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Software Quality Daily Sum Series
x402
Software Quality Daily Sum 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).
Computes daily sum time series for software quality metrics (issues opened or closed) across components, returning aggregated totals per date.
Price / call$0.01
Success—
StatusUnknown
How this service works
Software quality - Daily sum series: Daily sum series for Software quality. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded daily sum series deliverable.
Output
Returns a daily sum time series where each date entry contains the aggregated total of the selected field (issues_opened or issues_closed) across all component records for that date, computed locally from the supplied rows without external enrichment.
Example use cases
Daily bug volume trend for a sprint
“I have daily issue data for components frontend and backend across a two-week sprint — can you sum up the total issues_opened per day so I can see which days had the highest defect injection rate?”
Post-release issue closure tracking
“After our release last week I tracked issues_closed for three components each day — can you compute the daily sum series for issues_closed so I can see how fast we're resolving defects over time?”
Multi-team quality dashboard aggregation
“I've got rows from four different teams with their daily issues_opened counts — can you aggregate those into a daily total sum series so I can build a quality dashboard showing the overall issue trend?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-analytics-software-quality-date-series?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, low-cost daily aggregation of software issue counts (opened or closed) from your own records, with up to 200 typed rows, and no need for external data enrichment or forecasting. Ideal for building dashboards, sprint retrospectives, or defect trend analysis from structured daily issue data.
Side effects
- Empty or missing rows array returns an error or empty result
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Null values in numeric fields are handled but may affect sum accuracy
- Invalid field enum value (not issues_opened or issues_closed) causes rejection
- Missing required fields (row_id, component, date) causes record-level validation failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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