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Issue Throughput — String Normalisation + Adjacent Row Changes
x402
Issue Throughput — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs two analytical reports on issue throughput data: string normalisation of component/text fields and adjacent-row change detection for issues opened or closed metrics.
Price / call$0.01
Success—
StatusUnknown
How this service works
Issue throughput — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied issue throughput records (issues_opened, issues_closed). 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 analytical reports per call: (1) a string normalisation report identifying and standardising inconsistent text values in component and related fields, and (2) an adjacent row changes report showing differences between consecutive rows for the selected metric (issues_opened or issues_closed). Covers up to 200 input rows.
Example use cases
Daily bug count drift detection
“I have a CSV of daily issue records for our components over the last quarter — can you check for adjacent row changes in issues_opened so I can see where the counts shifted significantly day over day?”
Component name cleanup in issue logs
“Our issue tracking export has inconsistent component name formatting across rows — can you run string normalisation on the component field in my issues_closed dataset so everything is standardised?”
Sprint retrospective data audit
“I need to prepare for our sprint retro — can you analyse these 150 rows of issue throughput records and give me both a string normalisation report and an adjacent row changes report for issues_closed?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-13-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have issue throughput records (issues opened/closed) that need both text field standardisation and sequential row-change analysis in a single low-cost call. It is purpose-built for software engineering metrics with a specific schema, so prefer it over general-purpose analytics when your data matches the issues_opened/issues_closed structure.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, component, date, issues_opened, issues_closed) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside allowed range trigger validation failure
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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