# Study Recruitment String Normalisation and Numeric Row Ordering

> Study Recruitment String Normalisation and Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-26).

Normalises string fields and orders rows numerically for study recruitment records (eligible_candidates, enrolled_candidates), producing 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-09-025?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/study-recruitment-string-normalisation-and-numeric-row-ordering-bfbb847d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ubj7C_PyN8GCgE-u0MdFx

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 study-recruitment-string-normalisation-and-numeric-row-ordering-bfbb847d -d '<json body>'
```

Example prompt: Can you normalise the course group strings and sort these study recruitment rows by eligible_candidates — I have 4 records: row-1 on 2026-10-01 group-a with 10 eligible and 1 enrolled, row-2 on 2026-10-02 group-b with 20 eligible and 2 enrolled, row-3 on 2026-10-03 group-a with 15 eligible and 3 enrolled, row-4 on 2026-10-04 group-b with 30 eligible and 4 enrolled?

## When to prefer this

Choose this endpoint when you have structured study recruitment tabular data (up to 200 rows) and need both string normalisation of categorical fields and numeric ordering of candidate counts in a single low-cost call. It is purpose-built for education and study recruitment contexts and delivers two reports per call. It does not perform live lookups, predictions, or external actions, so it is appropriate when all data is supplied inline.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, date, eligible_candidates, enrolled_candidates) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric field values outside allowed range (-1e12 to 1e12) — validation error
- Invalid field enum value (not 'eligible_candidates' or 'enrolled_candidates') — rejected input

## How this service works

Study recruitment — String normalisation + Numeric row ordering: String normalisation + Numeric row ordering for supplied study recruitment records (eligible_candidates, enrolled_candidates). 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 covering the supplied study recruitment rows: one with string-normalised course_group and related fields, and one with rows reordered numerically by the specified field (eligible_candidates or enrolled_candidates). Handles up to 200 rows per call with no external lookups or predictions.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/study-recruitment-string-normalisation-and-numeric-row-ordering-bfbb847d/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)