What problem does it solve? AI agents often produce shallow or error-prone company analysis because they lack a structured investment methodology and tend to hallucinate financial figures. This Skill enforces a rigorous, multi-stage research workflow based on Buffett, Munger, Duan Yongping, and Li Lu, with programmatic verification of every key financial data point. ## Core Features & Use Cases - Four-Master Framework: Eight sequential modules covering business quality, moat assessment, inversion-based risk analysis, management evaluation, civilizational trend analysis, and three-scenario valuation. - Programmatic Data Verification: The financial_rigor.py script verifies market cap, valuation ratios, and cross-source data consistency using exact decimal arithmetic, eliminating LLM mental-math errors. - Report Audit Gate: The report_audit.py script randomly samples 15% of data points in the final report and blocks publication until all sampled values match trusted sources within 1%. - Use Case: Ask the agent to research a company like Tencent, and it will collect multi-source financials, generate SVG trend charts, run valuation scenarios, and deliver a Markdown report with an explicit buy/hold/avoid recommendation. ## Quick Start Ask the agent to run a full investment research report on a specific company, for example: run a deep investment research analysis on Tencent.
