
Options Payoff Curve
FreeVisualize options trades with interactive payoff charts.
Free · Opens the source repo
What Options Payoff Curve does
The Options Payoff Curve skill enables users to generate dynamic and interactive charts that visualize the financial outcomes of various options trading strategies. When a user shares a screenshot of an options position or describes a specific strategy, this skill automatically extracts relevant data such as strike prices, premiums, expiry dates, and the underlying asset. It can handle a wide range of strategies, including butterflies, spreads, straddles, and more, making it versatile for traders looking to analyze complex multi-leg options structures.
Once the necessary information is gathered, the skill computes the expected payoffs using established financial models, including the Black-Scholes formula. It then renders a detailed HTML widget that displays both the expiry payoff curve and the theoretical value curve, allowing users to see how their options positions will perform at expiration and under varying market conditions. The widget includes dynamic sliders for key parameters, enabling real-time adjustments and updates to the visualization.
This skill is particularly useful for traders who want to quickly assess potential profits and losses from their options trades, helping them make informed decisions based on current market data. By providing real-time statistics such as maximum profit, maximum loss, and breakeven points, users can gain insights into their positions and strategize accordingly.
Whether you're a seasoned options trader or just starting out, the Options Payoff Curve skill offers a powerful tool for visualizing and understanding the complexities of options trading.
When to use it
Use this skill when you need to analyze an options position or strategy, especially when sharing screenshots or specific details about trades.
When not to use it
This skill may not be suitable for users who are not familiar with options trading concepts or for those seeking a simple overview without interactive analysis.
What you can build with it
Analyzing a Butterfly Spread
User uploads a screenshot of a butterfly spread to visualize potential outcomes and risks.
Exploring a Straddle Strategy
User describes a straddle strategy and wants to see how changes in the underlying price affect profitability.
Evaluating an Iron Condor Position
User inputs details of an iron condor trade to understand maximum profit and loss scenarios.
How to install Options Payoff Curve
View source1. Install with the skills CLI
npx skills add himself65/finance-skills/options-payoff --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by himself65Options Payoff Curve Skill
Generates a fully interactive HTML widget (via visualize:show_widget) showing:
- Expiry payoff curve (dashed gray line) — intrinsic value at expiration
- Theoretical value curve (solid colored line) — Black-Scholes price at current DTE/IV
- Dynamic sliders for all key parameters
- Real-time stats: max profit, max loss, breakevens, current P&L at spot
Step 1: Extract Strategy From User Input
When the user provides a screenshot or text, extract:
| Field | Where to find it | Default if missing |
|---|---|---|
| Strategy type | Title bar / leg description | "custom" |
| Underlying | Ticker symbol | SPX |
| Strike(s) | K1, K2, K3... in title or leg table | nearest round number |
| Premium paid/received | Filled price or avg price | 5.00 |
| Quantity | Position size | 1 |
| Multiplier | 100 for equity options, 100 for SPX | 100 |
| Expiry | Date in title | 30 DTE |
| Spot price | Current underlying price (NOT strike) | middle strike |
| IV | Shown in greeks panel, or estimate from vega | 20% |
| Risk-free rate | — | 4.3% |
Critical for screenshots: The spot price is the CURRENT price of the underlying index/stock, NOT the strikes. Never default spot to a strike price value.
Current SPX reference price:
!`python3 -c "import yfinance as yf; print(f'SPX ≈ {yf.Ticker(\"^GSPC\").fast_info[\"lastPrice\"]:.0f}')" 2>/dev/null || echo "SPX price unavailable — check market data"`
Step 2: Identify Strategy Type
Match to one of the supported strategies below, then read the corresponding section in references/strategies.md.
| Strategy | Legs | Key Identifiers |
|---|---|---|
| butterfly | Buy K1, Sell 2×K2, Buy K3 | 3 strikes, "Butterfly" in title |
| vertical_spread | Buy K1, Sell K2 (same expiry) | 2 strikes, debit or credit |
| calendar_spread | Buy far-expiry K, Sell near-expiry K | Same strike, 2 expiries |
| iron_condor | Sell K2/K3, Buy K1/K4 wings | 4 strikes, 2 spreads |
| straddle | Buy Call K + Buy Put K | Same strike, both types |
| strangle | Buy OTM Call + Buy OTM Put | 2 strikes, both OTM |
| covered_call | Long 100 shares + Sell Call K | Stock + short call |
| naked_put | Sell Put K | Single leg |
| ratio_spread | Buy 1×K1, Sell N×K2 | Unequal quantities |
For strategies not listed, use custom mode: decompose into individual legs and sum their P&Ls.
Step 3: Compute Payoffs
Black-Scholes Put Price
d1 = (ln(S/K) + (r + σ²/2)·T) / (σ·√T)
d2 = d1 - σ·√T
put = K·e^(-rT)·N(-d2) - S·N(-d1)
Black-Scholes Call Price (via put-call parity)
call = put + S - K·e^(-rT)
Butterfly Put Payoff (expiry)
if S >= K3: 0
if S >= K2: K3 - S
if S >= K1: S - K1
else: 0
Net P&L per share = payoff − premium_paid
Vertical Spread (call debit) Payoff (expiry)
long_call = max(S - K1, 0)
short_call = max(S - K2, 0)
payoff = long_call - short_call - net_debit
Calendar Spread Theoretical Value
Calendar cannot be expressed as a simple expiry function — always use BS pricing for both legs:
value = BS(S, K, T_far, r, IV_far) - BS(S, K, T_near, r, IV_near)
For expiry curve of calendar: near leg expires worthless, far leg = BS with remaining T.
Iron Condor Payoff (expiry)
put_spread = max(K2-S, 0) - max(K1-S, 0) // short put spread
call_spread = max(S-K3, 0) - max(S-K4, 0) // short call spread
payoff = credit_received - put_spread - call_spread
Step 4: Render the Widget
Use visualize:read_me with modules ["chart", "interactive"] before building.
Required Controls (sliders)
Structure section:
- All strike prices (K1, K2, K3... as needed by strategy)
- Premium paid/received
- Quantity
- Multiplier (100 default, show for clarity)
Pricing variables section:
- IV % (5–80%, step 0.5)
- DTE — days to expiry (0–90)
- Risk-free rate % (0–8%)
Spot price:
- Full-width slider, range = [min_strike - 20%, max_strike + 20%], defaulting to ACTUAL current spot
Required Stats Cards (live-updating)
- Max profit (expiry)
- Max loss (expiry)
- Breakeven(s) — show both for two-sided strategies
- Current theoretical P&L at spot
Chart Specs
- X-axis: SPX/underlying price
- Y-axis: Total USD P&L (not per-share)
- Blue solid line = theoretical value at current DTE/IV
- Gray dashed line = expiry payoff
- Green dashed vertical = strike prices (K2 center strike brighter)
- Amber dashed vertical = current spot price
- Fill above zero = green 10% opacity; below zero = red 10% opacity
- Tooltip: show both curves on hover
Code template
Use this JS structure inside the widget, adapting pnlExpiry() and bfTheory() per strategy:
// Black-Scholes helpers (always include)
function normCDF(x) { /* Horner approximation */ }
function bsCall(S,K,T,r,sig) { /* standard BS call */ }
function bsPut(S,K,T,r,sig) { /* standard BS put */ }
// Strategy-specific expiry payoff (returns per-share value BEFORE premium)
function expiryValue(S, ...strikes) { ... }
// Strategy-specific theoretical value using BS
function theoreticalValue(S, ...strikes, T, r, iv) { ... }
// Main update() reads all sliders, computes arrays, destroys+recreates Chart.js instance
function update() { ... }
// Attach listeners
['k1','k2',...,'iv','dte','rate','spot'].forEach(id => {
document.getElementById(id).addEventListener('input', update);
});
update();
Step 5: Respond to User
After rendering the widget, briefly explain:
- What strategy was detected and how legs were mapped
- Max profit / max loss at current settings
- One key insight (e.g., "spot is currently 950 pts below the profit zone, expiring tomorrow")
Keep it concise — the chart speaks for itself.
Reference Files
references/strategies.md— Detailed payoff formulas and edge cases for each strategy typereferences/bs_code.md— Copy-paste ready Black-Scholes JS implementation with normCDF
Read the relevant reference file if you're unsure about payoff formula edge cases for a given strategy.
Frequently asked questions about Options Payoff Curve
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