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Token Average Reported Trade Notional — Sequential Input-Change Attribution
x402
Token Average Reported Trade Notional — Sequential Input-Change Attribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).
Computes a sequential input-change (waterfall) attribution for the average reported trade notional of a token, comparing before and after trade/volume states.
Price / call$0.01
Success—
StatusUnknown
How this service works
Token average reported trade notional — Sequential input-change attribution: Sequential input-change attribution for Token average reported trade notional. 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 sequential input-change attribution report.
Output
A deterministic sequential input-change attribution (waterfall) report showing how changes in trade count and USD volume between the 'before' and 'after' states contributed to the change in the token's average reported trade notional. The result includes per-input contribution amounts and is not a live scan or trade recommendation.
Example use cases
Explain average trade size shift after market event
“Our token had 150 trades and $90,000 volume before a major announcement, and now has 300 trades and $135,000 volume. Run a waterfall attribution to show me how much of the average trade notional change came from the volume increase versus the trade count increase.”
Daily trading metrics attribution for DeFi token
“For our DeFi token, yesterday we had 500 trades totaling $250,000 in volume, and today we have 480 trades and $264,000 in volume. Do a sequential input-change attribution on the average trade notional so I can see what drove the per-trade size change.”
Quarterly review of trade notional drivers
“Compare two periods for our token: Q1 had 10,000 trades and $5,000,000 volume, Q2 had 12,500 trades and $7,500,000 volume. I need a sequential attribution report showing how each input — trades and volume — contributed to the shift in average reported trade notional.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-bx-token-mean-trade-waterfall?utm_source=zero.xyzWhen to prefer
Use this endpoint when you need a deterministic, decomposed attribution of how changes in trade count and traded volume drove a shift in average token trade notional between two snapshots. It is best suited for post-hoc analytical attribution rather than real-time monitoring or predictive modeling. Choose it over generic statistics endpoints when you specifically need a sequential (waterfall-style) input-change decomposition for token trading metrics.
Side effects
- Invalid input: trade count or volume_usd is zero or negative (exclusiveMinimum enforced)
- Malformed request body: missing required fields trades or volume_usd in before/after objects
- Values exceed maximum threshold (1e16)
- Payment failure: insufficient USDC balance or x402 protocol error
- Service unavailable or engine at capacity
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| after | object | |
| before | object |
Tags
x402
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