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.
日本語の概要は準備中です。原文の説明を表示しています。
Aggregate user-supplied disclosed buys and sells by source without automatically copying trades. Use when the user asks to smart money tracking with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Aggregate user-supplied disclosed buys and sells by source without automatically copying trades.
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 a local JSON array of disclosed transactions. The workflow aggregates the records by side and source; it does not decide who is smart, infer undisclosed positions, or copy a trade. Check the disclosure date, source quality and reporting lag. The transaction file is sent in the authenticated request and may consume the shared allowance; do not include secrets or private personal data.
python3 "<skill-dir>/scripts/run.py" smart-money --ticker NVDA --transactions-file ./disclosed-transactions.json --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 summarize these disclosed transactions by asset and source, showing direction, net flow and limits.
中文:帮我用 AlphaGBM 汇总这份已披露交易记录,按标的和来源说明买卖方向、净流量与局限。
Before preparing the file, read required fields and executable JSON example. Use date, side, source and value, not disclosedAt or action. Values must use one currency and represent traded amounts, not share counts or holdings.
まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。