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Document Retrieval Record Quality Audit + String Normalisation + Two-Measure Correlation
x402
Document Retrieval Record Quality Audit + String Normalisation + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Audits quality, normalises strings, and computes correlation between retrieved_bytes and request_ms for up to 200 document retrieval records, returning three analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Document retrieval — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied document retrieval records (retrieved_bytes, request_ms). 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 values, invalid formats, and anomalies; (2) a string normalisation report for the site_group field; and (3) a Pearson or similar two-measure correlation result between retrieved_bytes and request_ms — all computed locally without external lookups, covering up to 200 supplied rows.
Example use cases
Audit web crawler retrieval log quality
“I have a batch of document retrieval logs from our web crawler — each row has a row_id, site_group, date, retrieved_bytes, and request_ms. Can you run a record quality audit, normalise the site_group strings, and check the correlation between retrieved_bytes and request_ms for me?”
Detect latency-vs-size patterns in CDN logs
“We pulled 150 rows from our CDN retrieval records with fields row_id, site_group, date, retrieved_bytes, and request_ms. Please give me a quality audit of those records, normalise any messy string fields, and show me how correlated the byte sizes are with request latency.”
Validate data integrity before reporting
“Before I include our document retrieval metrics in the weekly report, can you check these rows for quality issues, clean up the site_group strings, and run a correlation between retrieved_bytes and request_ms? I have about 80 rows with row_id, date, site_group, retrieved_bytes, and request_ms.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-web-09-204?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need simultaneous data quality auditing, string normalisation, and statistical correlation on document retrieval records (retrieved_bytes, request_ms) in a single low-cost call. It is ideal for batch validation of web retrieval logs before reporting or ingestion, when you do not need live data lookup, ML prediction, or external enrichment — just fast, local analytical computation on supplied tabular data up to 200 rows.
Side effects
- Exceeds 200-row limit — request rejected or truncated
- Missing required fields (row_id, date, retrieved_bytes, request_ms) cause row-level errors
- Invalid date format (non YYYY-MM-DD) fails pattern validation
- Numeric fields out of allowed range cause validation errors
- Empty rows array returns an error
- All-null numeric columns produce undefined correlation result
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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