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Structured Data Observations — Numeric Interval Filter + Adjacent Row Changes
x402
Structured Data Observations — Numeric Interval Filter + Adjacent Row Changes 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).
Filters structured observation rows by a numeric interval on a chosen field and detects adjacent row changes, returning two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Structured data observations — Numeric interval filter + Adjacent row changes: Numeric interval filter + Adjacent row changes for supplied structured data observations records (valid_items, total_items). 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 reports: (1) rows from the input dataset whose chosen field (valid_items or total_items) falls within the specified [minimum, maximum] interval; (2) a list of adjacent row pairs where the chosen field value changed from one row to the next. Both reports operate on the same supplied dataset of up to 200 rows with no external lookups.
Example use cases
QA check on daily site observation exports
“Here are 120 rows of daily site observation data with valid_items and total_items — filter to only rows where valid_items falls between 5 and 200, and also tell me wherever the value changed from one row to the next.”
Detecting anomalous sequential shifts in item counts
“I want to see which rows in my observation dataset have total_items in the range 0 to 1000, and also highlight any row where total_items jumped or dropped compared to the row immediately before it — there are about 60 records.”
Validating site group data before reporting
“Before I send this report, can you run two checks on my 45 observation rows: first filter valid_items to anything between 20 and 500, and second flag any adjacent row where valid_items changed so I can investigate those transitions?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-08-127?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have structured observation data (with site_group, date, valid_items, total_items fields) and need both a numeric range filter AND adjacent-row change detection in a single low-cost call. It is ideal for lightweight data QA, pre-report validation, or sequential anomaly detection on datasets up to 200 rows, without needing external data sources or live lookups.
Side effects
- Empty or missing rows array returns an error
- More than 200 rows submitted exceeds the per-call limit
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Minimum value greater than maximum value may produce an empty interval result
- Null numeric values in valid_items or total_items may be excluded or cause unexpected behavior in comparisons
- Unsupported field enum value returns a validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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