ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: HIGH β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.8 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.4 Research Bundle **Command:** ```bash /us-stock-analysis:research-bundle AMZN ``` **Sample Output (condensed):** ``` # Research Bundle β€” AMZN (Amazon.com, Inc.) ## Composite Scorecard | Component | Weight | Sub-Score | Contribution | |-----------------|--------|-----------|--------------| | Business Quality| 25% | 8.1 | 2.03 | | Valuation | 25% | 6.2 | 1.55 | | Market Signals | 20% | 7.5 | 1.50 | | Technical Setup | 15% | 6.0 | 0.90 | | Risk Profile | 15% | 8.0 | 1.20 | | COMPOSITE | 100% | 7.18/10 | | ## Investment Thesis Amazon's AWS recovery (re-accelerating to 19% growth) combined with the highest-margin advertising business scaling to $50B+ creates a powerful earnings leverage story over the next 3 years. ## Entry / Exit Strategy Ideal entry: $205–$215 (key support zone on pullback) Bull target: $275 | Base target: $250 | Stop loss: $195 ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: MEDIUM β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.2 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.5 Technical Analysis **Command:** ```bash /us-stock-analysis:technical-analysis TSLA --chart ``` **Sample Output (condensed):** ``` # Technical Analysis β€” TSLA (Tesla, Inc.) ## Trend Analysis Primary Trend: BEARISH (price below 200-day MA) Secondary Trend: NEUTRAL (consolidating above 50-day MA) MTF Alignment: MIXED β†’ proceed with caution ## Key Levels Support 1: $195 β€” Strong (tested 4x, accumulation zone) Resistance: $240 β€” Strong (prior breakdown point, now overhead) ## Indicator Signals | Indicator | Value | Signal | |----------------|----------|-----------| | RSI (14) | 48.2 | NEUTRAL | | MACD | βˆ’2.1 | NEUTRAL | | OBV | Declining| BEARISH | ## Trade Setup Entry: $197–$202 | Stop: $188 | Target 1: $240 (R/R: 1:3.5) ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: NEUTRAL β•‘ β•‘ Confidence: LOW β•‘ β•‘ Horizon: SHORT-TERM β•‘ β•‘ Score: 4.5 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: HOLD β•‘ β•‘ Conviction: WEAK β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.6 Portfolio Review **Command:** ```bash /us-stock-analysis:portfolio-review # Then paste your holdings as a list: # AAPL 18%, MSFT 15%, NVDA 12%, AMZN 10%, GOOGL 8%, BRK.B 7%, ... ``` **Sample Output (condensed):** ``` # Portfolio Review β€” Tech-Heavy Growth Portfolio (12 holdings) ## Executive Summary βœ… Strong long-term performance: +22.1% vs. S&P 500 +18.4% (3Y annualized) ⚠️ Concentration risk: Top 3 positions = 45% of portfolio (max recommended: 30%) ⚠️ Zero international exposure β€” significant geographic blind spot ⚠️ No dividend/income component β€” purely growth-oriented ## Performance Scorecard | Metric | Portfolio | S&P 500 | Delta | |--------------------|-----------|---------|--------| | YTD Return | +14.2% | +11.8% | +2.4% | | 1Y Return | +28.6% | +22.1% | +6.5% | | 3Y Annualized | +22.1% | +18.4% | +3.7% | | Sharpe Ratio | 1.42 | 1.18 | +0.24 | | Max Drawdown | βˆ’28.4% | βˆ’19.4% | βˆ’9.0% | | Beta | 1.35 | 1.00 | +0.35 | ## Asset Allocation vs. Target | Sector | Current | Target | Action | |--------------|---------|--------|--------------| | Technology | 68% | 40% | TRIM βˆ’28% | | Consumer Disc| 14% | 15% | HOLD | | Comm. Services| 10% | 10% | HOLD | | Healthcare | 0% | 10% | ADD +10% | | Financials | 0% | 10% | ADD +10% | | International| 0% | 15% | ADD +15% | | Cash | 8% | 5% | DEPLOY βˆ’3% | ## Holdings Review (Top 5) | Ticker | Weight | 1Y Return | Status | Note | |--------|--------|-----------|---------|-------------------------------| | AAPL | 18% | +12.4% | TRIM | Overweight; reduce to 10% | | MSFT | 15% | +31.2% | HOLD | Core position, justified | | NVDA | 12% | +89.4% | TRIM | Elevated after run; take 5% | | AMZN | 10% | +28.1% | HOLD | AWS recovery thesis intact | | GOOGL | 8% | +18.6% | HOLD | AI monetization optionality | ## Priority Action List 1. Trim AAPL from 18% β†’ 10% (tax-loss pair with any unrealized losses) 2. Trim NVDA from 12% β†’ 7% (lock in gains, reduce concentration) 3. Initiate VTI/VXUS for international diversification (~15%) 4. Add healthcare exposure via XLV or individual name (~10%) 5. Deploy 3% cash into financials (JPM or XLF) given rate environment ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: NEUTRAL β•‘ β•‘ Confidence: HIGH β•‘ β•‘ Horizon: MEDIUM-TERM β•‘ β•‘ Score: 5.5 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: HOLD (rebalance needed) β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.7 Earnings Call Analysis **Command:** ```bash /us-stock-analysis:earnings-call-analysis META Q4-2024 # Then paste the earnings call transcript ``` **Sample Output (condensed):** ``` # Earnings Call Analysis β€” META (Meta Platforms) Q4 2024 ## Sentiment Dashboard Overall Tone: POSITIVE (score: 7.8/10) Management Confidence: HIGH Guidance Quality: SPECIFIC (quantitative targets given) Analyst Reception: NEUTRAL-TO-POSITIVE (no hostile questioning) ## Key Themes (by frequency) | Theme | Mentions | Sentiment | Implication | |---------------------|----------|------------|--------------------------------------| | AI infrastructure | 34 | Very Bullish| Massive capex commitment ($60-65B) | | Reels monetization | 18 | Bullish | Engagement β†’ revenue conversion | | Llama adoption | 14 | Bullish | Developer ecosystem building | | Reality Labs losses | 9 | Cautious | $5B+ annual losses continue | | Regulatory risks | 7 | Neutral | EU DMA, FTC mentioned briefly | ## Guidance Analysis | Metric | Q1 2025 Guide | Consensus Est. | Beat/Miss | |-----------------|----------------|----------------|-----------| | Revenue | $36.5–$39.0B | $38.2B | In-line | | Capex | $60–65B (FY) | $52B | ABOVE | | DAU Growth | "continued growth" | +4% | Vague | ⚠️ Capex guide $8-13B above consensus β€” markets may react negatively short-term but signals long-term AI infrastructure investment conviction. ## Language Shift vs. Prior Quarter INCREASED mentions: "AI", "infrastructure", "efficiency" (+22 mentions combined) DECREASED mentions: "metaverse", "VR" (βˆ’14 mentions) β€” strategic pivot confirmed NEW language: "superintelligence", "AGI timeline" β€” CEO tone more ambitious ## Management Credibility Check Prior guidance accuracy: Q3 Revenue Guide: $38.5–$41.0B β†’ Actual: $40.6B βœ… (beat midpoint) Capex Guide (FY24): $37–40B β†’ Actual: $38.0B βœ… (on target) Credibility Score: 8.5/10 β€” Highly reliable guidance history ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: MEDIUM β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.0 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.8 Dividend Analysis **Command:** ```bash /us-stock-analysis:dividend-analysis JNJ ``` **Sample Output (condensed):** ``` # Dividend Analysis β€” JNJ (Johnson & Johnson) ## Dividend Profile Current Yield: 3.1% Annual Dividend: $4.96/share Consecutive Years: 62 years (Dividend King) 5Y Dividend CAGR: 5.8% Next Ex-Dividend Date: Approx. Feb 18 (quarterly) ## Safety Scorecard | Factor | Value | Assessment | |----------------------------|----------|---------------| | Payout Ratio (EPS) | 44.2% | SAFE (< 60%) | | Payout Ratio (FCF) | 38.8% | VERY SAFE | | Dividend / Net Income | 44% | Comfortable | | Debt/EBITDA | 1.2x | Low leverage | | Interest Coverage | 18.4x | Very strong | | FCF Growth (3Y CAGR) | +7.2% | Healthy | Dividend Safety Score: 9.1/10 β€” VERY SAFE ## Growth Trajectory Year Dividend YoY Growth 2020 $4.04 +5.7% 2021 $4.24 +5.0% 2022 $4.52 +6.6% 2023 $4.76 +5.3% 2024 $4.96 +4.2% 2025E $5.20E +4.8%E (projected) ## Risk Factors β€’ Litigation overhang: talc baby powder settlements β€” ongoing but ring-fenced β€’ MedTech segment growth slowing (orthopedics competition from Stryker) β€’ Spinoff of Kenvue (consumer health) reduces revenue diversification ## Peer Comparison (Dividend Yield vs. Safety) | Company | Yield | Safety Score | 5Y DGR | |---------|-------|--------------|--------| | JNJ | 3.1% | 9.1/10 | 5.8% | | ABT | 2.1% | 8.4/10 | 7.2% | | MDT | 3.5% | 7.8/10 | 4.1% | | PFE | 6.8% | 5.2/10 | 2.8% | JNJ offers the best safety-to-yield balance in healthcare. ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: HIGH β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.5 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.9 Chart Master **Command:** ```bash /us-stock-analysis:chart-master AAPL --type price-volume ``` **Sample Output:** ``` # Chart Master β€” AAPL Price + Volume (6-Month) ## Mermaid Chart (primary β€” renders in Claude Code, GitHub, Notion) xychart-beta title "AAPL β€” 6-Month Price & Volume" x-axis ["Aug", "Sep", "Oct", "Nov", "Dec", "Jan", "Feb"] y-axis "Price (USD)" 160 --> 240 bar [145, 138, 152, 168, 181, 175, 195] line [162, 155, 171, 184, 196, 188, 212] ## ASCII Chart (fallback β€” works in any terminal or plain text output) AAPL β€” 6M Price (Aug–Feb) 240 | * 220 | * * * 200 | * * 180 | * * * 160 | * * * * 140 | * * * * +------------------------------------------ Aug Sep Oct Nov Dec Jan Feb Volume Bars: HIGH β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–‘β–‘β–‘β–‘β–‘β–‘β–‘β–‘β–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆβ–ˆ Aug Sep Oct Nov Feb NOTE: β–ˆβ–ˆβ–ˆβ–ˆ = above avg volume | β–‘β–‘β–‘β–‘ = below avg ## Key Chart Observations β€’ Breakout above $195 resistance on above-average volume (Feb) β€” bullish confirmation β€’ Price crossed above 50-day MA in January β€” trend reversal signal β€’ Volume contraction during Oct–Nov pullback β€” healthy consolidation, not distribution β€’ Support zone: $178–$182 (tested twice, held both times) ## HTML Chart (interactive β€” paste into browser or export to report) ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: MEDIUM β•‘ β•‘ Horizon: SHORT-TERM β•‘ β•‘ Score: 6.8 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` **Other chart types you can request:** ```bash /chart-master NVDA --type fair-value-range # Bull/base/bear valuation bands /chart-master MSFT --type multi-factor-signal # Radar chart of 6 signal dimensions /chart-master AMZN --type revenue-breakdown # Bar chart of segment revenue /chart-master TSLA --type rsi-macd # Technical indicator dual-panel ``` --- ### 3.10 Full Report **Command:** ```bash /us-stock-analysis:full-report MSFT ``` **What it does:** The `full-report` skill orchestrates 15 analysis modules sequentially and saves a single professional HTML report to `output/MSFT-full-report.html`. ``` # Full Report β€” MSFT (Microsoft Corporation) Orchestrating analysis modules... βœ… 1/15 β€” Stock Evaluation (business quality, moat) βœ… 2/15 β€” Fundamental Analysis (income statement, balance sheet, FCF) βœ… 3/15 β€” DCF Valuation (3-scenario intrinsic value) βœ… 4/15 β€” Stock Valuation (comps, EV multiples, football field) βœ… 5/15 β€” Competitor Analysis (moat vs. peers: GOOGL, AMZN, CRM) βœ… 6/15 β€” Technical Analysis (trend, key levels, indicators) βœ… 7/15 β€” Earnings Call Analysis (last 2 quarters, tone delta) βœ… 8/15 β€” Insider Trading (Form 4 activity, 6 months) βœ… 9/15 β€” Institutional Ownership (13F changes, smart money) βœ… 10/15 β€” Short Interest (days-to-cover, squeeze risk) βœ… 11/15 β€” Options Analysis (implied vol, put/call, unusual activity) βœ… 12/15 β€” Dividend Analysis (yield, safety, growth) βœ… 13/15 β€” Economics Analysis (macro tailwinds/headwinds) βœ… 14/15 β€” Portfolio Impact (how MSFT fits a typical portfolio) βœ… 15/15 β€” Chart Master (price, valuation range, factor radar) Report saved to: output/MSFT-full-report.html Open: open output/MSFT-full-report.html ## Report Contents - Interactive Chart.js visualizations (price + volume, fair-value range) - Tabbed layout: Summary | Fundamentals | Valuation | Technicals | Risk - Printable PDF-ready styling - Signal blocks for each module + composite signal ## Composite Signal Across 15 modules: 9 BULLISH | 5 NEUTRAL | 1 BEARISH Weighted composite score: 7.1/10 ╔══════════════════════════════════════════════╗ β•‘ INVESTMENT SIGNAL β•‘ ╠══════════════════════════════════════════════╣ β•‘ Signal: BULLISH β•‘ β•‘ Confidence: HIGH β•‘ β•‘ Horizon: LONG-TERM β•‘ β•‘ Score: 7.1 / 10 β•‘ ╠══════════════════════════════════════════════╣ β•‘ Action: BUY β•‘ β•‘ Conviction: MODERATE β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ### 3.11 Result Validator **Command:** ```bash /us-stock-analysis:result-validator # Then paste any InvestSkill analysis output for auditing ``` **Use case:** Run this after any analysis to get a second opinion on whether the output is reliable. **Sample Output:** ``` # Result Validator β€” Auditing: NVDA DCF Valuation ## Audit Dimensions | Dimension | Score | Notes | |------------------------|-------|----------------------------------------------------| | Data Quality | 7/10 | Revenue/FCF sourced, WACC assumptions need cite | | Methodology Soundness | 8/10 | Standard 2-stage DCF, SBC adjustment done | | Signal Consistency | 6/10 | DCF says HOLD but narrative skews bullish β€” gap | | Risk Coverage | 7/10 | Downside scenarios present; tail risk underweighted| | Reasoning Transparency | 8/10 | Sensitivity table provided, terminal value % shown | ## Issues Found ⚠️ SIGNAL INCONSISTENCY: Score is 5.8/10 (Neutral/Hold) but analysis prose contains predominantly bullish language. Recommendation may be biased upward. ⚠️ DATA GAP: WACC beta of 1.72 is not sourced β€” 30-day beta vs. 5-year beta could shift IV by Β±$80/share. Verify input. ⚠️ RISK UNDERWEIGHT: Custom silicon risk from hyperscalers (Google TPU, Amazon Trainium) mentioned briefly but not quantified in bear case. Bear IV may be optimistic at $320. ## Adjustments Recommended β€’ Revise Action from HOLD to HOLD-with-caution (given signal-narrative gap) β€’ Re-run DCF with 5-year average beta (1.45) as sensitivity check β€’ Add hyperscaler chip risk scenario to bear case ## Confidence Score ╔═══════════════════════════════════════╗ β•‘ CONFIDENCE ASSESSMENT β•‘ ╠═══════════════════════════════════════╣ β•‘ Raw Score: 5.8 / 10 β•‘ β•‘ Adjusted Score: 5.2 / 10 β•‘ β•‘ Tier: MEDIUM β•‘ β•‘ Reliability: Use with caution β•‘ ╠═══════════════════════════════════════╣ β•‘ Recommendation: Re-verify WACC input β•‘ β•‘ before acting β•‘ β•šβ•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β•β• ``` --- ## 4. Practical Workflows Real-world investor scenarios showing how to combine multiple skills. --- ### Workflow A β€” Pre-Earnings Deep Dive **Scenario:** Earnings are in 3 days. You want to know if the setup is worth holding through. ```bash # Step 1: Check analyst expectations vs. historical beats /us-stock-analysis:earnings-call-analysis AAPL Q3-2024 # Look for: guidance accuracy track record, tone shift, beats/misses # Step 2: Scan options market for implied move /us-stock-analysis:options-analysis AAPL # Look for: implied volatility rank, straddle price, unusual put/call activity # Step 3: Check insider activity before lockout /us-stock-analysis:insider-trading AAPL # Look for: any CEO/CFO purchases or unusual sales in past 60 days # Step 4: Technical setup β€” is the stock at a good risk/reward level? /us-stock-analysis:technical-analysis AAPL # Look for: proximity to support/resistance, whether it's overbought into earnings # Decision matrix: # - Positive earnings tone history + low IV rank + insider buys + at support = Hold through # - Negative tone shift + high IV rank + insider sales + at resistance = Reduce before ``` --- ### Workflow B β€” Value Stock Screening **Scenario:** You found a stock that looks cheap on P/E. Is it a value trap or a genuine opportunity? ```bash # Step 1: Quality check first β€” cheap can stay cheap if the business is bad /us-stock-analysis:stock-eval INTC # Look for: Piotroski F-score, ROIC vs. WACC, moat assessment # Step 2: Understand why it's cheap /us-stock-analysis:competitor-analysis INTC # Look for: market share trends, moat erosion, competitive threats # Step 3: Read the last annual report for red flags /us-stock-analysis:financial-report-analyst INTC 10-K # Look for: risk factor changes, management tone, accounting quality # Step 4: Build the valuation with appropriate discount /us-stock-analysis:dcf-valuation INTC --scenarios # Use conservative assumptions β€” if it's still cheap, that's interesting # Step 5: Validate the output /us-stock-analysis:result-validator # Paste the DCF output β€” check if assumptions are defensible # Value trap signals: ROIC < WACC, moat eroding, FCF declining, management tone defensive # Genuine value signals: ROIC > WACC, short-term headwind, improving FCF, insider buying ``` --- ### Workflow C β€” Dividend Portfolio Construction **Scenario:** Building a dividend income portfolio and evaluating 3 candidates. ```bash # Evaluate each candidate for dividend safety and growth /us-stock-analysis:dividend-analysis JNJ /us-stock-analysis:dividend-analysis ABBV /us-stock-analysis:dividend-analysis PG # For each: note Safety Score, 5Y DGR, Payout Ratio, and Yield # Build a comparison table: # Ticker | Yield | Safety | 5Y DGR | Payout Ratio | Decision # JNJ | 3.1% | 9.1 | 5.8% | 38% | Core # ABBV | 4.2% | 7.2 | 8.1% | 52% | Satellite # PG | 2.5% | 9.4 | 5.2% | 61% | Core # Check portfolio-level impact /us-stock-analysis:portfolio-review # Add the 3 positions and see how they affect overall yield and sector balance # Tip: Target portfolio yield of 3%+ with average Safety Score > 7.5 ``` --- ### Workflow D β€” Swing Trade Setup **Scenario:** Looking for a short-term technical trade with defined risk. ```bash # Step 1: Screen for short squeeze potential /us-stock-analysis:short-interest GME # Look for: short float > 20%, days-to-cover > 5, borrow rate rising # Step 2: Confirm with technicals /us-stock-analysis:technical-analysis GME # Look for: price above 20-day MA, RSI recovering from oversold, volume surge # Step 3: Options setup for defined risk /us-stock-analysis:options-analysis GME # Look for: call skew, low-cost entry strikes, OI building above current price # Step 4: Visualize the setup /us-stock-analysis:chart-master GME --type price-volume # Look for: breakout pattern, volume confirmation # Trade structure: long call or call spread to cap risk to premium paid # Exit: price target (resistance) or time stop (2-4 weeks max for swing) ``` --- ### Workflow E β€” Full Investment Memo (1-command) **Scenario:** You want a complete investment memo for a stock before a significant position. ```bash # One command β€” produces a full HTML report with all 15 analysis modules /us-stock-analysis:full-report NVDA # Opens as: output/NVDA-full-report.html # Includes: all signal blocks, interactive charts, football field valuation, # sector comparison, risk matrix, entry/exit strategy # After reading, validate the composite output: /us-stock-analysis:result-validator # Paste the composite signal block β€” get a confidence score and any gaps flagged ``` --- ### Workflow F β€” Macro-Driven Sector Rotation **Scenario:** Rates are rising and you want to understand which sectors benefit. ```bash # Step 1: Understand current macro regime /us-stock-analysis:economics-analysis # Look for: yield curve shape, Fed language, leading indicators, inflation trend # Step 2: Identify which sectors historically outperform in this environment /us-stock-analysis:sector-analysis # Look for: rate-sensitive vs. rate-beneficiary sectors, relative strength # Step 3: Pick a stock within the favored sector /us-stock-analysis:stock-eval JPM # Financials benefit from higher rates /us-stock-analysis:stock-eval XOM # Energy benefits from inflation regime # Step 4: Check the portfolio impact of the rotation /us-stock-analysis:portfolio-review # Paste current holdings β€” see if adding JPM/XOM reduces rate sensitivity ``` --- ## 5. Cross-AI Usage InvestSkill works with any AI assistant. The `prompts/` directory contains all 21 analysis frameworks as standalone files. ### Gemini CLI ```bash # GEMINI.md is automatically loaded by Gemini CLI cd /path/to/InvestSkill gemini # Reference a prompt directly > @prompts/stock-valuation.md Analyze AAPL using all valuation methods # Paste a 10-K section for analysis > @prompts/financial-report-analyst.md > [paste your 10-K text here] # Generate a chart > @prompts/chart-master.md Create a fair-value range chart for NVDA ``` ### GitHub Copilot The `.github/copilot-instructions.md` file is automatically loaded as workspace context. ``` # In Copilot Chat (VSCode or github.com) Analyze NVDA using the stock-valuation framework # Reference a specific prompt Use the framework in @workspace /prompts/dcf-valuation.md to value MSFT # Portfolio review Use @workspace /prompts/portfolio-review.md to evaluate this portfolio: [paste holdings] ``` ### Cursor The `.cursor/rules/invest-skill.mdc` file is auto-applied in Cursor. ``` # Cursor AI Chat @prompts/fundamental-analysis.md Analyze GOOGL's financial statements # Or just ask naturally β€” Cursor knows the frameworks Run a DCF valuation of AMZN using the InvestSkill methodology # Full report @prompts/full-report.md Generate a complete investment report for TSLA ``` ### Any AI (ChatGPT, Claude.ai, etc.) ```bash # 1. Copy the content of any prompt file cat prompts/stock-eval.md | pbcopy # macOS # 2. Paste into any AI chat as a system prompt or at conversation start # 3. Ask your question "Analyze AAPL using this framework" ``` --- ## 6. Tips & Best Practices ### Getting Better Results **Be specific about the company and context:** ```bash # Good /stock-eval NVDA # Clear ticker /dcf-valuation MSFT --scenarios # With flag for richer output # Even better β€” add context /financial-report-analyst AAPL # Then paste the actual 10-K text /earnings-call-analysis META # Then paste the transcript ``` **Chain skills for deeper analysis:** ```bash # Step 1: Get the fundamentals /fundamental-analysis MSFT # Step 2: Value the business /dcf-valuation MSFT --scenarios # Step 3: Check competitive position /competitor-analysis MSFT # Step 4: Validate the output /result-validator # paste the analysis β€” catch gaps before acting # Step 5: Or run everything at once /research-bundle MSFT # Or generate a full HTML report: /full-report MSFT ``` ### Choosing the Right Skill | Your Question | Best Skill | |---------------|-----------| | "Is this stock cheap or expensive?" | `/dcf-valuation` + `/stock-valuation` | | "Is this a good business?" | `/stock-eval` + `/competitor-analysis` | | "What's in this earnings report?" | `/financial-report-analyst` | | "What did management say on the call?" | `/earnings-call-analysis` | | "What are insiders doing?" | `/insider-trading` | | "Is this dividend safe?" | `/dividend-analysis` | | "Where is the stock technically?" | `/technical-analysis` | | "Full deep-dive before I invest" | `/research-bundle` or `/full-report` | | "Is this a squeeze candidate?" | `/short-interest` | | "Is my portfolio balanced?" | `/portfolio-review` | | "Can I trust this analysis?" | `/result-validator` | | "I need a chart for my report" | `/chart-master` | ### Interpreting Signal Scores The 0–10 score is a composite that should be used as **one input**, not a definitive answer: - **Score 8+**: Strong conviction. Multiple signals aligned. Still requires risk management. - **Score 6–8**: Moderate conviction. Mostly positive with some concerns. Appropriate for normal position sizing. - **Score 4–6**: Neutral. Mixed signals. Consider waiting for clarity or reducing position size. - **Score 2–4**: Bearish lean. More concerns than positives. Avoid new long positions. - **Score < 2**: Strong bear case. Multiple red flags. Consider avoiding or hedging. ### Using with Real Financial Data For best results, provide the AI with actual data: 1. **Paste financial statements** from the company's IR page 2. **Attach 10-K/10-Q PDFs** when using the `financial-report-analyst` skill 3. **Provide specific numbers** (revenue, margins, share count) for DCF accuracy 4. **Reference earnings call transcripts** with the `earnings-call-analysis` skill 5. **Give your holdings list** when running `portfolio-review` ### Validating AI-Generated Analysis AI analyses can contain plausible-sounding but incorrect assumptions. Best practices: - Always run `/result-validator` after a DCF or complex valuation - Cross-check key numbers (revenue, margins) against the company's actual filings - Treat a HIGH confidence score as "worth acting on with normal sizing" β€” not a guarantee - When scores are 4–6 (Neutral), the AI is genuinely uncertain β€” match your conviction to that --- ## Disclaimer InvestSkill provides educational analysis frameworks only. Nothing in this project constitutes financial advice. All outputs are AI-generated analyses based on the methodologies embedded in the skills β€” they are not guarantees of future performance. Always consult a qualified financial advisor before making investment decisions.