CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Universe-aggregate cross-factor-class divergence detector. Averages t_scores across ~200 active assets from metrics.factor_scores at the latest asof_day per horizon (excludes OPT), then runs three hardcoded patterns over TR/VOL/FLOW only: Ignition (TR+VOL extreme), Capitulation (FLOW+TR collapsed), Distribution (outflows while trend holds). Live path uses fixed thresholds, not the adaptive percentile engine. Returns ok, asof_day, total_alerts, by_type counts, by_horizon grouping, ranked alerts array (severity-weighted by horizon), durationMs. Market-wide regime read, not per-asset; use for top-down inflection scanning.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per (asset, day) factor t-score breakdown plus composite score, wrapped under an `explanation` JSONB blob with the queried `signal_id`, `day`, `asset` echoed back at the top level. Surfaces class x horizon t-scores (CORR, EFF, FLOW, FUT, OB, OPT, TR, VOL) and the weighted composite from metrics.factor_scores and metrics.composite. Note: the underlying signals.signal_explain() function does not currently read signal_log or signal_registry, so the explanation is asset-day scoped, not signal-trigger scoped. Use for inspecting which factor classes were hot on a given asset-day, not for a per-signal trigger justification.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Recently triggered atomic signal events from CRYPTYX's 143-signal registry, served from api.v_signals_atomic_ux. Returns up to 50 events as { events: [{ asset, signal_id, confidence, triggered_at }] } where triggered_at is the day-level asof_day, filtered to is_triggered=true. Single query param: since (ISO date, default 24h back, clamped to max 7 days). Ordered by asof_day DESC then asset. Use as a change-detection digest of which atomic signals fired across ~200 assets — pair with /api/signals/catalog or /api/signals/explain to resolve class, geometry, grade, and regime context.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Signal trigger-activity leaderboard over a configurable lookback (window=7-365 days, default 30). Reads signals.signal_log and joins signals.signal_registry to return per-signal rows: signal_id, total_days, triggered_days, trigger_events, trigger_rate_pct, avg_confidence, confidence_std, assets_triggered, last_triggered, class, horizon, plus a per-horizon `walk_forward` block (latest 180d/70-30 IS/OOS split: is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade) so an agent reading the leaderboard sees firing frequency AND robustness in one pass. Ranks 143 atomic + 9 composite signals across ~200 assets by avg_confidence DESC, then trigger_rate_pct.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset spot order-book depth timeseries from api.asset_liquidity_timeseries_v1: ob_bid_50bp_usd, ob_ask_50bp_usd, ob_bid_100bp_usd, ob_ask_100bp_usd, ob_bid_200bp_usd, ob_ask_200bp_usd, plus spot_vol_1d_usd, spot_vol_7d_avg_usd, spot_vol_30d_avg_usd. Daily aggregate anchored to UTC−1, full history or trailing days window. Handler returns a bare JSON array of rows ordered by asof_day ASC; include=futures switches the envelope to {spot:[...], futures:{...}} where futures carries latest-day fut_ob_bid/ask_*bp_usd from compat.fut_ob_agg_1d_*. Use for pre-trade depth checks and venue routing across ~200 CRYPTYX-tracked assets.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Last N days (default 30, max 365) of taker aggressor flow per asset, split into spot and futures arrays of recent rows with asof_day, asset, taker_buy_usd, taker_sell_usd, bs_ratio - pass-through of compat.spot_taker_bs_1d and compat.fut_takerbs_1d with no z-score, FLOW factor t-score, regime label, or signal context. Feeds custom flow models on CRYPTYX cleaned spot and perp taker tape

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Single-call LLM grounding bundle. Returns {ok, asofDay, brief, structured, durationMs}: top 10 + bottom 5 composite-ranked assets across ~200 universe (asset, score, asof_day), all signals triggered today with triggered_count/total_assets/avg_confidence sorted by breadth, 30d market_pulse_timeseries_v1 across 8 factor classes (positive/negative/neutral_count, avg_t_score, expand_share_pct, factor_state), totalSignalTriggers tally, plus a pre-formatted plaintext brief string ready to drop into an agent prompt. No params required. Use before any market reasoning task to anchor on today's composite ranks and signal breadth.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Daily OHLCV bars for a single asset over a configurable lookback (1-1825 days, default 90), anchored to the latest pipeline day. Response is a bare JSON array of rows with keys asof_day, asset, open_px, high_px, low_px, close_px, volume_usd, sourced from api.v_daily_ohlcv. UTC-1 canonical anchor, ~200-asset universe, up to 5 years of backfilled history. Use as the grounded spot price tape feeding all CRYPTYX factor scores and signals.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | One-shot LLM grounding snapshot. Six parallel reads in ~200-400ms. Returns asofDay, factorBreadth (assetsWithScores + activeClasses array of CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), compositeScores (topAssets top-10 + bottomAssets bottom-5, each carrying macro `regime` (expansion/consolidation/deleveraging) + `regime_confidence`), recentSignals (day, totalTriggered, bySignal aggregation), platformCounts (metrics, signals, classes), pipelineStatus (lastRunDay, status, totalDurationMs). Optional ?asset= adds perAssetMetrics: top-10 metrics ranked by absolute time-series IC with TS + CS health grades. Call before any market reasoning.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Daily aggregated-exchanges close funding rate (fr_close) for one asset, last N days, sourced from compat.fut_funding_1d (CoinGlass/Deribit, UTC-1 anchor day, ALL_EXCHANGES scope). Response is a raw JSON array of {asof_day, asset, fr_close} rows ordered DESC — no wrapper object. No annualization, no z-score, no FUT_FUNDING_STRESS signal context — use /api/ai/signals or composite endpoints for enrichment. Cheap historical funding feed for carry-trade backtests and crowding diagnostics.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | One-call agent grounding bundle. Returns latest anchor `asof_day` plus per-asset payload across four slim queries: `profile` (comp_score, comp_rank_eq, comp_rank_pct, ret_1d/7d/30d, vol_rv_7d/30d, sharpe_7d/30d), `factors[class][horizon]` cube of `t_score_pct` + `t_band` across 8 classes (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), `regime.primary` and `regime.secondary` with confidence + `resolution_mode`, and raw `liquidity` OB depth row. ~200-asset universe, single aligned `asof_day`. Drop into a prompt for quant-aware agents.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Backtest any of 143 atomic or 9 composite signals over up to 365 days. Returns totalDays, triggeredDays, triggerRate, totalTriggerEvents, avgConfidence, per-day rows[], plus a performance block: 1d/7d/14d/30d horizons each with sample_size, mean_return, median_return, hit_rate, bootstrap_ci_95, statistical_significance, is_reliable, capped by reliability_grade (green/yellow/red) and explicit caveats. The user-bounded backtest above is in-sample only; alongside it the top-level `walk_forward` block returns the latest nightly out-of-sample read at 7d/14d/30d (is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade) from analytics.signal_eval_wf_day so the IS conclusions can be cross-checked against the OOS evidence in the same response. dryrun skips signal_log writes.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset bundle of latest atomic + composite signal snapshot plus N-day event lookback, pulled from four api.v_*_ux views and grouped by asset. Response: {ok, asof_day, assets[]} where each asset carries {asset, asof_day, regime (expansion/consolidation/deleveraging), regime_confidence, atomic:{snapshot,events}, composite:{snapshot,events}}. 143 atomic signals across 8 classes (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL) and 9 IC-weighted composites, ~200 assets. Filter via assets (CSV), events_days (1-90, default 7), min_conf_pct (0-100). One call carries the full signal picture + regime gating for an agent prompt.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Forks a registered signal with a new params JSONB into an INACTIVE version row in signals.signal_params — production firing is untouched. Verifies signal_id exists in signals.signal_registry, then inserts COALESCE(MAX(version),0)+1 with is_active=false. Returns ok, signal_id, version, params, is_active, created_at. Experimentation primitive for the agent optimization loop: fork, then call /api/signals/backtest dryrun, then activate. Covers all 143 atomic signals across CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL classes.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Class-level attribution waterfall for one asset/horizon. Returns `master` (score, rank, n_classes), `classes[]` (class, class_score, n_signals, n_triggered, weight, weighted_contribution) ordered by |contribution|, `signals[]` (signal_id, class, triggered, z, confidence, quality_weight, intensity, plus `walk_forward` block per signal at the requested horizon: is_ic, oos_ic, overfit_ratio, reliability_grade), `health{}` (per signal: health_grade, predictive_grade, operational_grade, ic, hit_rate, is_anti_predictive) and `ts_class_metrics{}` (ts_a/ts_b/ts_df counts + avg_ts_ic per class). Decomposes the IC-weighted composite over 8 factor classes across ~200 assets with walk-forward robustness inlined.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Pre-flight threshold simulator for the signal registry. POST {signal_id, threshold_key, threshold_value, asof_day?} — looks up the signal's underlying metric (z-score from metrics.fact_stats window=365, or t-score from metrics.factor_scores for TR signals), counts how many of the ~200 assets would trigger at the proposed cutoff for one asof_day, returns {ok, signal_id, threshold_key, proposed_threshold, current_threshold, asof_day, n_triggered, n_total, estimated_trigger_rate, estimated_trigger_pct}. Single-day scalar only — no IC delta, no per-asset breakdown, no sweep. Use before forking params via /api/signals/fork.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Pipeline primitive that re-runs the database-side signal evaluator for a single YYYY-MM-DD day. Pass signal_id+dryrun=true → returns wouldTrigger row count from signals.signal_dryrun_count (no writes). Pass signal_id alone → executes signal_eval_day, returns insertedRows written to signal_log. Omit signal_id → executes signal_eval_all_for_day across enabled signals, returns results[] of {signal_id, inserted_rows} plus durationMs. Row counts only — no per-asset, IC, regime, or grade. Use as smoke-test or to recompute a missed eval day.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Bundles four arrays for the latest N days (max 30): master composite scores per (asset, horizon) with rank, n_classes, meta; latest-day class composites per (asset, class) with n_signals, n_triggered, meta; latest-day macro regime context (primary/secondary regime_id, confidence, resolution_mode); current intraday micro_regime state per asset and regime_type. Drives multi-horizon factor heatmaps. Scores are raw, 4 decimals — not 0-1 normalized.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Single-metric z-score backtest over 5+ yr fact history. POST {metric_id, asset, operator (gt/lt/gte/lte/abs_gt), threshold, cooldown_days?}. Returns ok, echoed params, full timeseries [{asof_day, close_px, z, pctl, triggered}], triggers [{asof_day, z, pctl, fwd_1d/7d/14d/30d/60d/90d/180d/365d, max_dd_*}] (1d-30d from analytics.forward_returns, 60d-365d on-the-fly), and summary {n_observations, n_triggers, n_triggers_raw, n_suppressed, trigger_rate, horizons.{h}.{n, mean_return, median_return, max_return, min_return, std_return, hit_rate, sharpe, max_dd_mean, max_dd_p95, max_dd_worst}} over 8 horizons. Cooldown suppresses repeat triggers. Pre-composite single-factor edge testing across 440+ metric catalog, ~200 assets.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Walk-forward backtest of an agent-supplied 8-class composite weight vector (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL, 0-2 each) over [from, to] at 7d/14d/30d horizon. Loads class composite scores from signals.class_composite_log and forward returns from analytics.forward_returns, then runs three blends in parallel — custom, IC-weighted default, equal-weight — applying ±threshold long/short rules. Returns performance.{custom,default,equal_weight} with total_days, avg_daily_return, hit_rate, sharpe, max_drawdown, cumulative_return, avg_assets_triggered, plus a daily[] array with n_bullish, n_bearish, n_total, avg_score, top_asset, top_score. Strategy-design primitive for autonomous agents benchmarking custom factor blends against CRYPTYX's production IC-weighted moat. Institutional+ tier.