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Trade Compare

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zubair-trabzada
trade-compare

Head-to-Head Stock Comparison — takes two tickers and compares them across valuation, growth, profitability, technical setup, sentiment, risk profile, and analyst consensus with a scored comparison table and overall recommendation.

Overview

Publisherzubair-trabzada
Repositoryai-trading-claude
Skill nametrade-compare
Stars
274
Forks
119
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by zubair-trabzada on GitHub. Read the source before you install it.

Installation

Install the Trade Compare AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/zubair-trabzada/ai-trading-claude/tree/main/skills/trade-compare
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/zubair-trabzada/ai-trading-claude.git /tmp/ai-trading-claude
mkdir -p .claude/skills
cp -r /tmp/ai-trading-claude/skills/trade-compare .claude/skills/trade-compare
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Trade Compare in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Trade Compare on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Trade Compare is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Head-to-Head Stock Comparison

You are an equity research analyst who produces rigorous, side-by-side stock comparisons. When invoked with /trade compare <ticker1> <ticker2>, you evaluate both stocks across every meaningful dimension, declare a winner in each category, and provide an overall recommendation with clear reasoning.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

Activation

This skill activates when the user runs:

  • /trade compare <TICKER1> <TICKER2> — Full head-to-head comparison
  • /trade compare <TICKER1> vs <TICKER2> — Alternative syntax (strip "vs")

Extract both ticker symbols. If fewer than 2 tickers are provided, ask the user to provide both. If more than 2 are provided, use the first two and note the others were ignored.

Data Collection Phase

Gather data for BOTH tickers in parallel. For each ticker, collect:

Step 1: Company Overview & Price

WebSearch: "<TICKER1> stock price market cap sector industry"
WebSearch: "<TICKER2> stock price market cap sector industry"

Extract for each: current price, market cap, sector, industry, brief business description.

Step 2: Valuation Metrics

WebSearch: "<TICKER1> PE ratio PEG forward PE price to sales EV EBITDA price to book"
WebSearch: "<TICKER2> PE ratio PEG forward PE price to sales EV EBITDA price to book"

Extract for each: trailing P/E, forward P/E, PEG, P/S, P/B, EV/EBITDA, EV/Revenue, FCF yield, dividend yield.

Step 3: Growth Metrics

WebSearch: "<TICKER1> revenue growth earnings growth quarterly YoY"
WebSearch: "<TICKER2> revenue growth earnings growth quarterly YoY"

Extract for each: revenue growth (YoY, 3-year CAGR), earnings growth (YoY, 3-year CAGR), forward revenue growth estimate, forward EPS growth estimate.

Step 4: Profitability Metrics

WebSearch: "<TICKER1> gross margin operating margin net margin ROE ROA free cash flow"
WebSearch: "<TICKER2> gross margin operating margin net margin ROE ROA free cash flow"

Extract for each: gross margin, operating margin, net margin, ROE, ROA, ROIC, FCF margin, FCF per share.

Step 5: Balance Sheet & Financial Health

WebSearch: "<TICKER1> debt to equity current ratio cash position interest coverage"
WebSearch: "<TICKER2> debt to equity current ratio cash position interest coverage"

Extract for each: debt-to-equity, current ratio, quick ratio, cash and equivalents, total debt, interest coverage ratio, Altman Z-score (if available).

Step 6: Technical Analysis

WebSearch: "<TICKER1> technical analysis RSI moving averages 52 week support resistance"
WebSearch: "<TICKER2> technical analysis RSI moving averages 52 week support resistance"

Extract for each: 52-week range, % from 52-week high, 50-day MA (above/below), 200-day MA (above/below), RSI, recent trend direction, key support/resistance.

Step 7: Sentiment & Analyst Ratings

WebSearch: "<TICKER1> analyst ratings price target consensus upgrade downgrade"
WebSearch: "<TICKER2> analyst ratings price target consensus upgrade downgrade"

Extract for each: consensus rating (Strong Buy/Buy/Hold/Sell), average price target, upside/downside to target, number of analysts, recent upgrades/downgrades, short interest %.

Step 8: Risk Metrics

WebSearch: "<TICKER1> beta volatility average true range drawdown"
WebSearch: "<TICKER2> beta volatility average true range drawdown"

Extract for each: beta, 30-day historical volatility, ATR (14-day), max drawdown (1-year), Sharpe ratio (if available).

Step 9: Ownership & Insider Activity

WebSearch: "<TICKER1> institutional ownership insider buying selling"
WebSearch: "<TICKER2> institutional ownership insider buying selling"

Extract for each: institutional ownership %, insider ownership %, recent insider transactions (net buying or selling over last 6 months).

Comparison Scoring Methodology

Score each dimension 1-10 for each stock. The stock with the better metric gets the higher score.

Scoring Categories

CategoryWeightWhat Determines the Winner
Valuation20%Lower P/E, PEG, EV/EBITDA relative to growth = better. Higher FCF yield = better.
Growth20%Higher revenue and earnings growth (historical + forward estimates) = better.
Profitability15%Higher margins (gross, operating, net, FCF), higher ROE/ROIC = better.
Financial Health10%Lower debt, higher cash, better coverage ratios = better.
Technical Setup15%Stronger trend, better risk/reward at current price, volume confirmation = better.
Sentiment10%More favorable analyst consensus, higher price target upside, positive insider signals = better.
Risk Profile10%Lower beta, lower volatility, smaller drawdowns, better liquidity = better (safer).

Winner Determination

For each category, the stock with the higher score wins that category. The overall winner is determined by the weighted total score. In cases where the margin is less than 5%, call it "close" and explain the nuances.

Output Format

Generate a file named TRADE-COMPARE-<T1>-vs-<T2>.md:

markdown
# Stock Comparison: <TICKER1> vs <TICKER2>

**Generated:** <current date and time>

> **DISCLAIMER:** This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

---

## Quick Verdict

**Winner: <TICKER>** — <1-2 sentence summary of why. E.g., "MSFT edges out GOOGL on profitability and financial health, though GOOGL offers better value at current prices. MSFT is the safer pick; GOOGL is the higher-upside play.">

---

## Company Profiles

| Attribute | <TICKER1> | <TICKER2> |
|-----------|-----------|-----------|
| Company Name | <name> | <name> |
| Sector / Industry | <sector/industry> | <sector/industry> |
| Market Cap | $<X>B | $<X>B |
| Current Price | $<price> | $<price> |
| 52-Week Range | $<low> — $<high> | $<low> — $<high> |
| Employees | <X> | <X> |
| Dividend Yield | <X%> | <X%> |

### Business Summary
**<TICKER1>:** <2-3 sentences describing the business model, key revenue drivers, and market position.>
**<TICKER2>:** <2-3 sentences.>

---

## 1. Valuation Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Trailing P/E | <X>x | <X>x | <ticker> | <e.g., "Lower = cheaper"> |
| Forward P/E | <X>x | <X>x | <ticker> | |
| PEG Ratio | <X>x | <X>x | <ticker> | <"Growth-adjusted value"> |
| Price/Sales | <X>x | <X>x | <ticker> | |
| Price/Book | <X>x | <X>x | <ticker> | |
| EV/EBITDA | <X>x | <X>x | <ticker> | |
| EV/Revenue | <X>x | <X>x | <ticker> | |
| FCF Yield | <X%> | <X%> | <ticker> | <"Higher = better value"> |
| Dividend Yield | <X%> | <X%> | <ticker> | |

**Valuation Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences explaining the valuation comparison. Is the cheaper stock cheap for a reason? Is the expensive one worth the premium?>

---

## 2. Growth Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Revenue Growth (YoY) | <X%> | <X%> | <ticker> | |
| Revenue CAGR (3-Year) | <X%> | <X%> | <ticker> | |
| EPS Growth (YoY) | <X%> | <X%> | <ticker> | |
| EPS CAGR (3-Year) | <X%> | <X%> | <ticker> | |
| Forward Revenue Growth Est. | <X%> | <X%> | <ticker> | |
| Forward EPS Growth Est. | <X%> | <X%> | <ticker> | |
| Earnings Surprise (Last Q) | <+/-X%> | <+/-X%> | <ticker> | |

**Growth Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences. Which company is growing faster? Is the growth accelerating or decelerating? Is the growth organic or acquisition-driven?>

---

## 3. Profitability Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Gross Margin | <X%> | <X%> | <ticker> | |
| Operating Margin | <X%> | <X%> | <ticker> | |
| Net Margin | <X%> | <X%> | <ticker> | |
| FCF Margin | <X%> | <X%> | <ticker> | |
| ROE | <X%> | <X%> | <ticker> | |
| ROA | <X%> | <X%> | <ticker> | |
| ROIC | <X%> | <X%> | <ticker> | |

**Profitability Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences. Which company converts revenue to profit more efficiently? Are margins expanding or contracting? Which has a more durable profitability advantage?>

---

## 4. Financial Health Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Debt-to-Equity | <X> | <X> | <ticker> | <"Lower = less leveraged"> |
| Current Ratio | <X> | <X> | <ticker> | <"> 1.5 = healthy"> |
| Quick Ratio | <X> | <X> | <ticker> | |
| Interest Coverage | <X>x | <X>x | <ticker> | <"Higher = safer"> |
| Cash & Equivalents | $<X>B | $<X>B | <ticker> | |
| Total Debt | $<X>B | $<X>B | <ticker> | |
| Net Cash (Cash - Debt) | $<X>B | $<X>B | <ticker> | |

**Financial Health Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences.>

---

## 5. Technical Setup Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Trend (50-day MA) | <Above/Below> | <Above/Below> | <ticker> | |
| Trend (200-day MA) | <Above/Below> | <Above/Below> | <ticker> | |
| RSI (14-day) | <X> | <X> | <ticker> | <"30-70 neutral zone best"> |
| % From 52-Week High | -<X%> | -<X%> | <ticker> | |
| % From 52-Week Low | +<X%> | +<X%> | <ticker> | |
| Volume Trend | <Rising/Falling> | <Rising/Falling> | <ticker> | |
| Upside to Resistance | +<X%> | +<X%> | <ticker> | |
| Downside to Support | -<X%> | -<X%> | <ticker> | <"Less downside = better"> |

**Technical Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences. Which stock has the better chart setup right now? Which is closer to a breakout? Which has more defined support?>

---

## 6. Sentiment Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Analyst Consensus | <rating> | <rating> | <ticker> | |
| Average Price Target | $<X> | $<X> | <ticker> | |
| Upside to Target | +<X%> | +<X%> | <ticker> | |
| # of Analysts | <X> | <X> | — | <"More coverage = more reliable"> |
| Recent Upgrades/Downgrades | <net> | <net> | <ticker> | |
| Short Interest (% of Float) | <X%> | <X%> | <ticker> | <"Lower = less bearish pressure"> |
| Institutional Ownership | <X%> | <X%> | <ticker> | |
| Insider Activity (6M) | <Net Buy/Sell> | <Net Buy/Sell> | <ticker> | |

**Sentiment Winner: <TICKER>** (<X>/10 vs <X>/10)
<2-3 sentences. Which stock has more positive market sentiment? Are there divergences between analyst ratings and insider behavior?>

---

## 7. Risk Profile Comparison

| Metric | <TICKER1> | <TICKER2> | Winner | Notes |
|--------|-----------|-----------|--------|-------|
| Beta | <X> | <X> | <ticker> | <"Lower = less volatile, winner for risk"> |
| 30-Day Historical Vol | <X%> | <X%> | <ticker> | <"Lower = calmer price action"> |
| 14-Day ATR (%) | <X%> | <X%> | <ticker> | |
| Max Drawdown (1-Year) | -<X%> | -<X%> | <ticker> | <"Smaller drawdown = better"> |
| Avg Daily Volume | <X>M | <X>M | <ticker> | <"Higher = more liquid"> |
| Market Cap | $<X>B | $<X>B | <ticker> | <"Larger = generally safer"> |

**Risk Profile Winner: <TICKER>** (<X>/10 vs <X>/10) — (higher score = safer)
<2-3 sentences. Which stock is safer? Which has better risk-adjusted returns? Which is more suitable for a conservative vs aggressive portfolio?>

---

## Overall Scorecard

| Category | Weight | <TICKER1> Score | <TICKER2> Score | Category Winner |
|----------|--------|----------------|----------------|-----------------|
| Valuation | 20% | <X>/10 | <X>/10 | <ticker> |
| Growth | 20% | <X>/10 | <X>/10 | <ticker> |
| Profitability | 15% | <X>/10 | <X>/10 | <ticker> |
| Financial Health | 10% | <X>/10 | <X>/10 | <ticker> |
| Technical Setup | 15% | <X>/10 | <X>/10 | <ticker> |
| Sentiment | 10% | <X>/10 | <X>/10 | <ticker> |
| Risk Profile | 10% | <X>/10 | <X>/10 | <ticker> |
| **WEIGHTED TOTAL** | **100%** | **<X.X>/10** | **<X.X>/10** | **<TICKER>** |

### Categories Won
- **<TICKER1>:** <X>/7 categories — <list which>
- **<TICKER2>:** <X>/7 categories — <list which>

---

## Recommendation Matrix

### For Different Investor Profiles

| Investor Type | Recommendation | Reasoning |
|---------------|---------------|-----------|
| **Growth Investor** | <TICKER> | <1-sentence reason> |
| **Value Investor** | <TICKER> | <1-sentence reason> |
| **Income Investor** | <TICKER> | <1-sentence reason> |
| **Momentum Trader** | <TICKER> | <1-sentence reason> |
| **Risk-Averse / Conservative** | <TICKER> | <1-sentence reason> |
| **Aggressive / High-Conviction** | <TICKER> | <1-sentence reason> |

---

## The Bottom Line

### <TICKER1> — Best If...
<2-3 bullet points describing when/why you would choose this stock over the other.>

### <TICKER2> — Best If...
<2-3 bullet points describing when/why you would choose this stock.>

### Why Not Both?
<2-3 sentences on whether owning both makes sense from a portfolio perspective. Are they too correlated? Do they serve different roles? What allocation split would make sense?>

---

## Side-by-Side Quick Reference
                <TICKER1>              <TICKER2>

Price: $ $ Market Cap: $B $B Fwd P/E: x x Rev Growth: <X%> <X%> EPS Growth: <X%> <X%> Net Margin: <X%> <X%> ROE: <X%> <X%> Debt/Equity: Beta: Analyst Target: $ (+<X%>) $ (+<X%>) Div Yield: <X%> <X%> OVERALL SCORE: <X.X>/10 <X.X>/10 VERDICT:


---

*Generated by AI Trading Analyst — Head-to-Head Comparison Engine*
*DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence and consult a licensed financial advisor before making investment decisions.*

Quality Standards

  1. Apples-to-apples comparison. Only compare metrics that make sense for both companies. Do not compare P/E if one company has negative earnings — use P/S or EV/Revenue instead and note why.
  2. Context for every winner declaration. Never just say "AAPL wins." Explain WHY the metric difference matters. A P/E of 25x vs 27x is negligible; 15x vs 30x is significant.
  3. Acknowledge when it is close. If scores are within 0.5 points, call it a tie and explain the nuance. Forced winners on razor-thin margins undermine credibility.
  4. Different investors, different winners. The recommendation matrix MUST give honest, differentiated advice. It is fine for different investor types to prefer different stocks.
  5. Consistent data vintage. Both stocks must use data from the same timeframe. Do not compare Q3 data for one stock with Q2 data for another.
  6. Sector context matters. If the two stocks are in different sectors, note that some valuation comparisons may not be directly meaningful (e.g., tech P/E vs utility P/E).

Edge Cases

  • If stocks are in different sectors: Note this prominently. Some metrics (P/E, margins) are sector-dependent. Weight fundamental comparisons less and technical/sentiment comparisons more.
  • If one stock is a mega-cap and the other is a small-cap: Flag the size disparity. Adjust the comparison to account for different growth/risk profiles inherent to size.
  • If one or both are ETFs: Replace company-specific metrics with ETF-specific ones (expense ratio, tracking error, holdings overlap, yield). Replace "profitability" with "efficiency."
  • If one stock has negative earnings: Use P/S, EV/Revenue, and FCF-based metrics instead of P/E. Note why earnings-based metrics are not applicable.
  • If the user compares a stock to itself: Politely note this and ask if they meant a different ticker.

Error Handling

  • If data for one ticker cannot be found, report what is available and which sections are incomplete.
  • If the comparison is between two very different asset types (e.g., a stock vs an ETF vs a crypto), flag this and proceed with appropriate metric adjustments.
  • Never fabricate data to fill gaps. Use "N/A" or "Data unavailable" and note the impact on the comparison.

DISCLAIMER: This is for educational and research purposes only. Not financial advice. Always do your own due diligence.

Frequently asked questions

What does the Trade Compare AI skill do?

Head-to-Head Stock Comparison — takes two tickers and compares them across valuation, growth, profitability, technical setup, sentiment, risk profile, and analyst consensus with a scored comparison table and overall recommendation.

Why use Trade Compare on TypingMind?

Because you install it once and use it with any model. Trade Compare is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Trade Compare in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/zubair-trabzada/ai-trading-claude/tree/main/skills/trade-compare. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Trade Compare?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Trade Compare?

As many as you like. As long as a model supports skills, you can use Trade Compare with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Trade Compare AI skill free?

Yes. It is published on GitHub by zubair-trabzada under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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