# Duplicate Observations Analytics — Record Quality Audit, String Normalisation & Daily Sum Series

> Duplicate Observations Analytics — Record Quality Audit, String Normalisation & Daily Sum Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Runs three local analytical reports (record quality audit, string normalisation, and daily sum series) on up to 200 rows of duplicate-observation data containing duplicate_rows and total_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-04-198?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/duplicate-observations-analytics-record-quality-audit-string-935cb35c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2fSqiiK0aA_3mcPOP1jwp

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-analytics-record-quality-audit-string-935cb35c -d '<json body>'
```

Example prompt: Can you run the three-report duplicate-observations analysis on my dataset — here are 5 rows with row_id, dataset_group, date, duplicate_rows, and total_rows — and use 'duplicate_rows' as the target field? I need the record quality audit, string normalisation, and daily sum series all in one go.

## When to prefer this

Choose this endpoint when you need three bundled analytical reports (quality audit, string normalisation, daily sum series) on a compact dataset of duplicate-observation records (up to 200 rows) in a single low-cost call, without requiring live lookups or external data enrichment. It is ideal for offline data quality checks on pipeline outputs or warehouse exports where the data is already in hand.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Invalid date format (not YYYY-MM-DD) — row fails schema validation
- Null or out-of-range numeric values for duplicate_rows or total_rows — may cause partial computation
- Unrecognised field selector value (not 'duplicate_rows' or 'total_rows') — rejected by enum validation
- Missing required fields (row_id, dataset_group, date) — row rejected

## How this service works

Duplicate observations — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series for supplied duplicate observations records (duplicate_rows, total_rows). 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 distinct analytical reports returned together: (1) a record quality audit summarising anomalies or issues in the submitted rows, (2) a string normalisation report highlighting inconsistencies in text fields like dataset_group, and (3) a daily sum series aggregating the selected numeric field (duplicate_rows or total_rows) by date — all computed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "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-analytics-record-quality-audit-string-935cb35c/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)