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Release Readiness Secondary-Measure Weighted Mean + Keyed Dataset Comparison
x402
Release Readiness Secondary-Measure Weighted Mean + Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Computes a secondary-measure weighted mean and performs a keyed dataset comparison for release readiness records (checks_passed, checks_total) across up to 200 rows in two independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Release readiness — Secondary-measure weighted mean + Keyed dataset comparison: Secondary-measure weighted mean + Keyed dataset comparison 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
Returns two independent analytical reports: (1) a secondary-measure weighted mean of the selected field (checks_passed or checks_total) across the primary dataset, and (2) a keyed dataset comparison between the primary and secondary datasets, highlighting differences by row_id. All computation is performed locally with no external lookups.
Example use cases
Pre-release QA gate weighted analysis
“I've got 150 rows of release readiness data from our CI pipeline, each with a component name, date, checks_passed, and checks_total. Can you compute the weighted mean of checks_passed (weighted by checks_total) and compare it against last sprint's dataset to see where scores diverged?”
Multi-component release health comparison
“We have two snapshots of our release checks — one from before the hotfix and one after — both with row_id, component, date, checks_passed, and checks_total. Run a weighted mean on checks_total and do a keyed comparison so I can see which components improved.”
Release candidate audit across two builds
“I need to compare release readiness between build A and build B. Both datasets have up to 100 rows with checks_passed and checks_total per component. Give me the secondary-measure weighted mean for checks_passed and flag any rows where the keyed values differ between the two builds.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-12-186?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a weighted mean aggregation (using one measure as the weight for another) and a row-keyed comparison between two release readiness datasets in a single call. It is purpose-built for release readiness data with checks_passed and checks_total fields, making it ideal for CI/CD pipelines, QA gate audits, and sprint-over-sprint release health comparisons. Prefer it over generic stats APIs when your data is already structured with row_id, component, and date identifiers.
Side effects
- Missing required fields (row_id, component, date, checks_passed, checks_total) cause validation errors
- Exceeding 200 rows per dataset returns an error
- Invalid date format (non-YYYY-MM-DD) causes schema rejection
- Null values in numeric fields may affect weighted mean calculation
- Mismatched row_ids between primary and comparison datasets result in unmatched keys in comparison report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array |
Tags
x402
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