# Material Libraries Data Quality Audit: Record Quality Audit + String Normalisation + Explicit Missing-Value Fill

> Material Libraries Data Quality Audit: Record Quality Audit + String Normalisation + Explicit 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 2026-10-22).

Runs three analytical reports on material library records — a record quality audit, string normalisation, and explicit missing-value fill — for up to 200 rows of material_count and texture_mb data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-03-208?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/material-libraries-data-quality-audit-record-quality-audit-string-5e195448
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_vhE0SqzzlR6GwkKxa2QKj

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 material-libraries-data-quality-audit-record-quality-audit-string-5e195448 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and missing-value fill (using median) on my material library records — here are up to 200 rows with row_id, asset_group, date, material_count, and texture_mb fields — and give me all three reports?

## When to prefer this

Choose this endpoint when you need a combined data quality audit, string normalisation, and missing-value fill on material library records (material_count, texture_mb) in a single low-cost call. It is ideal for creative/3D production pipelines where asset data needs cleaning before downstream processing, and where no live external lookup or predictive model is needed — just fast, local analytical reports on up to 200 rows.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Invalid date format (must be YYYY-MM-DD) — validation error
- Unrecognised fill method enum value — schema validation error
- Numeric field values outside acceptable range — schema rejection
- Empty rows array — minimum 1 row required
- Missing required fields (row_id, asset_group, date) — schema validation error

## How this service works

Material libraries — Record quality audit + String normalisation + Explicit missing-value fill: Record quality audit + String normalisation + Explicit missing-value fill for supplied material libraries records (material_count, texture_mb). 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: (1) a record quality audit flagging data issues in the supplied rows, (2) a string normalisation report for text fields such as asset_group, and (3) an explicit missing-value fill report for the specified numeric field (material_count or texture_mb) using the chosen fill method (zero, mean, or median). All reports are computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/material-libraries-data-quality-audit-record-quality-audit-string-5e195448/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)