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.
中文简介正在准备中。当前显示原文说明。
Connect fundamentals, sentiment and risk to supporting and opposing evidence. Use when the user asks to stock opportunities with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
中文简介正在准备中。当前显示原文说明。
查看安装方法安装前可以查看交给 AI 代理的指令内容。
Connect fundamentals, sentiment and risk to supporting and opposing evidence.
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.
Identify the ticker and market suffix, and agree the research style. One explicit user-authorized research request is the starting point. Use only returned fundamentals, report and risk fields; no invented peer comparisons. The legacy risk.score is not the homepage opportunity score. For the stock-opportunities.v1 rollout, add --workflow --lang zh (or en). The runner first checks the public workflow contract without a key; unsupported servers receive no analysis request. Preserve partial status, resultId, scoring version and missingData. Do not retry a charged request automatically or claim the result was saved to user history. This opt-in format needs the matching backend deployment; the default legacy command remains available.
python3 "<skill-dir>/scripts/run.py" stock NVDA --style quality --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 research NVDA: supporting evidence, counterevidence and what to verify next.
中文:帮我调用 AlphaGBM 研究 NVDA,列出支持依据、反方证据,以及下一步要验证什么。
To compare two previous workflow results, read investment review. Use review --baseline <authorized-file> --current <authorized-file> --lang en (or zh). This is local comparison, not account-history access, automatic monitoring or a new paid query.
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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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。
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.
中文简介正在准备中。当前显示原文说明。