# Fact Check Workflow — String Normalisation + Base-100 Series

> Fact Check Workflow — String Normalisation + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-30).

Performs string normalisation and base-100 index series computation on fact-check workflow records (claims reviewed, references collected) for up to 200 rows, producing 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-18-030?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-30
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/fact-check-workflow-string-normalisation-base-100-series-ca0b6da5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EGPY2_lzycH9SGsMb7QVI

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 fact-check-workflow-string-normalisation-base-100-series-ca0b6da5 -d '<json body>'
```

Example prompt: Can you run string normalisation and a base-100 series on my fact-check workflow data — I have 4 rows with channel groups 'group-a' and 'group-b', claims_reviewed values of 10, 20, 15, and 30 for dates 2026-10-01 through 2026-10-04, using claims_reviewed as the field and row index 0 as the base?

## When to prefer this

Choose this endpoint when you need offline, local analytical processing of fact-check workflow records specifically requiring both string normalisation and base-100 index series computation in a single call. It is well-suited for newsroom or editorial analytics pipelines where no live data lookup or external action is needed and cost must be kept low ($0.01 for 2 reports). Prefer it over general-purpose analytics APIs when your data is already collected and you need deterministic, reproducible index series anchored to a specific baseline row.

## Known failure modes

- Input array below minItems:1 — request rejected
- date field does not match YYYY-MM-DD pattern — validation error
- row_id missing or empty string — schema validation failure
- base_index out of range (0–199) or exceeds actual row count — index error
- Numeric field values outside ±1,000,000,000,000 range — rejection
- More than 200 rows submitted — maxItems exceeded error

## How this service works

Fact check workflow — String normalisation + Base-100 series: String normalisation + Base-100 series for supplied fact check workflow records (claims_reviewed, references_collected). 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 2 analytical reports: one covering string normalisation of text fields (e.g. channel_group) and one providing a base-100 index series for the selected numeric field (claims_reviewed or references_collected) anchored to the specified base row. All analysis is performed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "channel_group",
     "date",
     "claims_reviewed",
     "references_collected"
    ],
    "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
     },
     "claims_reviewed": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "references_collected": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "channel_group": "group-a",
     "claims_reviewed": 10,
     "references_collected": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "channel_group": "group-b",
     "claims_reviewed": 20,
     "references_collected": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "channel_group": "group-a",
     "claims_reviewed": 15,
     "references_collected": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "channel_group": "group-b",
     "claims_reviewed": 30,
     "references_collected": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "claims_reviewed",
    "references_collected"
   ],
   "type": "string",
   "default": "claims_reviewed"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/fact-check-workflow-string-normalisation-base-100-series-ca0b6da5/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)