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Service Uptime Grouped Numeric Summary with IQR Outlier Flags
x402
Service Uptime Grouped Numeric Summary with 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 2026-10-30).
Computes grouped numeric summaries and IQR-based outlier flags for service uptime records (available_minutes, observed_minutes) grouped by component
Price / call$0.01
Success—
StatusUnknown
How this service works
Service uptime — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied service uptime records (available_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
Returns two analytical reports: (1) a grouped numeric summary (e.g. mean, median, min, max, count) of the selected field (available_minutes or observed_minutes) broken down by component, and (2) IQR-based outlier flags identifying which individual rows fall outside the interquartile range fence. Both reports are computed locally on the supplied data with no external lookups.
Example use cases
SRE weekly uptime anomaly review
“I have daily uptime logs for our microservices for the past month — each row has a component name, date, and how many minutes were available vs observed. Can you group them by component and flag any days where available_minutes looks like an outlier using IQR?”
Multi-team SLA compliance check
“We track uptime for about 8 components across two teams. I'll send you up to 200 rows with row IDs, component names, dates, and available_minutes and observed_minutes — can you give me a grouped summary per component and highlight which records are statistical outliers?”
Incident root-cause uptime drill-down
“After last week's incident I want to understand which service had the most unusual observed_minutes readings. Can you run a grouped numeric summary and IQR outlier detection on these uptime records grouped by component, analyzing the observed_minutes field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-16-094?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular service uptime data (up to 200 rows) and need both grouped descriptive statistics by component and IQR-based outlier detection in a single call without setting up any local analytics infrastructure. It is purpose-built for uptime (available_minutes, observed_minutes) data structures, making it faster to invoke than a general-purpose analytics API for this specific domain. Prefer it for lightweight, on-demand SRE analytics, SLA reviews, or post-incident uptime audits where you want statistical summaries and anomaly flags together.
Side effects
- Fewer than 1 row supplied — validation error
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, component, date, available_minutes, observed_minutes) — schema validation error
- Invalid date format (not YYYY-MM-DD) — rejected by pattern validation
- Null numeric values may be excluded from IQR computation depending on implementation
- Payment not attached or insufficient USDC — x402 payment required error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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