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Duplicate Observations Data Quality Analyzer
x402
Duplicate Observations Data Quality Analyzer is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Runs record quality audit, string normalization, and exact row deduplication analysis on supplied duplicate-observation records, returning three independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied duplicate observations records (duplicate_rows, total_rows). 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 covering: (1) a record quality audit highlighting data issues in the supplied rows, (2) a string normalization report identifying and correcting inconsistent string fields such as dataset_group, and (3) an exact row deduplication report identifying identical rows among the supplied records — all computed locally without external lookups.
Example use cases
ETL pipeline data quality gate
“Before loading my pipeline output, can you audit these 50 records for data quality issues, normalize any inconsistent strings, and flag exact duplicate rows? Each record has a row_id, a dataset_group like 'transactions' or 'events', a date in YYYY-MM-DD format, and duplicate_rows and total_rows counts.”
Monthly duplicate rate review
“I have a monthly summary of duplicate observations across 12 dataset groups — each row has a date, group name, duplicate_rows, and total_rows. Can you run the record quality audit, string normalization check, and exact deduplication analysis so I can see where my data has the worst duplication problems?”
Data warehouse cleaning report
“We're cleaning up our data warehouse and I need to audit 150 observation records for duplicates and string inconsistencies. Each record has a row_id, a dataset_group, a date, and counts for duplicate_rows and total_rows. Can you give me all three reports — quality audit, string normalization, and exact row deduplication?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 structured duplicate-observation records with row_id, dataset_group, date, duplicate_rows, and total_rows fields and need all three of: record quality auditing, string normalization, and exact deduplication in a single low-cost call ($0.01 USDC). Prefer this over general-purpose data tools when you specifically need a combined deduplication + normalization + quality audit report computed locally without any external lookups or live data connections.
Side effects
- More than 200 rows submitted — exceeds the maxItems:200 limit, request will be rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) cause validation errors
- Date field not matching YYYY-MM-DD pattern causes schema validation failure
- Numeric fields outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) cause validation errors
- Empty rows array (minItems:1 not satisfied) returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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