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Label Review — Record Quality Audit + String Normalisation
x402
Label Review — Record Quality Audit + String Normalisation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Runs two local analytical reports on label review data: a record quality audit and string normalisation, across up to 200 rows of reviewed_records and changed_labels data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Label review — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied label review records (reviewed_records, changed_labels). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Two independent analytical reports generated locally: (1) a record quality audit covering issues in the reviewed_records and changed_labels fields, and (2) a string normalisation report covering dataset_group and other string fields — all computed for up to 200 supplied rows without any external lookups or predictions.
Example use cases
ML annotation pipeline quality check
“I have logs from our annotation team's label review sessions — each row has a date, a dataset group name, how many records were reviewed, and how many labels were changed. Can you audit these for quality issues and normalise any inconsistent string values? I have about 80 rows covering the past month.”
Dataset group label change analysis
“We ran a label review process across three dataset groups last quarter and I want to make sure the data is clean before we use it for training. Can you do a record quality audit and string normalisation on these 120 rows of reviewed_records and changed_labels?”
Daily label review export validation
“Here are our daily label review exports for the past two weeks — each row has a row_id, dataset_group, date, number of reviewed_records, and changed_labels. Please run the quality audit and string normalisation reports so I can spot any bad data before I hand this off to the modelling team.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-12-001?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, offline-style analytical reports on label review data — specifically a quality audit of reviewed_records/changed_labels and string normalisation — for up to 200 rows at a very low flat cost ($0.01 USDC for both reports). Prefer this over general-purpose data tools when your data fits the label review schema and you want deterministic, reproducible local analysis with no external API calls or model inference.
Side effects
- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, reviewed_records, changed_labels) — validation error
- Date values not matching YYYY-MM-DD pattern — schema validation failure
- Numeric values out of allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected
- Empty rows array — minimum 1 item required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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