# Tutoring Sessions — Adjacent Row Changes + IQR Outlier Flags

> Tutoring Sessions — Adjacent Row Changes + IQR Outlier Flags 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).

Computes adjacent row-to-row changes and IQR-based outlier flags for tutoring session data (session_minutes or session_count) across up to 200 records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-16-157?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/tutoring-sessions-adjacent-row-changes-iqr-outlier-flags-ab40d9e9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_naobgNv5EGKWNQ71DW_TU

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 tutoring-sessions-adjacent-row-changes-iqr-outlier-flags-ab40d9e9 -d '<json body>'
```

Example prompt: Can you analyze these tutoring session records and flag any outliers in session_minutes using IQR, plus show me the adjacent row-to-row changes? I have about 50 rows with row_id, course_group, date, session_minutes, and session_count fields.

## When to prefer this

Choose this endpoint when you need lightweight, local statistical analysis of tutoring session records — specifically adjacent row delta detection and IQR outlier flagging — without any external data lookup, live prediction, or model inference. Ideal for education data auditing, anomaly detection in session logs, or data quality checks on up to 200 rows of session_minutes or session_count data at minimal cost ($0.01 USDC for both reports).

## Known failure modes

- More than 200 rows submitted — request exceeds maxItems limit and will be rejected
- Missing required fields (row_id, date, course_group, session_minutes, session_count) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Null numeric values may affect delta calculations and outlier boundaries
- Invalid field enum value (not 'session_minutes' or 'session_count') causes schema rejection
- Empty rows array (minItems:1 not met) returns an error

## How this service works

Tutoring sessions — Adjacent row changes + IQR outlier flags: Adjacent row changes + IQR outlier flags for supplied tutoring sessions records (session_minutes, session_count). 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 per call: (1) adjacent row change values showing delta between consecutive records for the selected field, and (2) IQR-based outlier flags marking records that fall outside the interquartile range — both applied to the supplied tutoring session rows (session_minutes or session_count) across up to 200 input records.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/tutoring-sessions-adjacent-row-changes-iqr-outlier-flags-ab40d9e9/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)