What problem does it solve? Evaluating a stock requires pulling together fundamentals, sentiment, risk scores, and research reports from scattered sources, then judging supporting versus opposing evidence. This Skill runs a structured AlphaGBM research workflow that returns dated, versioned evidence so conclusions stay traceable instead of fabricated. ## Core Features & Use Cases - Stock Opportunity Research: Run the stock-opportunities.v1 workflow for a ticker with a chosen style (quality, value, growth, momentum, balanced), returning fundamentals, risk fields, and opportunity scores with missing-data markers preserved. - Local Investment Review: Compare two user-authorized workflow snapshots offline with the bundled review engine, surfacing recorded changes and comparison warnings without any network call or API key. - Safe Access Controls: Enforces explicit usage approval via --confirm-usage before charged requests, requires ALPHAGBM_API_KEY only from the environment, restricts calls to official HTTPS origins, and never retries paid requests automatically. - Use Case: Ask your AI to research NVDA with AlphaGBM; it checks the public workflow contract first, runs the analysis only after you approve allowance use, and returns a conclusion with supporting evidence, counterevidence, and next verification questions. ## Quick Start Ask your AI assistant to use AlphaGBM to research NVDA, listing supporting evidence, counterevidence, and what to verify next, approving the allowance usage when prompted.
