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。
Extract report views, ratings, key assumptions and risks with sources and dates. Use when the user asks to research report breakdown 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。
Extract report views, ratings, key assumptions and risks with sources and dates.
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.
Read references/report-breakdown.md. Discover original reports with research --collection research --lang en --limit 5 or institutional summaries with research --collection news --view research --lang en --limit 5 (or zh). Select a returned slug and revision and replace the placeholders. Preserve institution, original rating, dates, currency, assumptions and limitations. Original research may include the full published reader; institutional reports return only the published summary, not private PDFs. The report-breakdown.v1 backend must be deployed; an unavailable response is not permission to fabricate a report. Read references/editorial-routing.md before selecting the next command. Check the returned workflow, language and published revision. A type mismatch needs the declared workflow, not a retry; a changed revision must be re-read. Never silently switch to paid analysis.
python3 "<skill-dir>/scripts/run.py" report --slug <published-report-slug> --revision <published-revision> --lang en
This command reads published data without a key or analysis-credit charge. No paid research is triggered.
Use AlphaGBM to break down a published report: institutional views, original ratings, key assumptions, risks and checkpoints. Find institutional views with research --collection news --view research, or original reports with research --collection research. Check workflow, language and revision before running report; re-read changed revisions first.
中文:帮我调用 AlphaGBM 拆解一份已发布研报,说明机构观点、原始评级、关键假设、风险和后续验证节点。机构观点用 research --collection news --view research 查找,自有研报用 research --collection research;核对 workflow、语言和 revision 后调用 report,版本变化先重新读取。
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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。