options-payoff

himself65/finance-skills · updated Apr 8, 2026

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$npx skills add https://github.com/himself65/finance-skills --skill options-payoff
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summary

Generates a fully interactive HTML widget (via visualize:show_widget) showing:

skill.md

Options 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:

  1. What strategy was detected and how legs were mapped
  2. Max profit / max loss at current settings
  3. 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 type
  • references/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.

how to use options-payoff

How to use options-payoff on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add options-payoff
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/himself65/finance-skills --skill options-payoff

The skills CLI fetches options-payoff from GitHub repository himself65/finance-skills and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/options-payoff

Reload or restart Cursor to activate options-payoff. Access the skill through slash commands (e.g., /options-payoff) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

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Use Cases

User Story & Requirements Generation

Create detailed user stories, acceptance criteria, and feature specs

Example

Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios

Reduce spec writing time by 50%, ensure comprehensive coverage

Competitive Analysis

Research competitors, compare features, identify gaps

Example

Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities

Complete competitive research in 2 hours instead of 2 days

Roadmap Prioritization

Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs

Example

Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale

Make data-driven prioritization decisions faster

Stakeholder Communication

Draft PRDs, status updates, and stakeholder presentations

Example

Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement

Save 3-5 hours/week on communication overhead

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client
  • Access to product documentation and roadmap tools (Jira, Notion, etc.)
  • Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
  • Stakeholder contact information and communication channels

Time Estimate

30-60 minutes to see productivity improvements

Installation Steps

  1. 1.Install product management skill
  2. 2.Start with user story generation for known feature
  3. 3.Progress to competitive analysis: research 2-3 competitors
  4. 4.Use for roadmap prioritization: apply RICE/ICE scoring
  5. 5.Draft stakeholder communications and refine based on feedback
  6. 6.Build template library for recurring PM tasks
  7. 7.Share effective prompts with product team

Common Pitfalls

  • Not validating competitive research—verify facts before sharing
  • Accepting user stories without involving engineering team
  • Over-relying on frameworks without qualitative judgment
  • Not customizing outputs to company culture and communication style
  • Skipping stakeholder validation of generated requirements

Best Practices

✓ Do

  • +Validate research and competitive analysis with real data
  • +Collaborate with engineering when generating technical requirements
  • +Customize frameworks and templates to your company context
  • +Use skill for first drafts, refine with stakeholder input
  • +Document successful prompt patterns for PM tasks
  • +Combine AI efficiency with human judgment and intuition

✗ Don't

  • Don't publish competitive analysis without fact-checking
  • Don't finalize user stories without engineering review
  • Don't make prioritization decisions solely on AI scoring
  • Don't skip customer validation of generated requirements
  • Don't ignore company-specific context and culture

💡 Pro Tips

  • Provide context: company goals, constraints, customer feedback
  • Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
  • Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
  • Use skill for 70% generation + 30% customization to company needs

When to Use This

✓ Use When

Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.

✗ Avoid When

Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.

Learning Path

  1. 1Basic: user stories, feature specs, status updates
  2. 2Intermediate: competitive analysis, prioritization frameworks, PRDs
  3. 3Advanced: product strategy, go-to-market planning, OKR setting
  4. 4Expert: product vision, market positioning, business model innovation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.425 reviews
  • Chaitanya Patil· Dec 28, 2024

    Solid pick for teams standardizing on skills: options-payoff is focused, and the summary matches what you get after install.

  • Evelyn Khanna· Dec 24, 2024

    I recommend options-payoff for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Piyush G· Nov 19, 2024

    We added options-payoff from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Shikha Mishra· Oct 10, 2024

    options-payoff fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Sep 1, 2024

    I recommend options-payoff for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

  • Dhruvi Jain· Aug 20, 2024

    Useful defaults in options-payoff — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • Isabella Mehta· Jul 19, 2024

    options-payoff reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Gonzalez· Jul 15, 2024

    Keeps context tight: options-payoff is the kind of skill you can hand to a new teammate without a long onboarding doc.

  • Oshnikdeep· Jul 11, 2024

    options-payoff is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Benjamin Khan· Jun 14, 2024

    Keeps context tight: options-payoff is the kind of skill you can hand to a new teammate without a long onboarding doc.

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