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Follow https://skillsmp.com/skill-install/prompt.md to install Agent Skills from https://github.com/AlphaGBM/skills.Loading the repository README…
Showing 27 of 27 collected skills.
Compare research records you provide to see changes in facts, scores and judgments. Use when the user asks to investment review with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
Separate reported claims from impact inferences, with related assets and next checkpoints. Use when the user asks to news impact with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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.
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.
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.
Volatility Snapshot via the published AlphaGBM interface. Use for this focused function, not as a promise that every website API accepts API keys.
Options Score via the published AlphaGBM interface. Use for this focused function, not as a promise that every website API accepts API keys.
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.
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.
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.
Build an auditable grid from a price range, current price and capital. Use when the user asks to grid plan with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
Score observed price trend, confirmation, risk and participation without forecasting a price. Use when the user asks to momentum following with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
Find published research and institutional views with sources, dates and related assets. Use when the user asks to research reports with AlphaGBM. Use the bundled Python runner; never silently replace real results with demos.
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.
Stock Analysis via the published AlphaGBM interface. Use for this focused function, not as a promise that every website API accepts API keys.
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.
Prediction Markets 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.
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.
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.
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.
Hedging Scenarios 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.
Strategy Builder 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.
Payoff Simulation 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.
Unusual Options Activity 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.
Volatility Smile 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.
Volatility Surface 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.
Market Sentiment 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.
Repository README source: README.md
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