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Reported Burned Token Fraction — Rolling Mean Report
x402
Reported Burned Token Fraction — Rolling Mean Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes a rolling mean of the burned-token fraction (burned_tokens / issued_tokens) over a sliding window across a supplied series of token observations.
Price / call$0.01
Success—
StatusUnknown
How this service works
Reported burned token fraction — Rolling mean report: Rolling mean report for Reported burned token fraction. Supplied token observations only. Deterministic calculation or caller-threshold verdict, not a live scan, safety proof or trade recommendation. Specialised preset in a shared 50-profile, 20-operation engine. 0.01 USDC includes one bounded rolling mean report report.
Output
Returns a rolling mean report for the burned token fraction (burned_tokens / issued_tokens) computed over the specified sliding window across the supplied observation rows. Output is a deterministic, calculation-based series — not a live scan or trade recommendation.
Example use cases
Token burn trend smoothing
“I have a series of daily token burn snapshots for a DeFi project — burned and issued counts for each day. Can you run a rolling mean on the burned fraction with a window of 3 to smooth out the noise?”
Deflationary pressure monitoring
“Here are 10 weekly observations of burned vs issued tokens for my project. Compute a rolling mean with window size 4 so I can see if deflationary pressure is increasing over time.”
Pre-listing token health check
“Before we list this token, I want to understand its burn dynamics. I have 8 historical snapshots of burned_tokens and issued_tokens. Can you calculate a rolling mean of the burn fraction using a window of 2?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-token-burned-supply-rolling?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a deterministic rolling mean of the burned token fraction from caller-supplied historical observations, particularly for tokenomics analysis, burn trend smoothing, or supply health reporting. It is purpose-built for this specific metric and does not perform live chain scans or provide investment advice.
Side effects
- Fewer than 2 rows supplied — minItems violation returns validation error
- Window size larger than number of rows — produces no valid windows
- issued_tokens value of 0 — exclusiveMinimum violation causes rejection
- Values exceeding 10^16 — maximum constraint violation
- Malformed row objects missing required burned_tokens or issued_tokens fields
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| window | integer |
Tags
x402
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