# Training Assessments Duplicate Key Report and Keyed Dataset Comparison

> Training Assessments Duplicate Key Report and Keyed Dataset Comparison is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).

Generates two analytical reports on training assessment records: a duplicate key report and a keyed dataset comparison between two supplied datasets of up to 200 rows each.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-education-11-069?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/training-assessments-duplicate-key-report-and-keyed-dataset-comparison-51e44098
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_7KoH6s7g8w2c2qjkXdEf9

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-duplicate-key-report-and-keyed-dataset-comparison-51e44098 -d '<json body>'
```

Example prompt: Can you check my training assessment records for duplicate row IDs and compare them against an updated version of the dataset? I have two sets of up to 200 rows each, both with fields like row_id, course_group, date, pre_score, and post_score.

## When to prefer this

Choose this endpoint when you need to simultaneously detect duplicate keys and compare two versions of a training assessment dataset in a single API call for a fixed low cost. It is ideal for education platforms, LMS administrators, or data pipelines that regularly ingest pre_score and post_score records and need data quality checks before committing data. Prefer this over general-purpose data tools when working specifically with training assessment schemas (course_group, pre_score, post_score) and when you want both duplicate detection and dataset reconciliation in one shot without spinning up external analytics infrastructure.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, course_group, date, pre_score, post_score) on any row causes validation error
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Empty rows array (minItems: 1 not satisfied) returns an error
- Numeric scores outside allowed range cause rejection
- Malformed JSON body returns HTTP 400

## How this service works

Training assessments — Duplicate key report + Keyed dataset comparison: Duplicate key report + Keyed dataset comparison 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

Returns two independent analytical reports: (1) a duplicate key report identifying any row_ids that appear more than once within the supplied dataset, and (2) a keyed dataset comparison highlighting rows that differ between the primary dataset and the secondary dataset, matched by row_id. No external lookups or predictions are made; all analysis is performed locally on the supplied data.

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

## More

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