AI analyst for pennies: 10 prompts for Claude that will replace an expensive stock expert
The market for analytical services is undergoing a tectonic shift. A set of 10 specialized prompts for Claude has emerged, enabling deep fundamental analysis of companies at the level of leading consulting firms. This is not just automation—it is the democratization of access to high-quality market research.
Each of the ten prompts assigns Claude a strictly defined role and parameters for analyzing a company or ticker. Together, they cover the full analysis cycle: from a general business overview to a detailed assessment of risks and management quality. None of the queries provide direct buy or sell recommendations—they merely structure the research process.
The First Five: From General Overview to Valuation
The first prompt turns Claude into a senior analyst preparing a research report understandable to a beginner. It covers the business model, revenue sources, industry trends, competitors, financial results, valuation, growth drivers, risks, and bull/base/bear scenarios. A critical requirement is to rely on recent public sources, specify dates, and clearly separate facts from assumptions.
The second prompt breaks down the company's latest earnings call: five main takeaways, changes in revenue and margins, management guidance, management tone, analyst concerns, pleasant and unpleasant surprises. It also generates a table of key metrics with current and previous results and an explanation of why each matters.
The third prompt sets Claude as a skeptical analyst looking for red flags in revenue quality, margins, cash flow, debt, dilution, insider actions, and management language. Each issue is assigned a severity rating, and a final overall risk score from 1 to 10 is provided.
The fourth and fifth prompts focus on competitive advantages and valuation. One assesses the company's "moat"—brand, network effects, switching costs, scale, intellectual property—on a scale and compares it with competitors. The second compares the company with competitors using multiples (P/E, forward P/E, EV/revenue, EV/EBITDA) and explains whether it appears cheap, fairly valued, or expensive.
The Second Five: From DCF Model to a Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model—a method of valuing a company based on future earnings. It generates bear, base, and bull scenarios for revenue growth, margins, tax rate, capital expenditures, and discount rate, explaining the logic behind each assumption.
The seventh prompt creates a calendar of catalysts for 3, 6, and 12 months: earnings reports, product launches, investor days, regulatory decisions, lawsuits, macro events, management changes, buybacks, and dividends. For each event, it specifies timing, impact, upside and downside risks, confidence level, and source.
The eighth prompt evaluates the management team: the CEO's track record, the CFO's credibility, forecast accuracy, transparency, capital allocation, acquisitions, insider ownership, and compensation. The ninth simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and a neutral judge explains which position is better supported.
The tenth prompt turns Claude into a patient teacher who explains the company in simple terms: what it does, how it makes money, what could go right and wrong, and its profitability, growth, debt, and valuation. It ends with a beginner's checklist.
My expert opinion: The value of this collection is not that it replaces an analyst, but that it structures the chaos of information. However, critical data verification and the final investment decision remain with the human. AI is a powerful tool, but not a substitute for common sense and due diligence.