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Cryptyx Composite Score Attribution by Factor Class
x402
Cryptyx Composite Score Attribution by Factor Class is a paid API for AI agents from www.cryptyx.ai, paid per call via x402, $0.05/call, status unknown (last checked 2026-10-11).
Decomposes an asset's composite score into per-factor-class contributions and weights at a given forward return horizon, explaining why the asset is ranked where it is.
Price / call$0.05
Success—
StatusUnknown
How this service works
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.
Output
Returns an array of factor-class attribution objects for the specified asset, each with the factor class label, its weight in the composite model, and its contribution to the composite score at the requested horizon. Useful for explaining composite rankings in client reports or model audits.
Example use cases
Client reporting on ETH ranking drivers
“Can you decompose ETH's composite score for me at the 14-day horizon? I need to explain to our investors why it's ranked where it is in our model.”
Model audit and signal quality check
“Walk me through SOL's composite attribution at the 7-day horizon and flag any factor classes that might be overfitting or unreliable based on the walk-forward metrics.”
Quick factor contribution comparison
“Show me how much each factor class is contributing to XRP's composite score right now at the 60-day forecast window — I want to see which ones are actually moving the needle.”
Technical details
Endpoint
GEThttps://www.cryptyx.ai/api/signals/composite/attribution?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to explain WHY a specific asset has its composite rank — for client-facing narratives, model audits, or compliance reporting. Use over the full composite thesis endpoint when you only need factor-class attribution and not the full signal breakdown. Use before the t-score matrix endpoint when you want asset-specific factor weights rather than a full-universe scan.
Side effects
- Missing required 'asset' parameter returns 400 error
- Invalid asset symbol not in the ~200-asset universe returns 404 or empty result
- Invalid horizon value (not 7d, 14d, or 30d) returns 400 validation error
- Payment not processed or insufficient USDC returns 402 Payment Required
- Service downtime or rate limiting returns 503 or 429
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| inputrequired | object | |
| output | object |
Output
Schema · Response
{
"type": "application/json",
"example": {
"attribution": [
{
"asset": "BTC",
"class": "TR",
"weight": 0.25,
"contribution": 0.35
}
]
}
}Tags
x402
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