equity-research

The equity-research skill transforms Claude into a specialized financial analyst, automating the synthesis of complex market data into coherent investment narratives. Designed for buy-side and sell-side analysts, portfolio managers, and investment researchers, this skill streamlines the end-to-end research workflow from data gathering to final output. It effectively bridges the gap between raw data providers and decision-ready intelligence, allowing users to focus on thesis development rather than manual data aggregation. By leveraging standardized tables and rigorous analytical frameworks, it ensures consistency across reports, whether for initiating coverage, generating morning notes, or monitoring earnings updates.

• Executes multi-step research workflows by orchestrating calls to core MCP tools like qa_ibes_consensus, qa_company_fundamentals, and qa_historical_equity_price.

• Generates standardized, publication-ready research snapshots including consensus estimate tables (EPS, Revenue, EBITDA, DPS), detailed financials summaries, and valuation metrics like forward P/E and EV/EBITDA.

• Integrates macroeconomic data via qa_macroeconomic to contextually anchor individual stock performance against broader economic trends, GDP, CPI, and policy rates.

• Produces structured investment theses that define clear recommendations (buy/hold/sell), fair value ranges, bull/bear cases, and identified upcoming catalysts.

• Provides deep-dive technical analytics including volume trends from tscc_historical_pricing_summaries, beta calculation, and historical performance context.

• Users should define the target company clearly to allow the agent to pull relevant fiscal years and peer comparison benchmarks.

• For accurate output, ensure appropriate MCP connectors for financial data providers are configured and authorized within the workspace.

• The tool is best used when comparing market expectations versus actual performance, assessing business quality, or performing quick-turnaround portfolio monitoring.

• Results should be verified against official regulatory filings (e.g., 10-K, 10-Q) as part of a professional risk management and compliance workflow.

• The output is structured to allow for direct incorporation into pitch decks, research notes, or Investment Committee (IC) memos, facilitating faster decision-making cycles.