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. | 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.

Asset × asset rolling correlation matrix over a configurable window. Use for portfolio construction, diversification checks, and identifying regime shifts in cross-asset relationships.

Regime label history per day for a single asset. Use to study how an asset behaves in each regime — entry timing, sizing, and stop calibration vary materially by regime.

Class × horizon factor t-scores per asset across CRYPTYX's 8 canonical factor classes (CORR, EFF, FLOW, FUT, OB, OPT, TR, VOL). Computed from 440+ underlying metrics with policy-aware winsorization and z-capping. Use for cross-sectional ranking, sector rotation, and factor exposure analysis.

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.

Macro regime classification per asset — expansion / consolidation / contraction — with confidence (0-1). Regimes are factor-derived (not price-derived), so they shift before price action confirms. Use to gate strategies by market state — mean-reversion logic fails in trending regimes.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset triggered signal feed on the latest anchor day from api.v_asset_signals_enriched. Returns ok, symbol, asof_day, macro `regime` (expansion/consolidation/deleveraging) + `regime_confidence`, total, high_grade (count of A/B), signals[], meta. Each signal row: signal_id, name, description, class (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), horizon, value, z, confidence, ic, hit_rate, ir, regime_accuracy, predictive_grade, operational_grade, health_grade, is_anti_predictive, plus `walk_forward` block per signal at its registered horizon (is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade) from analytics.signal_eval_wf_day. Anti-predictive signals filtered out, ordered by health_grade then |z|. IC/grades are cross-sectional (universe-wide) — flagged in meta. Per-asset live firing panel with regime gating + walk-forward robustness in one call.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Cross-class conviction panels per asset — one representative metric per microstructure factor class: FUT funding stress (FUT_FUNDING_MA_7D), OPT 1M 25-delta risk-reversal skew (OPT_SKEW_RR25D_1M, BTC/ETH only), OB 100bp liquidity imbalance (OB_IMB_100BP), and FLOW 7d taker buy/sell ratio (FLOW_TAKER_BS_RATIO_MA_7D). Each panel returns current_z, current_pctl, 30-day sparkline, last_asof_day, and a one-line narrative — pulled from metrics.fact_stats over the 365d window. No raw values exposed; null panels are dropped. Use for cross-class positioning reads, not for distributional tail statistics.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Nearest-k peers in CRYPTYX's 8-class factor t-score space (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL) for a target asset at the requested horizon (7d/14d/30d/90d). Point-in-time Euclidean distance over per-class t-scores from metrics.factor_scores on the latest available day — not a cluster label, not rolling correlation. Returns target {asset, composite, ret_7d, classes} plus peers ranked by distance with composite, divergence vs target, ret_7d, and shared_classes. Use for hedge selection, basket construction, and divergence trades grounded in the protected factor engine.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset macro regime context: returns current regime id, confidence, days_in_regime streak from signals.asset_regime_day, plus conditional forward-return stats (n, mean_return, median_return, hit_rate) at 1d/7d/14d/30d horizons from analytics.forward_returns, and top-12 historical regime transition pairs. Computed live across ~200 assets — grounds sizing and strategy selection in what historically tends to happen next when this asset sits in this regime.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset triggered signal ledger over last N days (7-365, default 90), filtered to grade A/B non-anti-predictive signals only. Returns ok, symbol, days, events[] with asof_day, signal_id, name, class (one of 8: CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), direction (long/short/neutral derived from registry tags + z sign), z, confidence, horizon, grade, close_px for chart overlay, fwd_return_7d realized outcome, plus meta.ic_context=cross_sectional. Use for "when did X last fire on SOL and what happened next" backtests across ~200 assets and 143 atomic signals.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Claude Haiku-narrated per-asset conviction call. Returns `thesis` (3-5 sentence prose), macro `regime` (expansion/consolidation/deleveraging) + `regime_confidence` at the top level, plus an `evidence` pack: `composite` (score, rank, rank_pct, score_yesterday, score_delta) vs ~200 assets, `returns` (ret_1d/7d/30d, vol_rv_30d), `factors` (t_score_pct + t_band per CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL class at chosen horizon), `active_signals` (top 8 health A/B/C, anti-predictive filtered, with z/confidence/ic/hit_rate/grade), `active_signals_total`/`_high_grade` counts, and `top_ts_metrics` (5 strongest per-asset predictors w/ ts vs cs grade_divergence). Plus `ok`, `symbol`, `asof_day`, `horizon`, `source`, `model`, `generated_at`, `cache_hit`. 4h cache.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-day composite conviction trajectory for one asset across a 7-90 day window. Reads metrics.composite for the score timeline and LEFT JOINs analytics.asset_thesis_daily for optional one-liner overlay (direction + one_liner + generated_at). Returns ok, symbol, days, points[] with {d, composite, direction, one_liner, generated_at}, thesis_count, and a note flagging when the thesis populate job has not yet written rows. Score timeline is always complete; narrative overlay is honest about gaps. Use to track conviction evolution before a major move.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset predictor explorer for one symbol at 7d/14d/30d horizon. Returns up to 5 top atomic signals AND 5 top metrics ranked by |IC| times hit_rate, gated to A/B health grades, anti-predictive filtered, family-deduped, max 2 per factor class. Signals carry ic, hit_rate, ir, grade, n_triggered_180d, last_triggered, plus `walk_forward` block at the requested horizon (is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade). Metrics carry ts_grade vs cs_grade divergence, polarity, per-asset time-series ic, current_z, current_pctl (walk-forward currently signal-only — metrics blocks omit it). Use to pick the strongest, walk-forward-validated inputs for one asset before building a strategy.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Per-asset historical signal edge. For one symbol at 7d/14d/30d, returns up to 6 health-grade A/B atomic signals that actually worked on THIS asset, grouped into reversal/continuation/breakout lanes (max 2 per lane). Each setup: signal_id, name, class, grade, tags, n_triggers, hit_rate, mean_fwd_return, median_fwd_return, last_triggered, ic_global, hit_rate_global, score, plus `walk_forward` block per setup at the requested horizon (is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade) from analytics.signal_eval_wf_day — the per-asset trigger evidence and universe-wide walk-forward robustness side by side. Anti-predictive signals filtered (Phase N11 gate); MIN_TRIGGERS=3. Scope: signals_only.

Composite scores and ranks across ~200 digital assets — comp_score, comp_rank, 1d / 7d returns, factor breadth, conviction count. Snapshot or time-series mode. Use as the master ranking feed for portfolio construction, watchlist generation, and rotation strategies.

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.

Natural-language intelligence query over the full CRYPTYX state — returns answer plus structured sources cited (factor scores, signal triggers, regime context). Use when the question doesn't fit a fixed schema, or when piping an LLM agent into CRYPTYX without per-endpoint plumbing.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Latest-day Deribit IV term structure for one asset plus current put/call open-interest ratio. Returns term_structure (per-tenor rows: tenor, atm_iv, rr_25d 25-delta risk reversal, bf_25d 25-delta butterfly, iv_25c, iv_25p), pcr block (pcr, oi_put, oi_call), and asof_day. Coverage limited to Deribit venues (BTC, ETH) — out-of-scope assets return empty arrays. Raw upstream telemetry feeding the OPT factor class; use for skew reads, vol-term structuring, and options positioning context.

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.

Market-wide signal pulse — total triggers across 143 atomic signals, positive/negative counts per factor class, net breadth, asof day. Single-call market state snapshot for the universe of ~200 assets. Use to time risk-on / risk-off shifts and detect early breadth divergence.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Top-N and bottom-N assets by CRYPTYX IC-weighted composite score for the latest asof_day. Each row carries asset, comp_score, comp_rank, ret_1d, ret_7d, funding_z (FUT_FUNDING_1D), oi_roc_z (FUT_OI_ROC_30D), n_atomic and n_composite signal counts, optional sharpe_7d, optional thematic_scores keyed by composite_id, plus macro `regime` (expansion/consolidation/deleveraging) + `regime_confidence`. Stablecoins filtered. One call returns top, bottom, asof_day, durationMs — the daily "where to look" leaderboard across ~200 assets with regime gating inline.

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.

Asset × factor-class t-score matrix with rank per class — full universe of ~200 assets. Use for factor-tilt construction, sector rotation, and "show me the strongest momentum assets right now" queries.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Macro-regime synthesis from analytics.macro_regime_day — NOT per-asset. Returns ok, asof_day, current (object keyed by horizon: 1d/7d/14d/30d/60d/90d/180d/365d, each with regime_label, regime_confidence, cross_class_state, breadth JSONB, horizon_alignment JSONB, n_assets, meta JSONB), history (raw rows over lookback window), count, durationMs. Built on ~200 assets, 8 factor classes (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL). Filter to one horizon via horizon param; slim=true drops JSONB blobs for timeline use. For per-asset regimes hit /api/asset-regimes. Read multi-horizon risk-on/off posture in one call.

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.

Multi-factor z-score intersection backtest — 2-4 metric conditions chained with AND logic. Hit rate, mean forward return, sample count. Use to test confluence strategies ("when TR is bullish AND VOL is compressing AND OB depth is rising") before live deployment.

Scan a single metric across all ~200 assets for current z-score extremes — ranked, with percentile context. Use to find live anomalies and outliers — "who is at 3+ sigma on TR_TREND_STRENGTH_14D right now?"

Generate a branded narrative report (daily digest / asset deep dive / signal summary) backed by live CRYPTYX data and AI-synthesized analysis. Outputs structured sections plus markdown narrative. Use for client-facing deliverables, weekly digests, and PM commentary.

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Latest-day firing signals across ~200 assets, returned as `{ atomic, composite }`. Atomic rows: signal_id, signal_name, class (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), horizon, tags, z, confidence, confidence_pct, confidence_band, event-delta (event_type, prev/new_triggered, prev/new_confidence, delta_confidence), plus macro `regime` (expansion/consolidation/deleveraging) + `regime_confidence` per row. Composite rows: composite_id, title, composite_type, same confidence + event-delta + regime block. Filtered to live registry; excludes anti-predictive signals via analytics.signal_health.

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. | Enabled signal registry. Per row: signal_id, name, description, class (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), horizon, tags, geometry_type, active_version, active_params, params_created_at, recent_total_assets, recent_triggered_assets, recent_days_evaluated, unique_assets_observed, unique_assets_ever_triggered, trigger_rate_per_asset_day, health_grade, predictive_grade, operational_grade, plus a `walk_forward` block (latest 180d/70-30 IS/OOS split from analytics.signal_eval_wf_day: is_ic, is_hit_rate, oos_ic, oos_hit_rate, overfit_ratio, ic_delta, reliability_grade green/yellow/red). Top-level: ok, count, signals, meta.ic_context='cross_sectional', durationMs. logic_sql withheld (protected IP). Discovery surface before backtest or fork.

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. | 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.

Bullish / bearish breadth per factor class at a chosen horizon — total counts, per-class splits, net positioning. Use to read market participation: is this rally broad, or concentrated in a few names?

CRYPTYX | institutional-grade crypto intelligence: 150+ signals, 440+ metrics, 200+ assets. | Re-rank the ~200-asset CRYPTYX universe under your own class weights across the 8 factor classes (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL) at 7d/14d/30d horizon. Reads signals.class_composite_log + the active versioned default weight set, returns asof_day, horizon, total_assets, custom_weights, default_weights, summary {bullish, bearish, neutral}, ranked assets [{asset, score, default_score, delta, class_contributions, rank}], and top_movers (10 largest |delta| vs default). Encode a house view, A/B test a composite recipe, or stress-test the production weights against your own.

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.

Composite score momentum over a configurable window — score_1d, score_7d, delta per asset, ranked by acceleration. Detects regime shifts before they show in price. Use as an early-warning system for trend changes.

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. | 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. | 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. | 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. | 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. | 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. | Curated top-10 atomic signals from CRYPTYX's 143-signal registry, gated to enabled + non-anti-predictive + A/B health-graded names ranked by 7d cross-sectional IC. Each row returns signal_id, name, description, class (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), horizon, tags, geometry_type, active_version, active_params, ic_7d, hit_rate_7d, n_obs_7d, n_triggers_7d, health_grade, unique_assets_observed, unique_assets_ever_triggered, trigger_rate_per_asset_day, plus a 7d `walk_forward` block (latest IS/OOS split: is_ic, oos_ic, overfit_ratio, ic_delta, reliability_grade) so the in-sample IC and the OOS check sit side by side. Response also carries count, selection_criteria block, durationMs. Default discovery surface MCP agents call before /api/signals/catalog to short-list which signals to wire into a live strategy.

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. | 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. | 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. | Top-N composite-ranked assets from the ~200-asset universe, bundled as a single agent starter pack. Each idea returns asset, rank, composite_score, returns{ret_1d,ret_7d}, sharpe_7d, derivatives{funding_z,oi_momentum_z}, regime{regime,confidence}, dominant_factor{class,t_score} across the 8 factor classes (CORR/EFF/FLOW/FUT/OB/OPT/TR/VOL), signal_count{atomic,composite}, top_setups (top-3 atomic signals gated by health_grade A/B, not anti-predictive, n_triggers>=5, with hit_rate + mean_fwd_return + last_triggered), and top_predictors (top-3 TS-graded metrics per asset). Replaces 5 separate calls.