io.github.gigshow/decker

Market State v0 — current engine structural state for a symbol/timeframe (latest evaluated bar, persisted engine emit read as-is, zero recompute). DOMAIN FRAME (why this engine exists): the market is read as a TARGET GAME — every coordinate comes from a *verified anchor* (a past level where a triggered move actually succeeded). The `game` block tells you the context that matters: game.status = forming_target (new anchor set, awaiting test) | testing_target (price is testing whether the declared …

AI-synthesized market reading for a symbol/timeframe, in customer-facing language: current state description, directional bias scores, bidirectional break targets, MTF verdict per timeframe, and an execution hint (stance + long/short setups). Engine-native raw fields are NOT exposed here — use the REST raw contract (GET /public/reading) or decker.get_market_state for those.

Active trading signals for the current user (with Skill Overlay applied), in customer-facing shape: coordinates (entry/target/stop), decision (ENTER/WAIT/SKIP), action_gate posture (GO/WATCH/HOLD — a stance, not an order command), progress, MTF verdict, and a plain-language summary_ko line. risk_reward_ratio is computed on the DISPLAYED coordinates (after overlay). Signals are retained rather than cut when they age (turn-retention policy) — read freshness_state (open|aged) / age_bars / freshness…

Market State v0 — per-bar state timeline for a symbol/timeframe (same schema as decker.get_market_state, except each item carries a SLIM `game` tag {status, target_id, zt_regime, provenance} instead of the full game block — read status transitions across bars to see how the target game unfolded (forming → testing → resolved/failed); ascending by bar_ts). Bars the engine did not emit are simply absent (honest gaps, no filling).