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Release Readiness String Normalisation & Secondary-Measure Weighted Mean
x402
Release Readiness String Normalisation & Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).
Performs string normalisation and secondary-measure weighted mean calculations on release readiness records containing checks_passed and checks_total fields, producing two independent analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Release readiness — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied release readiness records (checks_passed, checks_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
Two independent analytical reports: one covering string normalisation results for the supplied release readiness records, and one providing a secondary-measure weighted mean computed over the checks_passed or checks_total field across up to 200 input rows, delivered as local analytical output with no external lookups.
Example use cases
CI pipeline release gate analysis
“I have a list of 50 release readiness rows from our CI pipeline, each with a component name, date, checks_passed, and checks_total. Can you normalise the strings and compute the weighted mean for checks_passed and give me two analytical reports?”
Multi-component release health summary
“We have release check data for three components across the past week — about 20 rows total with checks_passed and checks_total per day. Can you normalize the data and run a weighted mean on checks_total so I can see which component is least ready for release?”
QA sign-off weighted scoring
“Before we sign off on this release, can you take our 15-row QA readiness dataset with checks_passed and checks_total fields, normalize the component strings, and calculate the secondary-measure weighted mean to produce two summary reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-12-034?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and a weighted mean calculation on release readiness check data (checks_passed/checks_total) in a single low-cost call, without requiring any external data lookup, prediction, or live system integration. Ideal for batch post-processing of CI/CD pipeline output where up to 200 rows need two clean analytical reports at minimal cost ($0.01 USDC).
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, checks_passed, checks_total) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null numeric values in checks_passed or checks_total may affect weighted mean computation
- field enum value not matching 'checks_passed' or 'checks_total' causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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