# Event Coverage String Normalisation + Two-Measure Correlation

> Event Coverage String Normalisation + Two-Measure Correlation 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 strings and computes correlation between covered_sessions and planned_sessions for up to 200 event coverage rows, producing two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-news-11-033?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/event-coverage-string-normalisation-two-measure-correlation-0fb89efd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_mJ1nIhry8anWyz9-lR7vm

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 event-coverage-string-normalisation-two-measure-correlation-0fb89efd -d '<json body>'
```

Example prompt: Can you normalise the channel group strings and run a two-measure correlation between covered_sessions and planned_sessions for my event coverage data? I have 4 rows: row-1 on 2026-10-01 for group-a with 10 covered and 1 planned, row-2 on 2026-10-02 for group-b with 20 covered and 2 planned, row-3 on 2026-10-03 for group-a with 15 covered and 3 planned, and row-4 on 2026-10-04 for group-b with 30 covered and 4 planned.

## When to prefer this

Choose this endpoint when you have tabular event coverage data with string fields needing normalisation and you want to measure statistical correlation between two numeric session measures (covered vs planned) in a single low-cost call. It is ideal for offline/batch analytical workflows where no live data lookup, prediction, or external enrichment is needed. Prefer this over generic analytics tools when the data fits within 200 rows and the $0.01 USDC flat-rate cost per two-report bundle is acceptable.

## Known failure modes

- Fewer than 1 row submitted — API rejects with validation error
- More than 200 rows submitted — exceeds maxItems limit, rejected
- Missing required fields (row_id, date, covered_sessions, planned_sessions) — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected
- covered_sessions or planned_sessions values outside ±1,000,000,000,000 range — rejected
- All covered_sessions or planned_sessions values are null — correlation cannot be computed, report may be empty or error

## How this service works

Event coverage — String normalisation + Two-measure correlation: String normalisation + Two-measure correlation for supplied event coverage records (covered_sessions, planned_sessions). 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 analytical reports: (1) string normalisation results for text fields such as channel_group, highlighting and standardising inconsistent casing or formatting; (2) a two-measure correlation analysis between covered_sessions and planned_sessions across all submitted rows, including the correlation coefficient and supporting statistics. No external lookups or predictions are made; all analysis is performed on the supplied data only.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/event-coverage-string-normalisation-two-measure-correlation-0fb89efd/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)