# Registry Snapshots — String Normalisation + Date by Category Pivot

> Registry Snapshots — String Normalisation + Date by Category Pivot 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 date-by-category pivot analysis on up to 200 rows of registry snapshot records (registered_entities and changed_entities fields), returning two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-04-035?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/registry-snapshots-string-normalisation-date-by-category-pivot-b36bd3a7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZxoUqGB3UrC3VzFX7I7Uz

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 registry-snapshots-string-normalisation-date-by-category-pivot-b36bd3a7 -d '<json body>'
```

Example prompt: Can you run string normalisation and a date-by-category pivot on these registry snapshot rows — I have data for company groups 'group-a' and 'group-b' with registered_entities counts across dates in October 2026, up to 50 rows, and I want the registered_entities field analysed?

## When to prefer this

Choose this endpoint when you have up to 200 rows of registry snapshot data with company group labels and entity counts, and you need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC for both reports). It is ideal for offline/batch analytical use cases where no live lookup, prediction, or external data enrichment is required — all processing is local and deterministic.

## Known failure modes

- Exceeds 200-row limit — request rejected, caller must batch input
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, company_group, date) — validation failure
- Null numeric values in both registered_entities and changed_entities — sparse or empty pivot output
- Invalid field enum value — schema rejection
- Empty rows array — minItems:1 constraint violated

## How this service works

Registry snapshots — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied registry snapshots records (registered_entities, changed_entities). 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) a string normalisation report cleaning and standardising company_group labels across the supplied rows, and (2) a date-by-category pivot report aggregating the selected numeric field (registered_entities or changed_entities) by date and company_group category. No external lookups are performed; all computation is local and analytical.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/registry-snapshots-string-normalisation-date-by-category-pivot-b36bd3a7/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)