equity-research

anthropics/financial-services-plugins · updated Apr 8, 2026

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$npx skills add https://github.com/anthropics/financial-services-plugins --skill equity-research
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summary

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.

skill.md

Equity 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

  1. Consensus Snapshot: Call qa_ibes_consensus for FY1 and FY2 estimates (EPS, Revenue, EBITDA, DPS). Note analyst count and dispersion.
  2. Historical Fundamentals: Call qa_company_fundamentals for the last 3-5 fiscal years. Extract revenue growth, margins, leverage, returns (ROE, ROIC).
  3. Price Performance: Call qa_historical_equity_price for 1Y history. Compute YTD return, 1Y return, 52-week range position, beta.
  4. Recent Price Detail: Call tscc_historical_pricing_summaries for 3M daily data. Assess volume trends and recent momentum.
  5. Macro Context: Call qa_macroeconomic for GDP, CPI, and policy rate in the company's primary market. Summarize whether macro is tailwind or headwind.
  6. 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).

how to use equity-research

How to use equity-research on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add equity-research
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/anthropics/financial-services-plugins --skill equity-research

The skills CLI fetches equity-research from GitHub repository anthropics/financial-services-plugins and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/equity-research

Reload or restart Cursor to activate equity-research. Access the skill through slash commands (e.g., /equity-research) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.826 reviews
  • Pratham Ware· Dec 28, 2024

    equity-research has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Xiao Perez· Dec 20, 2024

    equity-research reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Naina Bansal· Nov 27, 2024

    equity-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Yash Thakker· Nov 19, 2024

    Solid pick for teams standardizing on skills: equity-research is focused, and the summary matches what you get after install.

  • Kiara Harris· Nov 11, 2024

    Registry listing for equity-research matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Naina Kapoor· Oct 18, 2024

    Registry listing for equity-research matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Dhruvi Jain· Oct 10, 2024

    We added equity-research from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Kiara Martinez· Oct 2, 2024

    equity-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Naina Thomas· Sep 25, 2024

    Solid pick for teams standardizing on skills: equity-research is focused, and the summary matches what you get after install.

  • Oshnikdeep· Sep 17, 2024

    equity-research fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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