# Correction Logs String Normalisation + Numeric Interval Filter

> Correction Logs String Normalisation + Numeric Interval Filter 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).

Normalises string fields and filters correction log rows by a numeric interval (min/max) for correction_count or published_items, delivering two analytical reports from supplied data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-04-026?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/correction-logs-string-normalisation-numeric-interval-filter-3d9b219a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zeHgqsf3PrRu9DCbhLfWF

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 correction-logs-string-normalisation-numeric-interval-filter-3d9b219a -d '<json body>'
```

Example prompt: I have up to 200 rows of correction log records with fields like channel_group, date, correction_count, and published_items — can you normalise the string fields and filter the rows to only keep those where correction_count is between 5 and 100, and give me the two analytical reports?

## When to prefer this

Choose this endpoint when you have tabular correction log records (up to 200 rows) that need string field normalisation combined with numeric range filtering on either correction_count or published_items, and you want two bundled analytical reports in a single low-cost call. Prefer it over general-purpose data tools when your data fits the news/editorial correction domain schema exactly and you want a lightweight, local analytical pass without external API round-trips or predictions.

## Known failure modes

- Rows array empty or missing — request rejected
- More than 200 rows submitted — exceeds maximum item limit
- Invalid date format (non YYYY-MM-DD) — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — schema rejection
- Field enum value not 'correction_count' or 'published_items' — validation error
- Minimum greater than maximum — may return zero filtered rows
- Missing required row fields (row_id, channel_group, date) — schema error

## How this service works

Correction logs — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter for supplied correction logs records (correction_count, published_items). 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 based on the supplied correction log rows: one reflecting string-normalised channel_group values and one showing only rows whose selected numeric field (correction_count or published_items) falls within the specified minimum–maximum interval. Up to 200 rows processed per call with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "channel_group",
     "date",
     "correction_count",
     "published_items"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "channel_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "published_items": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "correction_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "channel_group": "group-a",
     "published_items": 1,
     "correction_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "channel_group": "group-b",
     "published_items": 2,
     "correction_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "channel_group": "group-a",
     "published_items": 3,
     "correction_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "channel_group": "group-b",
     "published_items": 4,
     "correction_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "correction_count",
    "published_items"
   ],
   "type": "string",
   "default": "correction_count"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/correction-logs-string-normalisation-numeric-interval-filter-3d9b219a/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)