# Time Series Completeness — Exact Row Deduplication + Duplicate Key Report

> Time Series Completeness — Exact Row Deduplication + Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Runs two local analytical reports on supplied time series completeness records: exact row deduplication and duplicate key detection, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-038?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-exact-row-deduplication-duplicate-key-report-69eb1982
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QaMwErGXHF_zEchr82Z4t

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 time-series-completeness-exact-row-deduplication-duplicate-key-report-69eb1982 -d '<json body>'
```

Example prompt: I have a batch of time series completeness records with fields row_id, dataset_group, date, observed_points, and expected_points — can you run both an exact row deduplication and a duplicate key report on them? Here are up to 200 rows to check.

## When to prefer this

Choose this endpoint when you need both exact duplicate row detection and duplicate key identification in a single call on time series completeness records (observed vs expected data points per date and group). It is especially useful for data pipeline validation, ETL deduplication, and completeness audit workflows where you have up to 200 rows and want two complementary deduplication reports without external data access or prediction.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, dataset_group, observed_points, expected_points) cause schema validation failure
- Malformed date strings not matching YYYY-MM-DD pattern are rejected
- Empty rows array returns an error
- Values outside the allowed numeric range for observed_points or expected_points are rejected

## How this service works

Time series completeness — Exact row deduplication + Duplicate key report: Exact row deduplication + Duplicate key report for supplied time series completeness records (observed_points, expected_points). 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) an exact row deduplication report identifying fully identical rows across the submitted records, and (2) a duplicate key report identifying rows sharing the same key fields (e.g. date and dataset_group). Both reports are generated locally 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",
     "dataset_group",
     "date",
     "observed_points",
     "expected_points"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observed_points": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_points": 1,
     "observed_points": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_points": 2,
     "observed_points": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_points": 3,
     "observed_points": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_points": 4,
     "observed_points": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-exact-row-deduplication-duplicate-key-report-69eb1982/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)