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Time Series Completeness — Numeric Interval Filter + Base-100 Series
x402
Time Series Completeness — Numeric Interval Filter + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Filters time series completeness records by a numeric interval and generates a Base-100 indexed series for up to 200 rows of observed vs. expected data points, producing two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Time series completeness — Numeric interval filter + Base-100 series: Numeric interval filter + Base-100 series for supplied time series completeness records (observed_points, expected_points). 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 independent analytical reports: (1) a numeric interval-filtered view of the supplied completeness records showing rows where the selected field (observed_points or expected_points) falls within the specified minimum/maximum range, and (2) a Base-100 indexed series anchored at the specified base_index row, normalizing values relative to that baseline. Both reports are computed locally without external lookups, covering up to 200 input rows.
Example use cases
Daily sensor data completeness check
“I have daily sensor readings across two device groups for October — here are 10 rows with observed and expected measurement counts. Filter to rows where observed_points is between 0 and 100, use the first row as the base index, and give me both the interval filter report and the Base-100 series so I can see which days had gaps.”
IoT pipeline monitoring across groups
“Can you analyze completeness of my IoT data pipeline? I'll give you 50 rows with dataset_group, date, observed_points, and expected_points. Filter the expected_points field to values between 100 and 500, anchor to base index 0, and return both the numeric interval report and the normalized Base-100 series.”
Data warehouse ingestion audit
“I need to audit my data warehouse ingestion completeness for Q3 — I have 120 rows of daily observed vs expected record counts split by group. Filter observed_points between 1000 and 50000, set the base at row index 5, and produce both completeness reports including the Base-100 indexed trend.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-16-128?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of time series completeness data (observed vs. expected counts) and need both a numeric interval filter and a Base-100 indexed series in a single paid call. It is ideal for offline/local analytical computation where no live data lookup, external enrichment, or prediction is needed — just deterministic statistical transformation of supplied rows. Prefer it over general-purpose analytics when you specifically need the paired interval-filter + base-indexed output in one shot at low cost ($0.01 USDC for both reports).
Side effects
- Fewer than 1 or more than 200 rows supplied — request rejected
- Date strings not matching YYYY-MM-DD pattern — validation error
- observed_points or expected_points outside allowed numeric bounds (±1,000,000,000,000) — validation error
- base_index out of range (0–199) or exceeding actual row count — error or unexpected baseline
- minimum greater than maximum — may return empty filtered set
- Missing required fields (row_id, date, observed_points, expected_points) per row — schema validation failure
- Payment of 0.01 USDC not completed via x402 — request blocked
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number | |
| base_index | integer |
Tags
x402
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