What problem does it solve? Direct AI stock analysis tends to produce vague, both-sides commentary without actionable conclusions. This Skill enforces a disciplined research workflow based on Buffett, Munger, Duan Yongping, and Li Lu methodologies, producing reports with explicit buy/hold/avoid verdicts, price ranges, and verified financial data. ## Core Features & Use Cases - Four-Master Analysis Framework: Evaluates business quality (Duan Yongping), economic moats (Buffett), inversion-based risk analysis (Munger), and long-term civilizational trends (Li Lu) across eight sequential modules. - Programmatic Data Verification: Cross-validates market cap, revenue, net income, and valuation metrics from at least two independent sources using tools/financial_rigor.py, with a 1% deviation threshold and mandatory post-report audit sampling. - Ten-Year Valuation Discipline: Computes terminal value via the perpetual growth model with hard constraints on discount rate, ROIC, and growth rate using tools/terminal_value.py, forbidding peer-analogy terminal multiples. - Use Case: Ask for a deep-dive on a company like Pinduoduo and receive a full Markdown report with an information-richness rating (A/B/C), three-scenario valuation, simulated commentary from all four investors, and a final decision table for different investor profiles. ## Quick Start Run a full investment research analysis on a company, for example: analyze whether Pinduoduo is worth buying at its current price using the four-master framework.
