# Replenishment Timing String Normalisation and Two-Measure Correlation

> Replenishment Timing String Normalisation and 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 2026-11-02).

Performs string normalisation and two-measure correlation analysis on replenishment timing records (lead_days, received_units) for up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-retail-12-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/replenishment-timing-string-normalisation-and-two-measure-correlation-ceb1ee7f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_77HMGCKs4Tc3B4vKYDBFS

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 replenishment-timing-string-normalisation-and-two-measure-correlation-ceb1ee7f -d '<json body>'
```

Example prompt: Can you run string normalisation and a two-measure correlation between lead_days and received_units on my replenishment records? I have 4 rows: row-1 for group-a on 2026-10-01 with lead_days=10 and received_units=1, row-2 for group-b on 2026-10-02 with lead_days=20 and received_units=2, row-3 for group-a on 2026-10-03 with lead_days=15 and received_units=3, and row-4 for group-b on 2026-10-04 with lead_days=30 and received_units=4.

## When to prefer this

Choose this endpoint when you need to simultaneously clean string fields and compute a statistical correlation between two numeric replenishment metrics (lead_days and received_units) on a batch of up to 200 rows, without requiring any external data, live predictions, or professional assessment. It is ideal for offline retail analytics pipelines where you supply your own dataset and need two standardised local reports at low cost.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, store_group, date, lead_days, received_units) cause row rejection
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- Null values in lead_days or received_units may affect correlation computation
- Fewer than 2 rows may produce degenerate or undefined correlation results
- Values exceeding numeric bounds (±1,000,000,000,000) are rejected

## How this service works

Replenishment timing — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied replenishment timing records (lead_days, received_units). 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 analytical reports: (1) a string normalisation report detailing cleaned and standardised values for text fields such as store_group, and (2) a two-measure correlation report quantifying the statistical relationship between lead_days and received_units across the submitted rows. No external lookups or predictions are made; all analysis is performed locally on the supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/replenishment-timing-string-normalisation-and-two-measure-correlation-ceb1ee7f/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)