# Proposal Preparation — Record Quality Audit + Missing-Value Fill

> 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.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-08-019?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/proposal-preparation-record-quality-audit-missing-value-fill-c4599948
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_x_bQXI0NSCRlNSEyFIqQY

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability proposal-preparation-record-quality-audit-missing-value-fill-c4599948 -d '<json body>'
```

Example prompt: Can you audit these proposal records for quality issues and fill any missing completed_sections values using median imputation? I have up to 50 rows with fields like row_id, document_group, date, completed_sections, and planned_sections.

## When to prefer this

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.

## Known failure modes

- 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)

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "document_group",
     "date",
     "completed_sections",
     "planned_sections"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "document_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "planned_sections": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "completed_sections": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "document_group": "group-a",
     "planned_sections": 1,
     "completed_sections": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "document_group": "group-b",
     "planned_sections": 2,
     "completed_sections": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "document_group": "group-a",
     "planned_sections": 3,
     "completed_sections": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "document_group": "group-b",
     "planned_sections": 4,
     "completed_sections": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "completed_sections",
    "planned_sections"
   ],
   "type": "string",
   "default": "completed_sections"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/proposal-preparation-record-quality-audit-missing-value-fill-c4599948/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)