AI analyst for pennies: 10 prompts for Claude that will transform your approach to the market
The cryptocurrency and stock market is undergoing a tectonic shift. Expensive analysts with their multi-thousand-dollar reports are becoming a thing of the past. Artificial intelligence, capable of performing in minutes work that used to take days, is taking center stage. This is about a set of 10 specialized prompts for Claude that allow for deep fundamental analysis at the level of a leading consulting firm. This is not just a tool — it's a paradigm shift.
Each prompt assigns Claude a clear role and a set of parameters, turning it into a highly specialized expert. None of these queries provide direct "buy" or "sell" recommendations — their goal is to provide a structured, comprehensive picture based on which the investor makes their own decision.
The First Five: From General Overview to Valuation
The first prompt assigns Claude the role of a senior analyst. It prepares a research report on a company or ticker that is understandable even to a beginner, covering the business model, revenue sources, industry trends, competitors, financial results, and bull/base/bear scenarios. The key requirement is to rely on fresh public sources, clearly separating facts from assumptions.
The second prompt focuses on the company's latest earnings call. It highlights five main takeaways, analyzes revenue and margin dynamics, management guidance, management tone, analyst concerns, as well as positive and negative surprises. Additionally, it creates a table of key metrics with explanations of why each indicator is important.
The third prompt turns Claude into a skeptical analyst who looks for red flags: issues with revenue, margins, cash flow, debt, dilution, insider actions, and management wording. Each issue is assigned a severity rating, and a total risk score from 1 to 10 is output at the end.
The fourth and fifth prompts are dedicated to competitive advantages and valuation. The first assesses the company's "moat" — brand, network effects, switching costs, scale, intellectual property — and compares it with competitors. The second compares the company with peers using multiples (P/E, forward P/E, EV/Revenue, EV/EBITDA) and determines whether it is overvalued, undervalued, or fairly valued.
The Second Five: From DCF Model to Beginner's Checklist
The sixth prompt helps build realistic assumptions for a discounted cash flow (DCF) model. It creates bear, base, and bull scenarios for revenue growth, margins, tax rate, and discount rate, explaining the logic behind each assumption in detail.
The seventh prompt creates a catalyst calendar for 3, 6, and 12 months: 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, M&A, insider ownership, and compensation. The ninth prompt simulates an investment committee debate, where Claude creates a bull analyst and a bear analyst, and a neutral judge explains at the end whose position is better supported.
The tenth prompt turns Claude into a patient teacher who explains the company in simple language: what it does, how it makes money, what could go right and wrong, and how things stand regarding profitability, growth, debt, and valuation. At the end, a beginner's checklist is formed.
My analysis: This methodology is a powerful tool for democratizing access to quality analysis. However, it is critically important to remember that AI lacks intuition and can make mistakes in data interpretation. Final verification and decision-making always remain with the human. This set of prompts does not replace an experienced analyst but turns every investor into a more effective researcher.