Estimate the intrinsic value of a public company using DCF, relative (peer multiple) and sum-of-parts (SOTP) methods, then triangulate to an implied share price with upside/downside versus the current market price. Use this skill whenever the user asks: "what is AAPL worth", "valuation of NVDA", "fair value of TSLA", "intrinsic value", "DCF for MSFT", "build a DCF", "discounted cash flow", "WACC", "terminal value", "implied share price", "upside to fair value", "is X overvalued/undervalued", "relative valuation", "peer comparison valuation", "EV/EBITDA target", "SOTP", "sum of the parts", "how much is [company] worth", "price target from fundamentals", "value this company", or any ticker in the context of computing intrinsic or relative valuation. Default to running ALL three methods (DCF + relative + SOTP-if-applicable) and presenting a blended implied price with a sensitivity table. Do not answer valuation questions from memory — always run the workflow.
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Low-risk findings worth noting
Low
Low-risk findings.
1 low severity finding. Worth noting, but not necessarily harmful.
The skill exposes the agent to untrusted, user-generated content from public third-party sources, creating a risk of indirect prompt injection. This includes browsing arbitrary URLs, reading social media posts or forum comments, and analyzing content from unknown websites.
At runtime the workflow reads free-text–influenced outsider content indirectly via yfinance/funda-data fetched by user-chosen tickers/peers, but the injected text is not shown to be explicitly ingested as arbitrary free-form text by the LLM (it’s numeric market/filing data used for calculations).
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