Equity Research
Synthesize IBES consensus, company fundamentals, price history, and macro data into structured equity research snapshots via MCP tools.
Overview
Equity Research is an agent skill most often used in Idea (also Validate) that combines MCP consensus, fundamentals, price, and macro pulls into structured equity research snapshots.
Install
npx skills add https://github.com/anthropics/financial-services-plugins --skill equity-researchWhat is this skill?
- Routes qa_ibes_consensus for EPS, Revenue, EBITDA, and DPS median/mean, dispersion, and actuals
- Pulls qa_company_fundamentals for income statement, balance sheet, and cash flow ratio context
- Uses qa_historical_equity_price for performance and valuation framing
- Frames every dataset around where consensus might be wrong
- Outputs standardized tables for quick opportunity assessment
Adoption & trust: 1.4k installs on skills.sh; 30.5k GitHub stars; 3/3 security scanners passed (skills.sh audits).
What problem does it solve?
You need a defensible stock snapshot but scattered MCP tool outputs never merge into one thesis-driven research brief.
Who is it for?
Builders with financial MCP tools installed who want repeatable equity memos for tickers, comps, or investment cases.
Skip if: Users without the listed QA MCP endpoints, or anyone needing licensed investment advice rather than agent-assisted research synthesis.
When should I use this skill?
Researching stocks, comparing estimates to actuals, analyzing company financials, assessing equity valuations, or building investment cases.
What do I get? / Deliverables
You get tabular consensus versus fundamentals and price context tied to an explicit view on where estimates may be wrong.
- Structured equity research snapshot
- Standardized data tables
- Investment thesis narrative
Recommended Skills
Journey fit
Spans multiple journey phases - primary shelf plus alternate fits below.
Stock and fundamentals research is canonical on the Idea shelf when you are exploring markets or investment theses before building a fintech product or report. The workflow is oriented toward gathering and tabulating external market data into a coherent narrative, which matches idea-phase research rather than shipping code.
Where it fits
Pull consensus and fundamentals for a ticker before deciding whether your niche fintech idea has a credible public-company analogue.
Size a paid research newsletter by testing whether MCP pulls produce enough structured tables for one flagship equity brief.
How it compares
Use as a structured analyst playbook on top of MCP data feeds, not as a replacement for Bloomberg-style terminals or compliance-reviewed research.
Common Questions / FAQ
Who is equity-research for?
Solo builders, indie fintech makers, and power users who already expose IBES, fundamentals, and price MCP tools and want consistent research formatting.
When should I use equity-research?
Use it in Idea (research) when exploring tickers or sectors, and in Validate (scope) when grounding a product or content bet in analyst consensus and reported financials.
Is equity-research safe to install?
Check the Security Audits panel on this page; the skill drives network-backed MCP calls and market data access that you should scope to trusted plugins and keys.
SKILL.md
READMESKILL.md - Equity Research
# 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).