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.
What a market regime is, the seven signals ŷRobot uses to call it, why the risk level is about drawdowns rather than returns, and how to use the page.
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.
