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Code Review Data Quality Suite: Record Audit + String Normalisation + Numeric Row Ordering
x402
Code Review Data Quality Suite: Record Audit + String Normalisation + Numeric Row Ordering 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 three local analytical reports on code review records (pull requests, review hours): record quality audit, string normalisation, and numeric row ordering — no external lookups or predictions.
Price / call$0.01
Success—
StatusUnknown
How this service works
Code review — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied code review records (pull_requests, review_hours). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns three independent analytical reports for the submitted code review rows: (1) a record quality audit flagging issues per row, (2) a string normalisation report for the component field, and (3) a numeric row ordering report ranked by the chosen field (pull_requests or review_hours). All processing is local with no external lookups.
Example use cases
Pre-merge code review data cleanup
“I've got a CSV of our team's weekly code review stats — component names, dates, pull request counts, and review hours. Can you audit the record quality, normalise the component strings, and order the rows by review_hours so I can spot outliers before importing it into our dashboard?”
Engineering metrics QA for sprint report
“Before I send out our sprint report, can you run all three checks — quality audit, string normalisation, and numeric ordering by pull_requests — on these 80 rows of code review data I'm pasting in? The fields are row_id, component, date, pull_requests, and review_hours.”
Detect bad records in PR tracking sheet
“Our pull request tracking sheet has some messy entries — inconsistent component names and possibly missing review hours. Can you do a record quality audit and string normalisation on up to 150 rows, ordered by pull_requests, so I know which rows need fixing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-software-11-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, affordable ($0.01) set of three data quality operations — audit, string normalisation, and numeric ordering — on up to 200 code review records in a single call, without needing live data lookups, ML predictions, or external integrations. Ideal for pre-import data cleaning or sprint reporting pipelines.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, component, date, pull_requests, review_hours) cause rejection
- Invalid date format (not YYYY-MM-DD) triggers a schema error
- Numeric values outside allowed range cause validation failure
- Empty rows array is rejected
- Payment not included or insufficient USDC causes x402 payment error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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