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Backup Exercises Data Quality Suite — Record Audit, String Normalisation & Exact Deduplication
x402
Backup Exercises Data Quality Suite — Record Audit, String Normalisation & Exact Deduplication 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).
Runs three local analytical reports on backup exercise records (restore_minutes, restored_gb): record quality audit, string normalisation, and exact row deduplication — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Backup exercises — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied backup exercises records (restore_minutes, restored_gb). 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
Three independent analytical reports: (1) a record quality audit flagging missing, null, or out-of-range values across all fields; (2) a string normalisation report showing standardised versions of text fields like control_group; (3) an exact row deduplication report identifying fully identical rows. All reports are computed locally with no external lookups.
Example use cases
Pre-analysis backup data cleanup
“I have a CSV of backup exercise logs with columns row_id, control_group, date, restore_minutes, and restored_gb — can you run a quality audit, normalise the string fields, and flag any exact duplicate rows before I hand this off for analysis? There are about 150 rows.”
Identifying dirty records in restore metrics
“My backup restore dataset has some suspicious entries — some restore_minutes and restored_gb values look off, and I think there are duplicates. Can you run all three reports — quality audit, string normalisation, and deduplication — on my 80-row dataset so I can see what needs fixing?”
Validating backup drill control group data
“We ran a backup drill last month across two control groups and I need to validate the data before reporting. Can you audit record quality, normalise the group name strings, and deduplicate the rows in this backup exercise table? It has about 60 rows with restore_minutes and restored_gb for each entry.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-security-05-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have backup exercise tabular data (restore_minutes, restored_gb) and need all three of record quality auditing, string normalisation, and exact deduplication in a single call without any external API lookups or predictions. It is especially suited for pre-analysis data cleaning pipelines on small-to-medium datasets (up to 200 rows) at very low cost ($0.01 per call for all three reports).
Side effects
- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, restore_minutes, restored_gb, control_group) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Numeric fields out of allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — minItems violation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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