# Learning Resource Usage — String Normalisation + Secondary-Measure Weighted Mean

> Learning Resource Usage — String Normalisation + Secondary-Measure Weighted Mean 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 computes a secondary-measure weighted mean across up to 200 learning resource usage records (access_count, resource_minutes), returning two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-12-034?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/learning-resource-usage-string-normalisation-secondary-measure-0c8e3107
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2LpUsluAxaixAJekXRzgB

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 learning-resource-usage-string-normalisation-secondary-measure-0c8e3107 -d '<json body>'
```

Example prompt: Can you run string normalisation and compute the access_count weighted mean on my learning resource usage data? I have 4 rows — group-a on 2026-10-01 with access_count 10 and resource_minutes 1, group-b on 2026-10-02 with access_count 20 and resource_minutes 2, group-a on 2026-10-03 with access_count 15 and resource_minutes 3, and group-b on 2026-10-04 with access_count 30 and resource_minutes 4.

## When to prefer this

Choose this endpoint when you need both string normalisation of course group labels AND a weighted mean computation on learning resource usage data (access_count or resource_minutes) in a single low-cost call. It is ideal for education analytics pipelines handling up to 200 rows of usage records where two bundled local analytical reports are sufficient and no live data lookup, prediction, or external service is required.

## Known failure modes

- More than 200 rows submitted — request rejected, max 200 rows enforced
- Missing required fields (row_id, course_group, date, access_count, resource_minutes) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Empty rows array (minItems: 1 not satisfied) — schema rejection
- Invalid field enum value (must be access_count or resource_minutes) — rejected

## How this service works

Learning resource usage — String normalisation + Secondary-measure weighted mean: String normalisation + Secondary-measure weighted mean for supplied learning resource usage records (access_count, resource_minutes). 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 analytical reports per call: (1) string-normalised course_group labels applied across all rows, and (2) a secondary-measure weighted mean computed over the specified field (access_count or resource_minutes) for the supplied dataset of up to 200 rows. No external lookups or predictions are included.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/learning-resource-usage-string-normalisation-secondary-measure-0c8e3107/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)