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Validator Uptime — String Normalisation + IQR Outlier Flags
x402
Validator Uptime — String Normalisation + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Normalises string fields and flags IQR-based outliers in validator uptime records (online_minutes, observed_minutes) for up to 200 rows, returning 2 analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Validator uptime — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied validator uptime records (online_minutes, observed_minutes). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two analytical reports per call: (1) a string normalisation report summarising cleaned/standardised string fields across the submitted rows, and (2) an IQR outlier flag report identifying which rows contain values in online_minutes or observed_minutes that fall outside the interquartile range, with row-level flags and summary statistics. Covers up to 200 input rows.
Example use cases
Staking pool uptime anomaly audit
“Here are 150 rows of daily validator uptime logs with online_minutes and observed_minutes. Can you normalise the string fields and flag any IQR outliers in online_minutes so I can spot validators that were behaving unusually last month?”
Observed minutes data quality check
“I've got a CSV of validator observations and I want to check the observed_minutes column for outliers using IQR analysis — can you run string normalisation and generate the two outlier-flag reports on this batch of around 80 rows?”
Pre-report data cleaning for validator dashboard
“Before I publish our quarterly validator performance report, can you clean up string inconsistencies and run IQR outlier flags on both online_minutes for these 200 validator records so I can exclude bad data points?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-finance-12-032?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of validator uptime data and need both string normalisation and IQR-based outlier detection in a single low-cost call. It is purpose-built for validator uptime records (online_minutes, observed_minutes) and returns two independent analytical reports. Prefer this over generic data tools when your dataset fits the validator/staking domain and you want structured outlier flags without building your own statistical pipeline.
Side effects
- Fewer than 1 or more than 200 rows submitted — validation error
- Missing required fields (row_id, date, online_minutes, observed_minutes, instrument_group) — schema rejection
- Date not in YYYY-MM-DD format — pattern validation failure
- Insufficient data spread for IQR calculation (e.g. all identical values) — may return empty outlier flags
- Invalid field enum value (not online_minutes or observed_minutes) — schema error
- Payment not completed via x402 — request blocked
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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