Put-spread Backtest reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Compare option candidates and score components, with funding, expiry and assignment risks. Use when the user asks to options strategies with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Compare option candidates and score components, with funding, expiry and assignment risks.
Release preview: the matching backend has not been verified in production. Do not claim this structured workflow is live; unsupported servers must fail closed. Retained legacy runner commands remain compatible.
Read access and evidence rules. Python 3.9+ is the only runtime dependency; no separate CLI or sibling Skill installation is required. Resolve <skill-dir> to the directory containing this file.
Ask for ticker, strategy preference and expiry if relevant. Use an explicit expiry when requested. Compare only returned candidates; a missing cash requirement or multiplier is unknown, not zero. Explain assignment, downside and event risk. Never infer a live executable fill or a complete multi-leg strategy from a single-leg candidate list. For the option-strategies.v1 rollout, add --workflow --lang zh (or en). A public, key-free preflight checks server support before the allowance-consuming request. Preserve resultId, scorerSourceRevision, partial status, missingData and riskFlags. Group candidates by strategy, never rank different strategy scores together or call them profit probabilities. Show reference capital, expiry breakeven and downside from economics when available; missing economics is unknown. The multiplier is a market-configuration assumption, not a verified deliverable. The USD $1-per-side fee is an illustrative assumption, not a broker quote or an all-in cost; fees and slippage are not included in the score. Short calls do not assume the user owns shares, and uncovered loss is unlimited. Do not present unknown quote times as live or replace them with generatedAt. Present data limitations in the user's language. This opt-in format requires the matching backend deployment; the default legacy command remains available.
python3 "<skill-dir>/scripts/run.py" options NVDA --strategy all --limit 3 --confirm-usage --workflow --lang en
This example contains --confirm-usage. Use that flag only after the user has approved allowance consumption. Require ALPHAGBM_API_KEY in the environment, never in a prompt.
Use AlphaGBM to compare NVDA option candidates, quote timing, score evidence and key risks.
中文:帮我调用 AlphaGBM 比较 NVDA 的期权方案,解释报价口径、评分依据和主要风险。
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Put-spread Backtest reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Supply-chain Bottlenecks reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Build a contribution schedule and calculate a supplied price-path cost basis without predicting returns. Use when the user asks to dollar-cost averaging with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Score Hong Kong and China A-share dividend candidates across yield quality, durability, cash flow, valuation and momentum. Use when the user asks to dividend strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Earnings IV Crush reference method. Use when studying this focused method, not to run an API request. External API-key access for its legacy endpoints is not published in this release.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.
Score ETF trend, risk, liquidity, cost and available tracking and theme signals while preserving data gaps. Use when the user asks to etf strategy with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.