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Carbon & Cashmere Mantis Track Record API
x402
Carbon & Cashmere Mantis Track Record API is a paid API for AI agents from api.carbon-cashmere.de, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-14).
Returns aggregate and per-asset track record statistics for ML signal models, including hit rates, predictive edge classification, and prediction counts over a rolling 30-day window.
Price / call$0.05
Success—
StatusUnknown
How this service works
Professional crypto market intelligence. Real-time prices, signals, and market scoring.
Output
Returns a JSON object with aggregate stats (total hits, overall hit rate, count of predictive/anti-predictive/near-baseline assets, total predictions) and a per-asset breakdown including edge classification (predictive, anti-predictive, near-baseline), hit count, hit rate, average absolute return percentage, and number of classifiable predictions. Filtered by minimum sample size of 100 and a 30-day lookback.
Example use cases
Screen coins by signal edge
“Before I deploy my signal-driven strategy, show me which crypto assets your ML models classify as predictive versus anti-predictive over the last 30 days — I want to focus only on coins where the edge is real.”
Audit overall prediction hit rate
“Give me a rolled-up summary of your signal model accuracy across all crypto assets — total predictions made, how many were correct, and what the aggregate hit rate looks like for the past 30 days.”
Rank assets by model performance
“Rank all the crypto assets in your system by signal model performance — I want to see hit rates and average absolute return percentages so I can figure out which coins are actually worth trading with your signals.”
Technical details
Endpoint
GEThttps://api.carbon-cashmere.de/v1/mantis-track-recordWhen to prefer
Use this endpoint when you need a rolled-up, portfolio-wide view of signal model accuracy across many crypto assets, rather than per-coin or per-model drill-downs. Prefer this over per-asset endpoints when evaluating which coins to trust with signal-driven strategies or screening for edge at a glance.
Side effects
- No assets meet the minimum sample threshold — returns empty by_asset array
- Upstream data pipeline delay causes stale or missing stats
- Payment not attached or insufficient — 402 Payment Required
- Rate limiting if called excessively — 429 Too Many Requests
- Service unavailable during maintenance — 503
Output
Schema · Response
{
"type": "json",
"example": {
"stats": {
"hits_total": 31480,
"assets_returned": 28,
"overall_hit_rate": 0.475,
"assets_predictive": 4,
"predictions_total": 66280,
"assets_near_baseline": 18,
"assets_anti_predictive": 6
},
"filter": {
"min_samples": 100,
"lookback_days": 30
},
"by_asset": [
{
"edge": "predictive",
"hits": 1256,
"asset": "AAVE",
"hit_rate": 0.5322,
"avg_abs_return_pct": 0.5358,
"predictions_classifiable": 2360
},
{
"edge": "anti-predictive",
"hits": 604,
"asset": "BGB",
"hit_rate": 0.2547,
"avg_abs_return_pct": 0.485,
"predictions_classifiable": 2371
}
]
}
}Tags
x402
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