# Training Question Label and Prediction Audit

> Training Question Label and Prediction Audit 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).

Audits labels and model predictions for up to 200 text records classified into training question categories (concept, procedure, example, assessment), returning performance metrics and error analysis.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-ml-training-question-label-audit?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/training-question-label-and-prediction-audit-b6eca1e9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kp8-dzBPa0-hBPjJGXi2c

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-question-label-and-prediction-audit-b6eca1e9 -d '<json body>'
```

Example prompt: Can you audit these 50 training question records for me — each has an actual label (concept, procedure, example, or assessment), a predicted label, and probabilities — and tell me where the classifier is making mistakes and how accurate it is overall?

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost audit of classifier predictions on educational/training question text without needing a hosted model or large-scale infrastructure. Best suited for small batches (up to 200 records), naive Bayes or similar small classifiers, and when you want a quick evaluation report for concept/procedure/example/assessment classification. Use when you have pre-computed predictions and probabilities and need an independent audit rather than retraining.

## Known failure modes

- Records array exceeds 200 items — request rejected or truncated
- Missing required fields (id, text, actual, predicted, probabilities) in any record — validation error
- Probabilities array does not contain exactly 4 values or values fall outside [0,1] — schema error
- Invalid enum value for actual or predicted (must be concept, procedure, example, or assessment) — validation error
- Empty records array — returns empty or minimal audit report
- id field exceeds 80 characters — schema rejection

## How this service works

Training question - Label and prediction audit: Label and prediction audit for Training question. Up to 200 supplied labelled text records. Local dataset tools, evaluation and small naive-Bayes baselines; no hosted model or foundation-model training. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded label and prediction audit deliverable.

## Output

Returns a bounded label and prediction audit deliverable covering accuracy metrics, per-class performance breakdown, and misclassification analysis for up to 200 supplied records across the four training question categories (concept, procedure, example, assessment). Includes comparison of actual vs predicted labels and probability-based diagnostics.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "records": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "id",
     "text",
     "actual",
     "predicted",
     "probabilities"
    ],
    "properties": {
     "id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "text": {
      "type": "string",
      "default": "",
      "maxLength": 1000
     },
     "actual": {
      "enum": [
       "concept",
       "procedure",
       "example",
       "assessment"
      ],
      "type": "string"
     },
     "predicted": {
      "enum": [
       "concept",
       "procedure",
       "example",
       "assessment"
      ],
      "type": "string"
     },
     "probabilities": {
      "type": "array",
      "items": {
       "type": "number",
       "default": 0,
       "maximum": 1,
       "minimum": 0
      },
      "default": [],
      "maxItems": 4,
      "minItems": 4
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "id": "example-0-0",
     "text": "concept sample document number 0 for this supplied dataset.",
     "actual": "concept",
     "predicted": "concept",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-1",
     "text": "concept sample document number 1 for this supplied dataset.",
     "actual": "concept",
     "predicted": "concept",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-0-2",
     "text": "concept sample document number 2 for this supplied dataset.",
     "actual": "concept",
     "predicted": "concept",
     "probabilities": [
      0.8,
      0.06666666666666667,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-0",
     "text": "procedure sample document number 0 for this supplied dataset.",
     "actual": "procedure",
     "predicted": "procedure",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
    {
     "id": "example-1-1",
     "text": "procedure sample document number 1 for this supplied dataset.",
     "actual": "procedure",
     "predicted": "procedure",
     "probabilities": [
      0.06666666666666667,
      0.8,
      0.06666666666666667,
      0.06666666666666667
     ]
    },
 
… (truncated)
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/training-question-label-and-prediction-audit-b6eca1e9/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)