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Commercial Proposal Comparisons — Record Quality Audit + String Normalisation + Base-100 Series
x402
Commercial Proposal Comparisons — Record Quality Audit + String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).
Runs three local analytical reports on commercial proposal data (quoted_amount or delivery_days): record quality audit, string normalisation, and base-100 indexed series — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Commercial proposal comparisons — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series 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 analytical reports computed locally on the supplied rows: (1) a record quality audit flagging missing, null, or malformed values in the specified field; (2) a string normalisation report cleaning and standardising company_group and other string fields; (3) a base-100 index series rebasing the chosen numeric field (quoted_amount or delivery_days) relative to the specified base row. No external data is fetched or returned.
Example use cases
Vendor quote quality audit
“I have 50 supplier proposal rows with company names, dates, quoted amounts, and delivery days — can you run the three reports (quality audit, string normalisation, base-100 series) on the quoted_amount field, using the first row as the base index, so I can spot data issues and see how quotes compare?”
Delivery days rebased comparison
“I want to compare delivery day commitments across 30 commercial proposals from different vendors — run the record quality audit, string normalisation, and base-100 series on the delivery_days field with row 0 as the base so I can see which suppliers are faster or slower relative to the baseline.”
Procurement data normalisation check
“Before I send this batch of 80 proposal comparison records to my procurement team, can you audit them for quality issues and normalise the company_group strings? Use quoted_amount as the field and index from row 0 — I need all three reports.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-24-201?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous analytical passes — quality audit, string normalisation, and base-100 indexing — on commercial proposal or vendor bid data in a single $0.01 call. It is ideal for procurement workflows where you want to validate data integrity, standardise string fields, and create a rebased numeric comparison series before further analysis. Prefer it over general-purpose analytics when your data maps cleanly to the quoted_amount/delivery_days schema and you need all three report types without external lookups or predictions.
Side effects
- rows array empty or missing — API returns validation error
- more than 200 rows submitted — rejected with maxItems error
- base_index out of range for submitted row count — validation error
- date strings not matching YYYY-MM-DD pattern — schema rejection
- quoted_amount or delivery_days outside ±1,000,000,000,000 bounds — validation error
- field enum value not 'quoted_amount' or 'delivery_days' — schema rejection
- row_id missing or empty string — required field validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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