equity-research
Generate professional equity research snapshots using consensus estimates, company fundamentals, historical pricing, and macroeconomic indicators to build investment theses.
Introduction
The equity-research skill empowers financial analysts to generate professional-grade equity snapshots by synthesizing complex market data into a coherent investment narrative. Designed for buy-side and sell-side analysts, this tool acts as a structured workflow orchestrator that bridges raw data from MCP providers with the expert judgment required for high-conviction decision making. By automating the retrieval and consolidation of disparate data points, users can move quickly from initial query to a completed, publication-ready research note.
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Aggregates IBES analyst consensus data including mean/median EPS, revenue, EBITDA, and DPS estimates, along with analyst count and range dispersion.
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Processes company fundamentals via historical income statements, balance sheets, and cash flow data to derive critical ratios like ROE, ROIC, and leverage metrics.
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Integrates historical pricing data (OHLCV, total returns, beta) and recent momentum analysis through TSCC pricing summaries.
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Incorporates macroeconomic contextual indicators like GDP, CPI, unemployment rates, and PMI to assess sector-specific tailwinds and headwinds.
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Outputs standardized, professional-grade tables covering consensus estimates, financial trends, and valuation summaries (Forward P/E, EV/EBITDA).
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Provides a concluding Investment Thesis framework with recommendation logic, fair value ranges, and clear bull/bear case synthesis.
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Use this skill when initiating coverage, drafting morning notes, updating earnings snapshots, or performing rapid valuation assessments.
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Requires active connectivity to MCP tools: qa_ibes_consensus, qa_company_fundamentals, qa_historical_equity_price, tscc_historical_pricing_summaries, and qa_macroeconomic.
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Inputs typically require a company ticker or name; the output is a synthesized research report formatted for immediate use in professional financial communications.
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Always verify AI-generated financial data against primary filings (e.g., 10-K, 10-Q) and maintain a critical eye on macro assumptions.
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This tool is intended for use within Claude Cowork or Claude Code environments and is part of the broader financial-services-plugins ecosystem.
Repository Stats
- Stars
- 7,822
- Forks
- 1,000
- Open Issues
- 42
- Language
- Python
- Default Branch
- main
- Sync Status
- Idle
- Last Synced
- Apr 29, 2026, 07:15 AM