# Data Freshness — String Normalisation + Base-100 Series

> Data Freshness — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Runs two analytical reports on data freshness records: string normalisation and a base-100 indexed series for age_minutes or record_count fields, across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-06-030?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-freshness-string-normalisation-base-100-series-1fe6e183
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_6xNG1FZGwtVFiebDWPdGF

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 data-freshness-string-normalisation-base-100-series-1fe6e183 -d '<json body>'
```

Example prompt: Can you run a string normalisation and base-100 index series on these data freshness records — use age_minutes as the field, set the base index to row 0, and include all 4 rows across group-a and group-b?

## When to prefer this

Choose this endpoint when you need two bundled offline analytical reports — string normalisation plus a base-100 index series — on data freshness records (age_minutes, record_count) for up to 200 rows, without requiring any live data lookup, external enrichment, or prediction. It is cost-effective at $0.01 USDC for both reports in a single call. Prefer alternatives if you need histograms, grouped summaries, duplicate detection, or distribution analysis (see sibling endpoints on the same platform).

## Known failure modes

- Rows array empty or missing — returns validation error
- More than 200 rows submitted — rejected with max-items error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- base_index out of range for supplied row count — error or undefined behaviour
- Null values in age_minutes or record_count when that field is selected — may produce nulls in series output
- Payment not included or insufficient — x402 payment required error

## How this service works

Data freshness — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied data freshness records (age_minutes, record_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

Two analytical reports returned together: (1) string-normalised versions of the categorical/label fields in the supplied rows, and (2) a base-100 indexed numeric series for the selected field (age_minutes or record_count), anchored to the specified base_index row. Results cover up to 200 input rows and are computed locally with no external data lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "age_minutes",
     "record_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "age_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "record_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "age_minutes": 10,
     "record_count": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "age_minutes": 20,
     "record_count": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "age_minutes": 15,
     "record_count": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "age_minutes": 30,
     "record_count": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "age_minutes",
    "record_count"
   ],
   "type": "string",
   "default": "age_minutes"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-freshness-string-normalisation-base-100-series-1fe6e183/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)