stock-deep-divelisted

# Stock deep dive Produces the analysis a fund manager would run before committing capital: what the business actually does, whether its economics are durable, what the price already assumes, and a scored verdict with the scenarios that would prove it right or wrong. The instinct behind asking for "superhuman" analysis is right, but the thing that makes analysis superhuman is not confidence. It is three unglamorous habits: doing the arithmetic from primary sources instead of recalling it, knowing what the market has *already* priced in, and hunting hard for the evidence that would make you wrong. Confident write-ups are common and cheap. Those three are rare, and they are what this skill enforces. ## The one idea that organises everything below **A great company and a great investment are different questions**, and only the second one is open. The market has usually already worked out that a dominant business is dominant — that view is in the price. What remains genuinely uncertain is whether the price demands more than the business can deliver. So the analysis does not stop at "is this good?". It asks: *what does the current price require to be true, and is that achievable?* That reframing is what `scripts/reverse_dcf.py` exists to answer, and it is why the valuation dimension frequently scores lowest on the best companies. ## What this needs Live access to primary sources. If you cannot search or fetch filings, **say so and stop**. Financial figures are the single h