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Proposal Preparation — Record Quality Audit + Missing-Value Fill
x402
Proposal Preparation — Record Quality Audit + Missing-Value Fill 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).
Audits proposal preparation records for quality issues and fills missing values in completed_sections or planned_sections fields using zero, mean, or median imputation, returning two reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Proposal preparation — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill for supplied proposal preparation records (completed_sections, planned_sections). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent reports: (1) a record quality audit identifying issues such as nulls, out-of-range values, or malformed rows in the provided proposal preparation records, and (2) a missing-value fill report showing the imputed values for the specified field (completed_sections or planned_sections) using the chosen method (zero, mean, or median). Both reports are generated locally from the supplied data with no external lookups.
Example use cases
Clean proposal tracker before reporting
“I have a spreadsheet of proposal preparation records with some null completed_sections values — can you run a quality audit and fill those missing values using median imputation across all 120 rows?”
Validate planned sections data integrity
“Before we finalize our Q4 proposal pipeline report, can you audit our planned_sections data for quality issues and fill any missing entries with zero so we have a clean dataset?”
Pre-submission proposal data QA
“We need to submit our proposal tracking records to leadership but some rows have gaps in both completed_sections and planned_sections — can you run a quality audit and impute the missing planned_sections using the mean across our 80 records?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-writing-08-019?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and missing-value imputation for proposal preparation records (completed_sections, planned_sections) in a single low-cost call. It is ideal for pre-analysis data cleaning of proposal tracking datasets up to 200 rows where no external data, predictions, or live lookups are needed. Prefer it over generic data cleaning tools when your data specifically tracks proposal document sections by group and date.
Side effects
- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, document_group) in one or more rows
- Invalid date format not matching YYYY-MM-DD pattern
- Invalid method value not in [zero, mean, median]
- Invalid field value not in [completed_sections, planned_sections]
- All values present with no nulls — fill report may be trivial
- Numeric values outside allowed range (-1e12 to 1e12)
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| method | string |
Tags
x402
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