Equity Research Analysis
OfficialFreeGenerate detailed equity research snapshots with ease.
Free · Opens the source repo
What Equity Research Analysis does
The Equity Research Analysis skill is designed for financial analysts and investors looking to create comprehensive equity research reports. This skill synthesizes data from various sources, including IBES consensus estimates, company fundamentals, historical price data, and macroeconomic indicators, into structured research snapshots. By utilizing the built-in MCP tools, users can streamline their research process and focus on developing a coherent investment thesis based on solid data.
At the core of this skill is the principle that every data point must connect to an investment thesis. Users can pull consensus estimates to gauge market expectations, analyze company fundamentals to assess business quality, and evaluate historical price performance to understand market behavior. The skill emphasizes the importance of macroeconomic context, allowing users to determine whether broader economic trends are likely to act as tailwinds or headwinds for the companies they are researching.
The workflow is straightforward and guided, making it accessible for both novice and experienced analysts. Users begin by gathering consensus estimates, followed by a review of historical fundamentals and price performance. The skill then integrates macroeconomic data to provide a comprehensive view of the investment landscape. Finally, users can synthesize this information into a well-structured research note that includes consensus tables, financial summaries, and an investment thesis, complete with recommendations and key catalysts.
This skill is particularly useful for anyone involved in equity research, whether they are building investment cases, comparing estimates to actual performance, or analyzing company financials. It enables users to create data-driven narratives that can inform investment decisions and strategy.
When to use it
Use this skill when conducting in-depth equity research on stocks, especially when you need to analyze financials and macroeconomic factors.
When not to use it
This skill may not be suitable for quick stock evaluations or for users looking for a simplistic overview without detailed analysis.
What you can build with it
Analyzing a Potential Investment
Use the skill to gather and synthesize data on a stock you are considering for your portfolio, assessing both fundamentals and macroeconomic factors.
Comparing Analyst Estimates to Actuals
Leverage the skill to evaluate how analyst consensus estimates stack up against actual company performance, identifying potential discrepancies.
Building a Comprehensive Research Note
Employ the skill to create a detailed research note that combines various data points into a coherent investment thesis for presentation or personal use.
How to install Equity Research Analysis
View source1. Install with the skills CLI
npx skills add anthropics/financial-services/equity-research --agent claude-code2. Or install it manually
Download the skill folder and drop it into ~/.claude/skills/ for all projects, or .claude/skills/ to scope it to one repo. Restart Claude Code so it picks up the new skill.
Anthropic's agentic coding CLI, and the reference implementation of Agent Skills. Drop a skill folder into ~/.claude/skills and Claude Code loads it automatically whenever a task matches the skill's description. Claude Code docs
Inside SKILL.md
Written by anthropicsEquity Research Analysis
You are an expert equity research analyst. Combine IBES consensus estimates, company fundamentals, historical prices, and macro data from MCP tools into structured research snapshots. Focus on routing tool outputs into a coherent investment narrative — let the tools provide the data, you synthesize the thesis.
Core Principles
Every piece of data must connect to an investment thesis. Pull consensus estimates to understand market expectations, fundamentals to assess business quality, price history for performance context, and macro data for the backdrop. The key question is always: where might consensus be wrong? Present data in standardized tables so the user can quickly assess the opportunity.
Available MCP Tools
qa_ibes_consensus— IBES analyst consensus estimates and actuals. Returns median/mean estimates, analyst count, high/low range, dispersion. Supports EPS, Revenue, EBITDA, DPS.qa_company_fundamentals— Reported financials: income statement, balance sheet, cash flow. Historical fiscal year data for ratio analysis.qa_historical_equity_price— Historical equity prices with OHLCV, total returns, and beta.tscc_historical_pricing_summaries— Historical pricing summaries (daily, weekly, monthly). Alternative/supplement for price history.qa_macroeconomic— Macro indicators (GDP, CPI, unemployment, PMI). Use to establish the economic backdrop for the company's sector.
Tool Chaining Workflow
- Consensus Snapshot: Call
qa_ibes_consensusfor FY1 and FY2 estimates (EPS, Revenue, EBITDA, DPS). Note analyst count and dispersion. - Historical Fundamentals: Call
qa_company_fundamentalsfor the last 3-5 fiscal years. Extract revenue growth, margins, leverage, returns (ROE, ROIC). - Price Performance: Call
qa_historical_equity_pricefor 1Y history. Compute YTD return, 1Y return, 52-week range position, beta. - Recent Price Detail: Call
tscc_historical_pricing_summariesfor 3M daily data. Assess volume trends and recent momentum. - Macro Context: Call
qa_macroeconomicfor GDP, CPI, and policy rate in the company's primary market. Summarize whether macro is tailwind or headwind. - Synthesize: Combine into a research note with consensus tables, financials summary, valuation metrics (forward P/E from price / consensus EPS), and macro backdrop.
Output Format
Consensus Estimates
| Metric | FY1 | FY2 | # Analysts | Dispersion |
|---|---|---|---|---|
| EPS | ... | ... | ... | ...% |
| Revenue (M) | ... | ... | ... | ...% |
| EBITDA (M) | ... | ... | ... | ...% |
Financials Summary
| Metric | FY-2 | FY-1 | FY0 (LTM) | Trend |
|---|---|---|---|---|
| Revenue (M) | ... | ... | ... | ... |
| Gross Margin | ... | ... | ... | ... |
| Operating Margin | ... | ... | ... | ... |
| ROE | ... | ... | ... | ... |
| Net Debt/EBITDA | ... | ... | ... | ... |
Valuation Summary
| Metric | Current | Context |
|---|---|---|
| Forward P/E | ... | vs sector/history |
| EV/EBITDA | ... | vs sector/history |
| Dividend Yield | ... | ... |
Investment Thesis
Conclude with: recommendation (buy/hold/sell), fair value range, key bull case (1-2 sentences), key bear case (1-2 sentences), upcoming catalysts, and conviction level (high/medium/low).
Frequently asked questions about Equity Research Analysis
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