What the 0–100 AI score measures, the eight signals inside it, and how to use it as a conviction gauge.
Where the fair-value estimate comes from and how to read the gap between value and price.
How the technical model reads chart structure and how it fits into the composite score.
Why a P/E only means something against the company's own past — and how to read the Quarterly P/E chart.
What the forward return forecast contributes to the score — and its limits.
How reported financial health feeds the score, separately from the fair-value gap.
Consensus is one input, not gospel — how the score weighs it at 8%.
Seasonal tendencies are real but weak evidence — that's why they get a 4% weight.
Why jumpier stocks clear a higher bar — the volatility penalty explained.
The stock page in reading order: scorecard first, then value, forecast, and P/E history.
Scan the whole US universe by AI score and outlooks — and use breadth to avoid over-concentration.
Track the names you care about and get the daily digest — a repeatable process beats hot takes.
ŷRobot analysis is AI-generated and quality-gated; nothing on this page is investment advice.
