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Proposal Preparation Data Quality Suite (Record Audit + String Normalisation + Adjacent Row Changes)
x402
Proposal Preparation Data Quality Suite (Record Audit + String Normalisation + Adjacent Row Changes) is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).
Runs three analytical reports — record quality audit, string normalisation, and adjacent row change detection — on up to 200 proposal preparation rows containing completed_sections and planned_sections fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Proposal preparation — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied proposal preparation records (completed_sections, planned_sections). 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 reports covering: (1) record quality audit flagging missing, null, or out-of-range values; (2) string normalisation findings for text fields like document_group; (3) adjacent row change detection highlighting significant shifts between consecutive rows in the selected numeric field (completed_sections or planned_sections). All computed locally with no external lookups.
Example use cases
Pre-submission proposal data cleanse
“I need to validate my proposal preparation records before submission — can you audit them for quality issues, normalise any string inconsistencies, and flag where adjacent rows show unexpected changes in completed_sections? I have about 50 rows across two document groups.”
Tracking section completion anomalies
“We're tracking planned_sections vs completed_sections across multiple proposal document groups. Can you run the quality audit and adjacent row change report on this data so I can spot any weird jumps or bad entries before we report to stakeholders?”
Cleaning imported proposal records
“I've just imported proposal preparation data from our project management tool and I'm worried about formatting issues and data gaps. Can you run string normalisation and a record quality audit on these rows — there are about 120 entries with completed_sections and planned_sections — and tell me what needs fixing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-08-200?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a fast, low-cost ($0.01 USDC) batch quality check on proposal preparation records that combines three distinct analytical passes — quality auditing, string normalisation, and sequential row change detection — in a single call. Prefer it over single-purpose validators when you want all three report types simultaneously without external lookups or predictions, and when your dataset is 200 rows or fewer.
Side effects
- More than 200 rows submitted — request rejected with maxItems violation
- Missing required fields (row_id, date, document_group) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- field enum value not one of completed_sections or planned_sections — rejection
- Empty rows array (minItems:1 not met) — error returned
- numeric values outside ±1,000,000,000,000 bounds — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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