# Knowledge Base Maintenance — Numeric Distribution + Two-Measure Correlation

> Knowledge Base Maintenance — Numeric Distribution + 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 2026-10-24).

Analyzes knowledge base maintenance records by generating a numeric distribution report and a two-measure correlation report for updated_articles and due_articles fields across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-writing-16-081?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/knowledge-base-maintenance-numeric-distribution-two-measure-correlation-52c3629b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZV7wc5d0KXjgY7M5AONg_

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 knowledge-base-maintenance-numeric-distribution-two-measure-correlation-52c3629b -d '<json body>'
```

Example prompt: Can you run a numeric distribution and two-measure correlation analysis on my knowledge base maintenance records? Here's the data with row IDs, document groups, dates, updated_articles, and due_articles counts — I want both reports covering all 200 rows, analyzing the updated_articles field.

## When to prefer this

Choose this endpoint when you have tabular knowledge base maintenance records with updated_articles and due_articles numeric fields and need both a distribution summary and a correlation between those two measures in a single call. It is ideal for editorial teams, content ops managers, or KB administrators who want quick statistical insight without setting up their own analytics pipeline. Prefer this over generic stats services when your data fits the KB maintenance schema (document_group, date, row_id) and you need exactly these two report types bundled at low cost.

## Known failure modes

- Empty or missing rows array returns a validation error
- Rows exceeding 200 items are rejected with a limit error
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Null values in both measure fields across all rows may produce degenerate or undefined correlation
- Missing required fields (row_id, document_group, date) cause per-row validation errors
- Invalid field enum value (not updated_articles or due_articles) returns an error

## How this service works

Knowledge base maintenance — Numeric distribution + Two-measure correlation: Numeric distribution + Two-measure correlation for supplied knowledge base maintenance records (updated_articles, due_articles). 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 statistical reports: (1) a numeric distribution report showing spread, central tendency, and shape of the selected field (updated_articles or due_articles) across the supplied rows, and (2) a two-measure correlation report quantifying the relationship between updated_articles and due_articles across the dataset. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/knowledge-base-maintenance-numeric-distribution-two-measure-correlation-52c3629b/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)