How to use the Financial Analysis agent skill

What is an agent skill and what does this one do?

An agent skill is a folder of instructions that an AI agent reads when a task matches the skill's description. This one is a single file, SKILL.md, with no code or data of its own.

The skill tells the agent to collect historical income statements, balance sheets and cash flow statements, check them for anomalies or missing data, and then calculate common ratios. It covers profitability (EBITDA margin, net profit margin, ROE, ROA), liquidity (current, quick and cash ratios), leverage (debt-to-equity, interest coverage) and efficiency (asset and inventory turnover).

• Valuation: DCF analysis, comparable company analysis using P/E and EV/EBITDA, and precedent transactions.
• Sensitivity: base, bull and bear scenarios, and tests on growth rates, discount rates and margins.
• Discipline: state assumptions, use conservative estimates when unsure, and include caveats and risks.

How do you install the financial-analysis skill?

Download the skill ZIP from this page and unzip it. You can install it in one of two ways depending on where you run your agent.

For Claude Code, unzip it into your personal skills folder at ~/.claude/skills/ or into a project-specific folder at .claude/skills/ inside your project. The skill folder should contain SKILL.md.

In the Claude apps, open Settings, go to Capabilities, and upload the skill under Skills.

• Personal install: ~/.claude/skills/
• Project install: .claude/skills/ in your project folder
• Claude apps: Settings → Capabilities → Skills

How do you trigger the skill with a natural request?

You do not need a special command. The skill's description covers DCF modeling, ratio analysis and financial statement evaluation, so ask for one of those tasks in plain language and name the company or opportunity. Give the agent the financial data it needs, or tell it where to find it.

Good requests state the goal and the object of analysis. Vague requests such as 'tell me about this company' are less likely to produce the structured method the skill describes.

• Analyze Tesla's financials and provide a DCF valuation.
• Evaluate this startup's unit economics and runway.
• Assess the financial implications of this acquisition.
• Calculate the key profitability and leverage ratios for this company's last three years of statements.

What output should you expect?

The skill asks the agent to produce five outputs: an executive summary, a detailed financial model with its assumptions, a valuation range with sensitivity analysis, an investment recommendation with risk assessment, and supporting charts and visualizations.

Check the assumptions first. The skill asks the agent to document each one and its rationale, so you can change an input and see how the result moves.

• Executive summary of findings
• Financial model with stated assumptions
• Valuation range with sensitivity analysis
• Investment recommendation with risk assessment
• Supporting charts and visualizations

What do you need before you start?

The skill lists no requirements. It does not run scripts and does not use the network. Its output depends entirely on the financial data you or the agent can access, so the quality of the analysis depends on the quality of that data.

Supply complete statements where you can. The skill tells the agent to flag missing data points rather than fill them silently.

• Historical income statement, balance sheet and cash flow statement for the company
• Any peer company data if you want comparable company analysis
• Deal terms if you want precedent transaction or M&A review

What are the safety notes?

Because the skill is only instructions, it cannot run code on your machine or send data over the network. The risk lies in the output. The agent generates the analysis from whatever data it can reach, and that data may contain errors or be out of date.

The skill does not verify sources and does not meet the standards of a formal audit or regulated advice. Treat the result as a first-pass screen and check important figures against the original filings.

• Do not use the output as the sole basis for an investment decision.
• Verify every figure that matters against primary sources.
• Do not rely on it for regulated advice or formal audits.

What tips improve the results?

Ask for scenarios up front. The skill already calls for base, bull and bear cases, but naming the assumptions you care about (for example, discount rate or margin path) makes the sensitivity analysis more useful.

Ask the agent to cross-check. The skill recommends validating findings with more than one valuation method, so a DCF result can be compared with comparable company multiples.

• Name the growth and discount rate assumptions you want tested.
• Ask for both DCF and comparable company analysis, then compare the ranges.
• Ask the agent to list its caveats and risk factors explicitly.