# Rig Complexity Data Audit, Normalisation & Date-Category Pivot

> Rig Complexity Data Audit, Normalisation & Date-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Runs three local analytical reports on rig complexity records (bone_count, constraint_count): record quality audit, string normalisation, and a date-by-category pivot — up to 200 rows per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-04-206?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/rig-complexity-data-audit-normalisation-date-category-pivot-30095747
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_WOYiRdbp7xLzKcFImfuom

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 rig-complexity-data-audit-normalisation-date-category-pivot-30095747 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and date-by-category pivot on my rig complexity data? I have 4 rows: row-1 group-a 2026-10-01 bone_count=10 constraint_count=1, row-2 group-b 2026-10-02 bone_count=20 constraint_count=2, row-3 group-a 2026-10-03 bone_count=15 constraint_count=3, row-4 group-b 2026-10-04 bone_count=30 constraint_count=4 — use bone_count as the primary field.

## When to prefer this

Choose this endpoint when you need three combined analytical passes — quality audit, string normalisation, and date-category pivot — on rig complexity records (bone_count, constraint_count) in a single low-cost call. It is purpose-built for 3D animation/rigging data with asset_group and date dimensions, and bundles three reports for $0.01 USDC. Prefer alternatives if you need live data lookup, predictive analytics, more than 200 rows, or reports on non-rig data domains.

## Known failure modes

- More than 200 rows submitted — request rejected, batch must be split
- Missing required fields (row_id, asset_group, date, bone_count, constraint_count) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- field enum value not one of bone_count or constraint_count — rejected
- Numeric values outside allowed range (±1,000,000,000,000) — schema error
- Empty rows array — minItems:1 constraint violated

## How this service works

Rig complexity — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied rig complexity records (bone_count, constraint_count). 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 analytical reports: (1) a record quality audit flagging nulls, out-of-range values, and structural issues in the supplied rows; (2) a string normalisation report standardising asset_group and row_id text fields; (3) a date-by-category pivot table summarising the selected numeric field (bone_count or constraint_count) by asset_group across dates. All computed locally with no external calls.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/rig-complexity-data-audit-normalisation-date-category-pivot-30095747/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)