# Duplicate Observations — Record Quality Audit + Equal-Width Histogram

> Duplicate Observations — Record Quality Audit + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).

Runs two local analytical reports on duplicate-observation data: a record quality audit and an equal-width histogram over up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-013?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-record-quality-audit-equal-width-histogram-9467341c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_3QUrGJkgog47VOxMvVXC7

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 duplicate-observations-record-quality-audit-equal-width-histogram-9467341c -d '<json body>'
```

Example prompt: Can you run a record quality audit and equal-width histogram on my duplicate observation data? I have 4 rows — row-1 on 2026-10-01 in group-a with 10 duplicate_rows out of 1 total, row-2 on 2026-10-02 in group-b with 20 out of 2, row-3 on 2026-10-03 in group-a with 15 out of 3, and row-4 on 2026-10-04 in group-b with 30 out of 4 — use 5 bins and analyze the duplicate_rows field.

## When to prefer this

Choose this endpoint when you need two simultaneous analytical reports (quality audit + histogram) on duplicate-observation tabular data without any external API calls, predictions, or live lookups. It is ideal for data engineering pipelines, ETL quality gates, or one-off data integrity checks where you supply the raw duplicate_rows and total_rows metrics and want a quick, cheap ($0.01 USDC) local analysis covering up to 200 rows across multiple dataset groups and dates.

## Known failure modes

- More than 200 rows submitted — request rejected
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- bins value outside 1–30 range — rejected
- Empty rows array — minimum 1 item required
- Non-numeric values in duplicate_rows or total_rows where numbers are expected — type error

## How this service works

Duplicate observations — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram for supplied duplicate observations records (duplicate_rows, total_rows). 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

Two independent analytical reports: (1) a record quality audit summarizing completeness, validity, and anomalies across the supplied duplicate-observation rows, and (2) an equal-width histogram bucketing the chosen field (duplicate_rows or total_rows) into the specified number of bins with counts per bin. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "duplicate_rows",
     "total_rows"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "total_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "duplicate_rows": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "total_rows": 1,
     "dataset_group": "group-a",
     "duplicate_rows": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "total_rows": 2,
     "dataset_group": "group-b",
     "duplicate_rows": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "total_rows": 3,
     "dataset_group": "group-a",
     "duplicate_rows": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "total_rows": 4,
     "dataset_group": "group-b",
     "duplicate_rows": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "duplicate_rows",
    "total_rows"
   ],
   "type": "string",
   "default": "duplicate_rows"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/duplicate-observations-record-quality-audit-equal-width-histogram-9467341c/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)