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Commercial Proposal Comparisons — Record Quality Audit, String Normalisation & Numeric Interval Filter
x402
Commercial Proposal Comparisons — Record Quality Audit, String Normalisation & Numeric Interval Filter 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).
Audits record quality, normalises strings, and filters rows by numeric interval for commercial proposal comparison datasets (quoted_amount, delivery_days) — up to 200 rows, 3 reports per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Commercial proposal comparisons — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter 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
Three independent analytical reports covering: (1) a record quality audit flagging missing, null, or malformed fields; (2) a string normalisation report for the company_group field; and (3) a numeric interval filter report listing rows where the selected field (quoted_amount or delivery_days) falls within the specified minimum–maximum range. All computed locally from the supplied rows with no external lookups.
Example use cases
Procurement bid data quality check
“I have 40 vendor proposal rows with quoted_amount and delivery_days — can you run a record quality audit, normalise the company group strings, and filter to only show bids where quoted_amount is between 1000 and 50000?”
Detecting out-of-range delivery promises
“Run the numeric interval filter on my 80 proposal comparison records for the delivery_days field, keeping only rows between 5 and 30 days, and also give me the quality audit and string normalisation reports for the same dataset.”
Cleaning messy RFQ comparison export
“I exported an RFQ comparison spreadsheet with 150 rows — there are inconsistent company name spellings and some null values. Can you audit the record quality, normalise the company_group strings, and filter quoted_amount between 0 and 100000 so I can see which records are clean and in scope?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-24-197?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of commercial proposal or vendor bid data and need all three of: record quality auditing, string normalisation, and numeric range filtering in a single low-cost call ($0.01 USDC). It is ideal for pre-processing RFQ or procurement comparison exports before analysis, when no external enrichment, prediction, or live data lookup is needed.
Side effects
- Rows array empty or exceeds 200-item limit — validation error
- row_id missing or blank — schema validation failure
- date field not matching YYYY-MM-DD pattern — rejected row
- minimum greater than maximum — likely empty filter result or error
- quoted_amount or delivery_days outside ±1,000,000,000,000 bounds — schema rejection
- Invalid field enum value (not 'quoted_amount' or 'delivery_days') — error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| maximum | number | |
| minimum | number |
Tags
x402
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