# Procurement Research — String Normalisation + Trailing Mean Series

> Procurement Research — String Normalisation + Trailing Mean Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Applies string normalisation and trailing mean series analysis to up to 200 procurement research records for quoted_amount or quoted_units fields, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-11-028?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/procurement-research-string-normalisation-trailing-mean-series-56db8799
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_XBgkguV94fJAYCSYy3PTm

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 procurement-research-string-normalisation-trailing-mean-series-56db8799 -d '<json body>'
```

Example prompt: Run string normalisation and a trailing mean series with a window of 3 on my procurement records — I have rows for group-a and group-b with dates from 2026-10-01 to 2026-10-04 and quoted_amount values of 10, 20, 15, and 30 — and analyse the quoted_amount field.

## When to prefer this

Choose this endpoint when you need both string normalisation and trailing mean series analytics on procurement data (quoted_amount or quoted_units) in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows where no live market lookup, prediction, or external enrichment is required — just local, deterministic computation on your supplied records.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, company_group, date, quoted_amount, quoted_units) — validation error
- Window size outside 2–200 range — schema validation failure
- Invalid date format (must match YYYY-MM-DD) — pattern validation error
- All values null for selected field — unable to compute meaningful series
- Payment not completed — 402 response, no analysis returned

## How this service works

Procurement research — String normalisation + Trailing mean series: String normalisation + Trailing mean series for supplied procurement research records (quoted_amount, quoted_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

Two analytical reports: (1) a string normalisation report on the chosen field across the supplied procurement rows, and (2) a trailing mean series computed over the specified rolling window for the same field — both derived locally from the input data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/procurement-research-string-normalisation-trailing-mean-series-56db8799/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)