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Classical Brooks price-action events detected in the current trading window — the day's first range breakout, breakout follow-through, closes in the top or bottom third of an established range, long-lived-range breakouts, climactic spikes — each paired with the outcome rate measured for that exact definition in that exact window (pre-registered, ES 5-minute bars 2010-2026). Range breakouts also carry a calibrated per-event estimate of the probability the breakout closes back through its level within 10 bars (validated zero-shot on NQ 2023+: AUC 0.646, calibration error 5.1%, n=2,637). Answers 'what just happened structurally, and how did events like it resolve historically'. Works around the clock on 24-hour instruments, including the Asia-close-to-US-open gap window. Some measured rates contradict the classical claims; quote the measured numbers, not the folklore. Every read also carries two blocks that answer different questions and must not be mixed: `day_type` is the five-class day-type distribution, from the model trained for the current window. In the regular day session it is mode=day_session, with published accuracy: 66% top-1 over a complete session and 53.5% at the 90-minute mark, against a 37% majority-class baseline. In the Asian window it is mode=asia_session — trained natively on Asian windows, pre-registered, confirmed zero-shot on NQ — whose accuracy figures live in the response's own `accuracy` field and use their own label taxonomy: never quote the day-session figures for an asia read or vice versa. The gap window has no validated model and returns available=false there. `shape` is plain arithmetic over the bars already printed (where price closed inside its own range, how much of the travel was one-way, deepest pullback) — no model, no accuracy claim, available in every window including the gap. Report day_type as a distribution with its baseline; report shape as measurement, never as a forecast. **`day_type.analysis` is the block to lead with (day-session reads only; the asia_session read carries no analysis layer)** — it answers 'should today's read be trusted at all' before it answers 'what is today'. It carries: `confidence` (the model's own conviction crossed with how consistently the most similar past sessions resolved — both high has been right 95% of the time, both low only 41%, against a 66% baseline; say which bucket today falls in and stop treating a low-confidence read as a call); `live_now` (patterns mechanically confirmed on today's bars so far — e.g. 'broke yesterday's low then reclaimed it = bear trap confirmed' — this is what actually happened, trust it over any statistical checklist); `what_to_watch` (patterns over-represented on this day type, each with a status_today of yes/no/forming/unknown and a concrete way to verify it intraday; use the ordering, not the raw lift decimals); and `summary` / `summary_zh`, a one-line verdict written to be relayed verbatim — if you pass along only one sentence, pass that one. Descriptive statistics — not a recommendation. Check window_is_live before calling a read 'now'.

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Weis Wave volume-price structure: price grouped into waves with volume summed per wave, plus which of five classical volume-price events have fired. Each event carries the win rate measured for it on sixteen years of S&P 500 futures data, including the two that came out REVERSED against the tradition. Answers 'is there volume behind this move'. Quote the measured reference numbers rather than the folklore. Spot FX has no volume at all — use CME currency futures (6E=F) instead. GC=F carries exchange volume and is the gold instrument here. A spot-gold request (XAUUSD) answers with the XAUT-USD token reading plus a note — that is the Tether Gold token's order book, a different instrument. Use session='full' to match the published reference-rate window, or the default 'rth' for a regular-session-only read.