# Render Jobs Category Frequencies and Keyed Dataset Comparison

> Render Jobs Category Frequencies and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).

Analyzes render job records to produce category frequency distributions and a keyed comparison between two supplied datasets (up to 200 rows each).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-02-111?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/render-jobs-category-frequencies-and-keyed-dataset-comparison-24fabbfc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Bpqrt0Oe1H9zok6gGoLxA

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-keyed-dataset-comparison-24fabbfc -d '<json body>'
```

Example prompt: I have two sets of render job logs — one from last week and one from this week — each with row IDs, asset groups, dates, render seconds, and sample counts. Can you run a category frequency breakdown and a keyed comparison between them to show me what changed?

## When to prefer this

Choose this endpoint when you have render job records with asset group and timing metrics and need both a categorical frequency breakdown and a keyed row-by-row comparison between two datasets in a single low-cost call. It is ideal for pipeline QA, comparing render job exports across time periods, or auditing discrepancies between two data pulls — all without requiring an external database or live lookup.

## Known failure modes

- Missing required fields (row_id, asset_group, date, render_seconds, sample_count) cause validation errors
- Supplying more than 200 rows in either dataset exceeds the row limit
- Date strings not matching YYYY-MM-DD pattern are rejected
- Empty rows array causes a minItems validation failure
- Mismatched or missing row_id keys between datasets may produce incomplete comparison results

## How this service works

Render jobs — Category frequencies + Keyed dataset comparison: Category frequencies + Keyed dataset comparison 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 report showing how often each asset_group (and potentially other categorical fields) appears across the supplied rows, and (2) a keyed dataset comparison report that aligns records from both the primary and secondary datasets by row_id and highlights differences in render_seconds and sample_count values. No external data is fetched; analysis is performed locally on the supplied data.

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

… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-jobs-category-frequencies-and-keyed-dataset-comparison-24fabbfc/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)