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Onboarding Progress — Record Quality Audit + String Normalisation + Adjacent Row Changes
x402
Onboarding Progress — Record Quality Audit + 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 2026-11-02).
Audits data quality, normalises strings, and detects adjacent row changes in onboarding progress records (completed_steps, required_steps) for up to 200 rows, returning 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Onboarding progress — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied onboarding progress records (completed_steps, required_steps). 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 reports: (1) a record quality audit flagging nulls, out-of-range values, and malformed fields; (2) a string normalisation report identifying and standardising inconsistent team_group strings; and (3) an adjacent row changes report showing where the selected field (completed_steps or required_steps) changed between consecutive rows. All computed locally from the supplied data with no external lookups.
Example use cases
Onboarding data hygiene check
“I have 50 onboarding progress rows across several team groups and I need to audit their data quality, normalise any inconsistent team group strings, and flag where completed_steps changed between consecutive rows — can you run all three reports on the completed_steps field?”
Detecting step count regressions
“Can you analyse my onboarding records for adjacent row changes in required_steps? I want to see where the required step count jumped or dropped between consecutive rows for my teams, along with a quality audit of the data.”
Pre-pipeline data validation for onboarding metrics
“Before I load these 120 onboarding progress records into our dashboard, can you check them for data quality issues, clean up the team_group string formatting, and show me any row-to-row changes in completed_steps so I can catch problems early?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-08-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a bundled, cost-effective batch analysis of onboarding progress data covering quality auditing, string normalisation, and sequential row change detection in a single call. It is ideal for preprocessing raw onboarding exports before loading into dashboards or pipelines, and when you want all three reports for one flat fee without needing live lookups, predictions, or external integrations.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, completed_steps, required_steps) causes rejection
- Date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the allowed range trigger schema validation errors
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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