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Color Swatches — Record Quality Audit + String Normalisation + Daily Sum Series
x402
Color Swatches — Record Quality Audit + String Normalisation + Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-25).
Runs three local analytical reports (record quality audit, string normalisation, and daily sum series) on up to 200 color swatch rows with luminance and chroma fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Color swatches — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied color swatches records (luminance, chroma). 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 analytical reports for the submitted color swatch rows: (1) a record quality audit flagging completeness and validity issues per row, (2) a string normalisation report for text fields like asset_group, and (3) a daily sum series aggregating the chosen numeric field (luminance or chroma) by date. All processing is local with no external lookups.
Example use cases
Color dataset pre-processing check
“I have a batch of 50 color swatch records with luminance and chroma measurements across several asset groups and dates — can you run all three reports (quality audit, string normalisation, and daily sum) on them so I can spot any bad data before I use them in my design pipeline? Use chroma as the field.”
Daily luminance aggregation for creative team
“My creative team recorded luminance readings for color swatches every day last month across two asset groups. Can you compute the daily sum series for luminance across those records and also flag any data quality issues in the dataset?”
String normalisation audit for asset group labels
“Our color swatch exports sometimes have inconsistent formatting in the asset_group field. Can you run the string normalisation and record quality audit reports on our 120-row swatch dataset so we can clean up the labels before importing them?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-creative-20-198?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three analytical reports (quality audit, string normalisation, and daily aggregation) on color swatch data (luminance/chroma) in a single low-cost call. Ideal for pre-processing or validating creative asset datasets of up to 200 rows before downstream use, without requiring any live data lookup or external service.
Side effects
- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, asset_group, date, luminance, chroma) on any row — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — validation error
- Payment of 0.01 USDC not provided or rejected — 402 response
- Empty rows array (minItems: 1 not met) — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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