# Render Jobs Category Frequencies and Date-by-Category Pivot

> Render Jobs Category Frequencies and Date-by-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).

Analyzes render job records to produce two reports: category frequencies by asset group and a date-by-category pivot for render_seconds or sample_count metrics.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-02-110?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/render-jobs-category-frequencies-and-date-by-category-pivot-039a3bc6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_c0_E0ou5mJsAHvGB_j2D-

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 render-jobs-category-frequencies-and-date-by-category-pivot-039a3bc6 -d '<json body>'
```

Example prompt: Can you analyze these render job records — rows with asset_group, date, render_seconds, and sample_count — and give me both a category frequency table by asset group and a date-by-category pivot on render_seconds? I have about 50 rows to send.

## When to prefer this

Choose this endpoint when you have up to 200 render job records with asset_group and date fields and need both a frequency distribution across categories and a pivot table of a numeric metric (render_seconds or sample_count) by date and category — all in a single $0.01 call. Prefer this over general analytics tools when your data is already structured in the required schema and you want two complementary offline reports without external lookups or predictions.

## Known failure modes

- Fewer than 1 row submitted — validation error
- More than 200 rows submitted — exceeds limit
- Missing required fields (row_id, asset_group, date, render_seconds, sample_count) — schema validation failure
- Date field does not match YYYY-MM-DD pattern — format validation error
- Invalid field enum value (not render_seconds or sample_count) — rejected
- Payment of 0.01 USDC not fulfilled — 402 response

## How this service works

Render jobs — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot for supplied render jobs records (render_seconds, sample_count). 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 analytical reports: (1) a category frequencies table showing how often each asset_group appears in the submitted rows, and (2) a date-by-category pivot table aggregating the chosen metric (render_seconds or sample_count) across dates and asset groups. Both reports are computed locally from the supplied data, up to 200 rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-jobs-category-frequencies-and-date-by-category-pivot-039a3bc6/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)