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Source Attribution Grouped Numeric Summary + IQR Outlier Flags
x402
Source Attribution Grouped Numeric Summary + 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 2026-10-23).
Computes grouped numeric summaries and IQR-based outlier flags for source attribution records (cited_sources, verified_links) across up to 200 rows, producing two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Source attribution — Grouped numeric summary + IQR outlier flags: Grouped numeric summary + IQR outlier flags for supplied source attribution records (cited_sources, verified_links). 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 grouped numeric summary breaking down the selected field (cited_sources or verified_links) by channel_group with statistics like mean, median, min, max, and count; (2) IQR-based outlier flags identifying which individual rows have values outside the interquartile range. No external lookups or predictions are made — all analysis is performed on the supplied data.
Example use cases
News channel source attribution audit
“I have attribution records for two news channel groups over the past week — each row has a row_id, date, channel_group, cited_sources, and verified_links. Can you group them and give me a numeric summary plus flag any cited_sources values that are IQR outliers?”
Verified links anomaly detection
“Here are 150 rows of source attribution data with channel_group and verified_links counts. Can you run grouped statistics on verified_links and use IQR to flag which rows look like outliers?”
Multi-group editorial quality check
“I'm tracking cited_sources across group-a and group-b channels over the last month. Can you summarize the numeric distribution by group and highlight any rows where cited_sources fall outside the interquartile range?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-news-02-094?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have tabular source attribution records with cited_sources or verified_links counts grouped by channel categories and need both summary statistics and outlier detection in a single call. It is ideal for datasets up to 200 rows where no external data enrichment, live lookups, or predictive modeling is needed — purely local analytical computation on supplied data. Prefer this over generic statistical tools when your data specifically involves news/media source attribution with channel_group dimensions.
Side effects
- Empty or missing rows array returns an error
- More than 200 rows submitted exceeds the maximum and will be rejected
- Invalid date format (non-YYYY-MM-DD) fails schema validation
- Missing required fields (row_id, channel_group, date) cause row rejection
- Non-numeric values for cited_sources or verified_links (outside null) fail validation
- Invalid field enum value (not cited_sources or verified_links) returns an error
- Payment failure via x402 protocol results in no report being returned
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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