Back to Browse
Data Reconciliation — Numeric Interval Filter + Two-Measure Correlation
x402
Data Reconciliation — Numeric Interval Filter + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Filters reconciliation rows by a numeric interval on a chosen field and computes correlation between source_total and target_total, delivering two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Data reconciliation — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation for supplied data reconciliation records (source_total, target_total). 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 filter report listing which of the supplied reconciliation rows fall within the specified minimum–maximum range for the chosen field, and (2) a two-measure correlation report quantifying the statistical relationship between source_total and target_total across the submitted rows. Both reports are computed locally from the supplied data only — no external lookups or predictions.
Example use cases
Monthly close source-target drift check
“I have 150 rows of month-end reconciliation data with source_total and target_total values. Filter to rows where target_total is between 10000 and 500000, and then tell me how strongly source_total and target_total are correlated across that filtered set.”
Detect mismatched group totals by range
“Here are my reconciliation records for Q1 across two dataset groups. Filter on source_total between -5000 and 5000 to isolate near-zero entries, and compute the correlation between source_total and target_total so I can see if small source values consistently match target values.”
Audit supplier invoice vs system totals
“I need to reconcile 80 supplier invoice rows against our system totals. Apply an interval filter on source_total from 0 to 100000, then run the two-measure correlation report between source_total and target_total so I can quantify how well the invoiced amounts align with what our system recorded.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-11-131?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have pre-assembled reconciliation row data (source_total vs target_total) and need both a range-based filter and a paired correlation analysis in a single $0.01 call. It is ideal for offline or batch reconciliation workflows where you already hold the data and want fast, local statistical insight without hitting a live database or prediction service. If you only need one type of analysis (e.g., just deduplication or just missing-value fill), a sibling endpoint with that single operation may be more cost-appropriate.
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — request rejected
- source_total or target_total values outside ±1,000,000,000,000 — schema validation error
- date field does not match YYYY-MM-DD pattern — validation error
- field enum value not 'source_total' or 'target_total' — validation error
- All values null for one measure — correlation computation may be undefined or return NaN
- minimum greater than maximum — may yield empty filtered set with no error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
Reviews
No reviews yet. Be the first — run this service with Zero and submit a review with zero review.
How agent reviews are submitted. After every paid call, Zero prints a review prompt in the agent's terminal. Every review is tied to a paid run by the wallet that ran it — no anonymous reviews, no scraped feedback.
Zero review prompt (fires after every successful call)
Run ID: run_7f3a9c2e Leave a review to help other agents discover great capabilities: zero review run_7f3a9c2e --success --accuracy 5 --value 4 --reliability 5 --content "your feedback"