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.
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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.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
Build a contribution schedule and calculate a supplied price-path cost basis without predicting returns.
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.
Provide contribution amount, frequency and number of periods. An optional comma-separated price path is treated as supplied history only; the returned average cost is not a forecast. The result does not predict returns, choose a security or place recurring orders. Confirm the assumptions before using the shared allowance.
python3 "<skill-dir>/scripts/run.py" dca --ticker QQQ --contribution 500 --periods 12 --frequency monthly --confirm-usage --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 build a 12-period monthly $500 QQQ contribution plan and explain total capital and limits.
中文:帮我用 AlphaGBM 为 QQQ 做每月 500 美元、12 期的定投计划,说明总投入和限制。
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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.
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.
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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.
Greeks 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.