# Study Recruitment String Normalisation + Numeric Interval Filter

> Study Recruitment String Normalisation + Numeric Interval Filter 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).

Normalises string fields and filters study recruitment rows by a numeric interval (min/max) on eligible or enrolled candidates, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-09-026?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/study-recruitment-string-normalisation-numeric-interval-filter-ef73dc5b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rxoswQfgikAGDfrMAsXRn

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-numeric-interval-filter-ef73dc5b -d '<json body>'
```

Example prompt: Normalise the course group strings and filter my study recruitment records to only those where eligible_candidates is between 5 and 50 — here are my rows: [{"row_id":"r1","course_group":"Group A","date":"2026-10-01","eligible_candidates":10,"enrolled_candidates":3}]. Give me both analytical reports.

## When to prefer this

Choose this endpoint when you need to both clean/normalise string fields and apply a numeric range filter to study recruitment or course enrollment records in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where you want two co-generated reports without external lookups or live data sources. Not suitable for real-time data enrichment, predictive analytics, or datasets exceeding 200 rows.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, eligible_candidates, enrolled_candidates) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Minimum value greater than maximum value may return empty filter results
- Null numeric values for the selected field may be excluded from interval filter output

## How this service works

Study recruitment — String normalisation + Numeric interval filter: String normalisation + Numeric interval filter 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

Returns two independent analytical reports covering: (1) normalised string values for the course_group field across all submitted rows, and (2) rows filtered to those where the selected numeric field (eligible_candidates or enrolled_candidates) falls within the specified minimum–maximum interval. Up to 200 input rows processed per call.

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/study-recruitment-string-normalisation-numeric-interval-filter-ef73dc5b/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)