Finance Skills is a collection of agent skills for financial analysis and trading, covering activities such as company valuation, earnings research, market analysis, and options calculations. It is for users who want coding agents to perform structured finance workflows, and the catalogue contains its skills, plugins, instructions, and MCP integration.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add himself65/finance-skills --skill options-payoffgit clone --depth 1 https://github.com/himself65/finance-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/himself65/finance-skills/options-payoff)<a href="https://agentmods.dev/skills/himself65/finance-skills/options-payoff"><img src="https://agentmods.dev/badge/skills/himself65/finance-skills/options-payoff/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/himself65/finance-skills/options-payoff"><img src="https://agentmods.dev/badge/skills/himself65/finance-skills/options-payoff.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00176 | $0.01932 |
| Opus 5 | $0.00088 | $0.00966 |
| Sonnet 5 | $0.00035 | $0.00386 |
| Haiku 4.5 | $0.00018 | $0.00193 |
Grade A, and why
options-payoff scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 197 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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 "exec('try:\n import yfinance as yf\n p=yf.Ticker(\'^GSPC\').fast_info[\'lastPrice\']\n print(f\'SPX ≈ {p:.0f}\')\nexcept Exception:\n print(\'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 |
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 197 lines · 176 tokens per session scan A 082e0cc79c30
options-payoff is a skill published in the GitHub repository himself65/finance-skills (3,298 stars, last pushed 12d ago), licensed MIT. It adds 176 tokens to every session and 1,932 once invoked, about $0.0009 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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