{"id":51197069,"url":"https://github.com/AlphaGBM/skills","last_synced_at":"2026-06-28T07:00:57.458Z","repository":{"id":349497978,"uuid":"1202559832","full_name":"AlphaGBM/skills","owner":"AlphaGBM","description":"Real-data options intelligence for AI agents — 15 Skills for Claude Code, Cursor \u0026 beyond","archived":false,"fork":false,"pushed_at":"2026-04-13T09:04:44.000Z","size":130,"stargazers_count":37,"open_issues_count":0,"forks_count":1,"subscribers_count":0,"default_branch":"main","last_synced_at":"2026-04-13T10:29:48.103Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":"mit","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/AlphaGBM.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":"CONTRIBUTING.md","funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null,"zenodo":null,"notice":null,"maintainers":null,"copyright":null,"agents":null,"dco":null,"cla":null}},"created_at":"2026-04-06T06:35:37.000Z","updated_at":"2026-04-13T10:04:07.000Z","dependencies_parsed_at":null,"dependency_job_id":null,"html_url":"https://github.com/AlphaGBM/skills","commit_stats":null,"previous_names":["alphagbm/skills"],"tags_count":0,"template":false,"template_full_name":null,"purl":"pkg:github/AlphaGBM/skills","repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AlphaGBM%2Fskills","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AlphaGBM%2Fskills/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AlphaGBM%2Fskills/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AlphaGBM%2Fskills/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/AlphaGBM","download_url":"https://codeload.github.com/AlphaGBM/skills/tar.gz/refs/heads/main","sbom_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/AlphaGBM%2Fskills/sbom","scorecard":null,"host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":286080680,"owners_count":34880189,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2026-05-26T15:22:16.424Z","status":"online","status_checked_at":"2026-06-28T02:00:05.809Z","response_time":54,"last_error":null,"robots_txt_status":"success","robots_txt_updated_at":"2025-07-24T06:49:26.215Z","robots_txt_url":"https://github.com/robots.txt","online":true,"can_crawl_api":true,"host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2026-06-27T21:31:06.298Z","updated_at":"2026-06-28T07:00:57.450Z","avatar_url":"https://github.com/AlphaGBM.png","language":"Python","funding_links":[],"categories":["Data Analysis Skills","🧠 Agent Skills"],"sub_categories":[],"readme":"\u003cdiv align=\"center\"\u003e\n\n# AlphaGBM Skills\n\n**See what options are pricing in — with real data, not guesswork.**\n\n*29 AI skills for options \u0026 research intelligence · Built on real market data · Trusted by 10,000+ traders*\n\n[![MIT License](https://img.shields.io/badge/license-MIT-blue.svg)](LICENSE) [![Skills](https://img.shields.io/badge/skills-29-green.svg)](#skills-overview) [![Users](https://img.shields.io/badge/users-10K%2B-orange.svg)](https://alphagbm.com)\n\n[Website](https://alphagbm.com) · [Documentation](#skills-overview) · [Quick Start](#quick-start) · [Contributing](CONTRIBUTING.md)\n\n---\n\n\u003c!-- TODO: Replace with actual screenshot of CLI/agent output --\u003e\n\u003cimg src=\"assets/demo-screenshot.png\" alt=\"AlphaGBM options analysis output\" width=\"720\"\u003e\n\n### 30-Second Demo\n\n```bash\ngit clone https://github.com/AlphaGBM/skills.git .claude/skills/alphagbm\n```\n\nThen ask your AI: *\"Analyze AAPL options using AlphaGBM\"* — works instantly with built-in data, no API key needed.\n\n\u003c/div\u003e\n\n## What is AlphaGBM?\n\nAlphaGBM is a **real-data options \u0026 research intelligence layer** for traders and AI agents. Every number comes from real market data -- IV, Greeks, VRP, skew, flow, plus a tracked research workspace -- not LLM hallucination.\n\nThese 26 skills bring AlphaGBM's capabilities into your AI workflow: Claude Code, Cursor, Windsurf, or any agent that supports skills.\n\n### Why AlphaGBM?\n\n| | LLM Roleplay Tools | Generic Finance APIs | **AlphaGBM** |\n|--|-------------------|---------------------|-------------|\n| Data Source | LLM-generated | Delayed/basic | **Real-time options data** |\n| Verifiable | \"85% confidence\" | Partial | **Every number has a source** |\n| Options Depth | None | Basic chain | **IV/HV/VRP/Greeks/Skew/Surface** |\n| Scoring | Subjective | None | **Quantitative scoring (0-100 options, 1-10 stocks)** |\n| Analysis Model | None | None | **G = B + M (Gain = Basics + Momentum)** |\n| Battle-tested | No | Varies | **10K users, 3mo live trading** |\n| Coverage | US only | Varies | **US + HK + CN + Commodities** |\n\n## Quick Start\n\n### Install as Claude Code Skills\n\n```bash\n# Clone into your project\ngit clone https://github.com/AlphaGBM/skills.git .claude/skills/alphagbm\n\n# Or add as submodule\ngit submodule add https://github.com/AlphaGBM/skills.git .claude/skills/alphagbm\n```\n\n### Install for Cursor\n\n```bash\ngit clone https://github.com/AlphaGBM/skills.git .cursor/skills/alphagbm\n```\n\n### Install CLI\n\n```bash\n# Clone and install\ngit clone https://github.com/AlphaGBM/skills.git\ncd skills/cli\npip install -e .\n\n# Set your API key\nalphagbm config set-key agbm_xxxxxxxxxxxxxxxx\n\n# Start analyzing\nalphagbm stock analyze AAPL\nalphagbm options score NVDA\n```\n\nSee [cli/README.md](cli/README.md) for full CLI documentation.\n\n### Try It (No API Key Needed)\n\nAll skills include built-in demo data for AAPL, NVDA, SPY, TSLA, and META. Just ask your AI:\n\n\u003e \"Analyze AAPL stock using AlphaGBM\"\n\u003e \"Score NVDA options\"\n\u003e \"Show me TSLA's volatility surface\"\n\u003e \"What's the best bullish strategy for META?\"\n\n### Connect Live Data\n\n```bash\n# Set your API key for real-time data\nexport ALPHAGBM_API_KEY=agbm_xxxxxxxxxxxxxxxx\nexport ALPHAGBM_BASE_URL=https://alphagbm.zeabur.app  # optional, this is the default\n\n# Get your free key at https://alphagbm.com/api-keys\n```\n\n### Check API Health\n\n```bash\ncurl https://alphagbm.zeabur.app/api/health\n```\n\nReturns API status, available data fields, data source health, and market coverage — no auth needed. Useful for AI agents to verify what's available before making calls.\n\n### Quota\n\n| Plan | Stock Analysis | Options Analysis | Quick Quote / Snapshot |\n|------|---------------|-----------------|----------------------|\n| Free | 2/day | 1/day | Unlimited |\n| Plus | 1,000/month | 1,000/month | Unlimited |\n| Pro | 5,000/month | 5,000/month | Unlimited |\n\n## Skills Overview\n\n### Core Analysis (7 skills)\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**Stock Analysis**](skills/alphagbm-stock-analysis/) | G=B+M model: fundamentals, momentum, EV, risk score, AI report | \"Analyze AAPL\" |\n| [**Options Score**](skills/alphagbm-options-score/) | Score 0-100 across 4 strategies (Sell Put/Call, Buy Put/Call) | \"Best NVDA call to buy\" |\n| [**Options Strategy**](skills/alphagbm-options-strategy/) | Strategy builder + scanner with 15+ templates | \"Bullish play on TSLA\" |\n| [**Vol Surface**](skills/alphagbm-vol-surface/) | 3D implied volatility across strikes \u0026 expiries | \"Is AAPL IV expensive?\" |\n| [**Vol Smile**](skills/alphagbm-vol-smile/) | Skew analysis for a single expiration | \"NVDA put skew\" |\n| [**Greeks**](skills/alphagbm-greeks/) | Greeks calculator + implied volatility solver | \"Greeks for AAPL 220C\" |\n| [**P\u0026L Simulator**](skills/alphagbm-pnl-simulator/) | What-if analysis for any position | \"Simulate my iron condor\" |\n\n### Data Intelligence (6 skills)\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**IV Rank**](skills/alphagbm-iv-rank/) | IV percentile vs. 252-day history | \"Is TSLA IV high?\" |\n| [**Earnings IV Panel**](skills/alphagbm-earnings-crush/) | Crush history + implied move + IV Rank tag + priced Iron Condor | \"Iron Condor for META earnings\" |\n| [**Unusual Activity**](skills/alphagbm-unusual-activity/) | Smart money / large block detection | \"Unusual options flow today\" |\n| [**Market Sentiment**](skills/alphagbm-market-sentiment/) | VIX, Put/Call, Fear \u0026 Greed dashboard | \"Market sentiment now\" |\n| [**VIX Status**](skills/alphagbm-vix-status/) ✨ | 5-tier fear thermometer: calm / normal / seller sweet spot / caution / extreme fear | \"Is this a good time for BPS?\" |\n| [**FearScore**](skills/alphagbm-fear-score/) ✨ | Per-ticker 6-indicator panic composite; ≥60 is BPS entry signal | \"Fear score QQQ\", \"is NVDA oversold\" |\n\n### Workflow Tools (4 skills)\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**Compare**](skills/alphagbm-compare/) | Side-by-side stock \u0026 options comparison | \"AAPL vs MSFT\" |\n| [**Watchlist**](skills/alphagbm-watchlist/) | Monitor tickers for key changes | \"Add NVDA to watchlist\" |\n| [**Alert**](skills/alphagbm-alert/) | Set IV, price, or activity alerts | \"Alert if TSLA IV \u003e 80\" |\n| [**Polymarket**](skills/alphagbm-polymarket/) | Prediction market vs. options pricing | \"Rate cut odds vs options\" |\n\n### Risk \u0026 Portfolio Discipline (3 skills) ✨\n\nExit, hedge, and sizing decisions quantified from real data — not opinion.\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**Hedge Advisor**](skills/alphagbm-hedge-advisor/) ✨ | Scenario-driven hedge for an existing position (Falling Knife / Bottom Fishing / Gain Protection); returns priced Long Put / Collar / Tier-down specs | \"Hedge my AAPL at cost 140, now 180\" |\n| [**BPS Backtest**](skills/alphagbm-bps-backtest/) ✨ | Walk-forward backtest of Bull Put Spread with signal vs no-signal control in one call | \"Backtest BPS on QQQ — does FearScore work?\" |\n| [**Take-Profit Lab**](skills/alphagbm-take-profit/) ✨ | Any-ticker 15-strategy exit backtest; auto-classifies whether it's holdable or needs tiered exit via a novel \"rollercoaster rate\" metric | \"Should I hold TQQQ long-term?\" |\n\n### Investor Masters (4 skills) 🎓\n\nMechanical translations of specific investors' philosophies into one-call tools.\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**Duan-Yongping Analysis**](skills/alphagbm-duan-analysis/) | Three-panel seller playbook (Sell Put at willing-buy price / Covered Call yield / VIX-tier panic-buy context) | \"Duan-style analysis on AAPL\" |\n| [**Buffett Analysis**](skills/alphagbm-buffett-analysis/) ✨ | 4-lens scorecard (business / moat / management / valuation) → weighted HOLDABLE / WATCHABLE / AVOID verdict for any ticker | \"Buffett analysis on KO\" |\n| [**Marks Cycle**](skills/alphagbm-marks-cycle/) ✨ | Howard Marks-style cycle position 0-100 blending VIX + IV Rank + P/C + valuation; maps to offense/defense posture. Free, no auth | \"Where are we in the cycle?\" |\n| [**Tepper Signal**](skills/alphagbm-tepper-signal/) ✨ | Quantified Tepper 2009/2020 panic-buy detector: VIX ≥ 35 + FearScore ≥ 80 + quality filter → armed/watch/near/cold | \"Is this a Tepper buy signal?\" |\n\n### Knowledge Base — Research Brain (5 skills)\n\nBuild a personal, monitored research workspace. Profiles auto-refresh, theses get checked against triggers, the system audits itself weekly.\n\n| Skill | What It Does | Example Query |\n|-------|-------------|---------------|\n| [**Company Profile**](skills/alphagbm-company-profile/) | Auto-built research files: fundamentals, PE/PB band, red flags, event radar | \"Add NVDA to my knowledge base\" |\n| [**Investment Thesis**](skills/alphagbm-investment-thesis/) | Buy reasons + structured sell triggers, monitored automatically | \"Why did I buy AAPL?\" |\n| [**Macro View**](skills/alphagbm-macro-view/) | Track VIX / US10Y / DXY / gold with portfolio-aware impact analysis | \"Track VIX and US10Y\" |\n| [**Theme Research**](skills/alphagbm-theme-research/) | Group tickers into themes (AI infra, HK dividend) + news keyword watching | \"Create an AI infra theme\" |\n| [**Health Check**](skills/alphagbm-health-check/) | Weekly audit: stale profiles, thesis drift, orphan pages → 0-100 score | \"Audit my research brain\" |\n\n### See Also\n\n- **[Investment Masters](https://github.com/AlphaGBM/investment-masters)** -- 12 masters' methodologies (Buffett, Dalio, Soros, Marks, Liang Wenfeng, Raschke...) + 13F tracking\n\n## Architecture\n\n```\nYou / Your AI Agent\n    |  (natural language)\n+------------------------------------------------------+\n|              AlphaGBM Skills (this repo)              |\n|                                                       |\n|  Stock    Options   Vol      Strategy   Greeks   ...  |\n|  Analysis  Score   Surface   Builder    Dashboard     |\n+-------------------------+-----------------------------+\n                          |\n               +----------+----------+\n               v                     v\n         Mock Data              AlphaGBM API\n      (built-in, free)      (alphagbm.zeabur.app)\n                             Real-time market data\n                             IV/HV/VRP/Greeks/Skew\n```\n\n### How Skills Connect\n\nSkills aren't isolated -- they reference each other to form a complete workflow:\n\n```\nStock Analysis --\u003e Options Score --\u003e Options Strategy --\u003e P\u0026L Simulator\n       |                |                    |\n       v                v                    v\n   Compare          Vol Surface           Greeks\n                    Vol Smile\n                    IV Rank --\u003e Earnings Crush\n\nMarket Sentiment --\u003e Unusual Activity --\u003e Alert\n                                          Watchlist\n\nPolymarket --\u003e Market Sentiment --\u003e Options Strategy\n```\n\n## Data Coverage\n\n| Market | Stocks | Options | Data Points |\n|--------|--------|---------|-------------|\n| US | 200+ | Full chains | IV/HV/VRP/Greeks/Skew/Surface |\n| HK | 35+ | Full chains | IV/HV/VRP/Greeks |\n| CN | 20+ ETFs | Full chains | IV/HV/VRP/Greeks |\n| Commodities | Au/Ag/Cu/Al | Futures options | IV/Greeks/Delivery risk |\n\n## Real Data, Not Guesswork\n\nEvery number in AlphaGBM is **verifiable**:\n\n| Metric | Value | How It's Computed |\n|--------|-------|-------------------|\n| **IV** | 32.5% | Black-Scholes on actual bid/ask prices |\n| **IV Rank** | 58 | Current IV vs. 252 trading days of history |\n| **VRP** | +4.0% | `Implied Vol - Historical Vol` — measures option overpricing |\n| **Option Score** | 80/100 | Weighted: premium yield + support/resistance + safety margin + trend + PoP + liquidity + time decay |\n| **Stock Score** | 7.0/10 | `G = B + M` — Basics (PE, PEG, growth, margins) + Momentum (VIX, technicals, flow) |\n| **Risk** | 4/10 | Additive: valuation +2, growth +2, liquidity +2, market +1.5, technical +1 |\n| **EV** | +5.2% | `50% × 1w + 30% × 1m + 20% × 3m` expected value |\n\nThis is not *\"based on my training data\"* or *\"I estimate with 85% confidence.\"*\n\nThis is math on market data.\n\n## Example Workflow\n\n\u003e **You**: \"Analyze AAPL, then find the best options play\"\n\nThe agent chains skills automatically:\n\n```\n1. GET  /api/stock/quick-quote/AAPL          → $261.40 (-0.8%)\n2. POST /api/stock/analyze-sync              → G=B+M score 7.0/10, EV +5.2%, BUY\n   {\"ticker\": \"AAPL\", \"style\": \"balanced\"}     Risk 4/10, target $275, stop-loss $239\n\n3. GET  /api/options/snapshot/AAPL           → IV 32.5%, IV Rank 58, VRP +4.0%\n4. POST /api/options/chain-sync              → Sell Put scores: 80, 78, 75...\n   {\"symbol\": \"AAPL\", \"expiry_date\": \"...\"}    Buy Call scores: 76, 74, 72...\n\n5. POST /api/options/tools/strategy/build    → Bull Call Spread 265/280\n   {\"template_id\": \"bull_call_spread\"}         Max profit $1085, max loss $415\n\n6. POST /api/options/tools/simulate          → Breakeven $269.15, PoP 44.5%\n   {\"symbol\": \"AAPL\", \"legs\": [...]}\n```\n\n\u003e **You**: \"Is that IV expensive?\"\n\n```\n7. GET  /api/options/snapshot/AAPL           → IV Rank 58 (moderate)\n8. GET  /api/options/tools/vol-surface/AAPL  → ATM IV in contango, earnings in 26d\n```\n\nAll from real API calls. All verifiable.\n\n## Roadmap\n\n- [x] 29 Skills with mock data\n- [x] Claude Code \u0026 Cursor support\n- [x] CLI tool (`pip install -e ./cli`)\n- [ ] Real-time WebSocket feeds\n- [ ] Community strategy sharing\n- [ ] More markets (EU, JP, KR options)\n\n## Contributing\n\nSee [CONTRIBUTING.md](CONTRIBUTING.md) for guidelines. We welcome:\n\n- Bug reports \u0026 feature requests\n- Skill improvements \u0026 new skill proposals\n- Translations (currently EN + CN)\n- Mock data for additional tickers\n\n## License\n\nMIT -- see [LICENSE](LICENSE).\n\n## Links\n\n- [alphagbm.com](https://alphagbm.com) -- Full platform with live data\n- [API Documentation](https://alphagbm.com/docs)\n- [Discord Community](https://discord.gg/alphagbm)\n- [Twitter/X](https://x.com/alphagbm)\n\n---\n\n\u003cdiv align=\"center\"\u003e\n\n**Built by the [AlphaGBM](https://alphagbm.com) team. Trusted by 10,000+ traders worldwide.**\n\n*Real data. Real signals. Real edge.*\n\n\u003c/div\u003e\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAlphaGBM%2Fskills","html_url":"https://awesome.ecosyste.ms/projects/github.com%2FAlphaGBM%2Fskills","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2FAlphaGBM%2Fskills/lists"}