# Training Assessments — Keyed Dataset Comparison + Explicit Missing-Value Fill

> Training Assessments — Keyed Dataset Comparison + Explicit Missing-Value Fill 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).

Compares two keyed datasets of training assessment scores (pre_score/post_score) and fills missing values, producing 2 analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-11-190?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/training-assessments-keyed-dataset-comparison-explicit-missing-value-735f2f92
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_P4ekRlqNx9XQWWy-tuND3

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 training-assessments-keyed-dataset-comparison-explicit-missing-value-735f2f92 -d '<json body>'
```

Example prompt: Compare these two sets of training assessment records by row_id — primary dataset has rows row-1 through row-50 with pre_score and post_score values, and the comparison dataset has slightly different scores for some of the same rows — fill any missing pre_score values and give me both reports.

## When to prefer this

Choose this endpoint when you need to compare two keyed training assessment datasets by row_id and simultaneously handle missing pre_score or post_score values — all in a single $0.01 call that returns two reports. Ideal for education analytics workflows that need lightweight, offline data reconciliation without external API dependencies or live predictions.

## Known failure modes

- Missing required fields (row_id, course_group, date, pre_score, or post_score) causes validation error
- More than 200 rows submitted exceeds limit and is rejected
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Field enum value other than 'pre_score' or 'post_score' is rejected
- Empty rows array returns error
- Both datasets must be supplied; missing 'other' dataset causes comparison failure

## How this service works

Training assessments — Keyed dataset comparison + Explicit missing-value fill: Keyed dataset comparison + Explicit missing-value fill for supplied training assessments records (pre_score, post_score). 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: (1) a keyed dataset comparison showing matched, unmatched, and differing rows between the primary and comparison datasets for the selected score field; (2) an explicit missing-value fill report showing which null pre_score or post_score values were detected and filled. Results are based entirely on the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/training-assessments-keyed-dataset-comparison-explicit-missing-value-735f2f92/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)