# Registry Snapshots: String Normalisation + Category Frequencies

> Registry Snapshots: String Normalisation + Category Frequencies 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).

Performs string normalisation and category frequency analysis on up to 200 registry snapshot rows containing registered and changed entity counts, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-04-024?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/registry-snapshots-string-normalisation-category-frequencies-4be236c7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_J8FC6ntrjlaMhh7JecC5u

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-category-frequencies-4be236c7 -d '<json body>'
```

Example prompt: I have registry snapshot records for a few company groups — can you normalize the company group strings and give me category frequency counts for both the registered_entities and changed_entities fields? I have 4 rows: group-a on 2026-10-01 with 10 registered and 1 changed, group-b on 2026-10-02 with 20 registered and 2 changed, group-a on 2026-10-03 with 15 registered and 3 changed, and group-b on 2026-10-04 with 30 registered and 4 changed.

## When to prefer this

Choose this endpoint when you have tabular registry snapshot data with company groups and entity counts and need both string normalisation of categorical labels and frequency analysis of numeric entity fields in a single low-cost call. It is well-suited for offline batch processing of up to 200 rows without requiring live data lookups or external enrichment. At $0.01 USDC for two reports, it is cost-effective for routine data cleaning and descriptive analytics pipelines on registry data.

## Known failure modes

- Exceeding 200 rows causes rejection — keep batch size within limit
- Missing required fields (row_id, date, company_group, registered_entities, changed_entities) will cause validation errors
- Dates not matching YYYY-MM-DD pattern will fail schema validation
- Numeric values outside ±1,000,000,000,000 range will be rejected
- Empty rows array is not permitted (minItems: 1)

## How this service works

Registry snapshots — String normalisation + Category frequencies: String normalisation + Category frequencies 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

Two independent analytical reports: (1) normalised string output for the company_group field across all supplied rows, and (2) category frequency tables for the registered_entities and changed_entities numeric columns — all computed locally without live lookup or external data enrichment, covering up to 200 rows per call.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/registry-snapshots-string-normalisation-category-frequencies-4be236c7/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)