# Agricultural Output — Record Quality Audit + Two-Measure Correlation

> Agricultural Output — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Audits data quality and computes Pearson correlation between output_tonnes and cultivated_hectares for up to 200 agricultural output rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-16-015?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/agricultural-output-record-quality-audit-two-measure-correlation-0f769d1d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_CpPE5bhZCDNvFo6gvIfwy

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 agricultural-output-record-quality-audit-two-measure-correlation-0f769d1d -d '<json body>'
```

Example prompt: Can you run a record quality audit and a correlation analysis between output_tonnes and cultivated_hectares on my agricultural dataset? I have about 50 rows covering regions like 'North Plains' and 'River Delta' from 2025-01-01 through 2025-06-30 — I want to know if the data is clean and whether there's a meaningful relationship between land area and crop output.

## When to prefer this

Choose this endpoint when you need both a data quality audit and a two-measure statistical correlation on agricultural output records (output_tonnes vs cultivated_hectares) in a single cheap call ($0.01 USDC for up to 200 rows). It is ideal for pre-publication data validation, exploratory data quality checks, and quick statistical sanity checks on farm or crop datasets without needing an external analytics platform. Prefer this over generic statistics APIs when your data is specifically structured around regional agricultural output with row-level identifiers and date-stamped entries.

## Known failure modes

- Empty rows array or fewer than 1 row returns a validation error
- More than 200 rows exceeds the maximum and will be rejected
- Rows missing required fields (row_id, region, date, output_tonnes, cultivated_hectares) cause schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern trigger format errors
- Completely null numeric columns may produce undefined or degenerate correlation results
- Payment not supplied or insufficient USDC causes 402 Payment Required response

## How this service works

Agricultural output — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied agricultural output records (output_tonnes, cultivated_hectares). 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 analytical reports: (1) a record quality audit flagging issues such as missing values, nulls, out-of-range numbers, and format errors across all submitted rows; and (2) a two-measure correlation report computing the statistical relationship (e.g. Pearson r) between output_tonnes and cultivated_hectares across the dataset. Both reports are derived entirely 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",
     "region",
     "date",
     "output_tonnes",
     "cultivated_hectares"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "region": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "output_tonnes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "cultivated_hectares": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "region": "group-a",
     "row_id": "row-1",
     "output_tonnes": 10,
     "cultivated_hectares": 1
    },
    {
     "date": "2026-10-02",
     "region": "group-b",
     "row_id": "row-2",
     "output_tonnes": 20,
     "cultivated_hectares": 2
    },
    {
     "date": "2026-10-03",
     "region": "group-a",
     "row_id": "row-3",
     "output_tonnes": 15,
     "cultivated_hectares": 3
    },
    {
     "date": "2026-10-04",
     "region": "group-b",
     "row_id": "row-4",
     "output_tonnes": 30,
     "cultivated_hectares": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/agricultural-output-record-quality-audit-two-measure-correlation-0f769d1d/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)