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Commercial Proposal Comparisons — Record Quality Audit + String Normalisation + Grouped Numeric Summary
x402
Commercial Proposal Comparisons — Record Quality Audit + String Normalisation + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs three analytical reports on commercial proposal data: a record quality audit, string normalisation, and grouped numeric summary for quoted_amount or delivery_days fields across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Commercial proposal comparisons — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary for supplied commercial proposal comparisons records (quoted_amount, delivery_days). 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 reports: (1) a record quality audit flagging missing, malformed, or out-of-range values across the submitted rows; (2) a string normalisation report cleaning and standardising the company_group field; and (3) a grouped numeric summary (e.g. count, sum, mean, min, max) of either quoted_amount or delivery_days, aggregated by company_group — all computed locally with no external lookups.
Example use cases
Supplier bid data quality check
“I've got 50 rows of supplier bid records — each with a row ID, company group, date, quoted amount, and delivery days. Can you run a record quality audit on them, normalise the company name strings, and give me a grouped numeric summary of the quoted_amount field so I can spot any dirty data before our procurement review?”
Delivery days comparison across vendors
“Here are 120 proposal rows from our last RFQ process with company groups like 'FastShip Inc', 'fastship inc', and 'FastShip INC' — can you audit the record quality, clean up those vendor name strings, and produce a grouped summary of delivery_days by company group?”
Pre-review cleanup of bid comparison sheet
“Before I send this to the finance team, can you check these 30 commercial proposal rows for quality issues, standardise the company group labels, and generate a grouped numeric summary of quoted_amount — I want to make sure the data is clean and the totals make sense per group?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-24-194?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled analytical operations — quality auditing, string normalisation, and grouped numeric summarisation — on commercial proposal or bid comparison data (quoted_amount, delivery_days) in a single low-cost call. It is ideal for pre-review data cleaning pipelines where you want to catch dirty records, standardise vendor names, and produce group-level stats without any external data lookups or predictions. Prefer it over general-purpose analytics tools when your data fits the commercial proposals schema and you want all three reports for $0.01 in one round-trip.
Side effects
- More than 200 rows submitted — endpoint rejects with a validation error
- Missing required fields (row_id, company_group, date, quoted_amount, delivery_days) cause row-level errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 range cause schema rejection
- Invalid field selector (not 'quoted_amount' or 'delivery_days') causes enum validation error
- Empty rows array (minItems: 1 not met) returns validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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