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Task Type Supplied-Group Evaluation
x402
Task Type Supplied-Group Evaluation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Evaluates a supplied set of labelled text records for task-type classification (research/writing/analysis/implementation) broken down by group, with per-group metrics and naive-Bayes baselines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Task type - Supplied-group evaluation: Supplied-group evaluation for Task type. 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 supplied-group evaluation deliverable.
Output
A bounded evaluation deliverable containing per-group classification metrics (accuracy, precision, recall, F1) for task-type labels (research, writing, analysis, implementation), a naive-Bayes baseline comparison, and local dataset summary statistics — all derived from the supplied labelled text records.
Example use cases
QA team model performance review
“We have 150 labelled documents from two teams — team A and team B — each tagged with an actual task type and what our classifier predicted (research, writing, analysis, or implementation). Can you evaluate our classifier's performance broken down by team group and include a naive-Bayes baseline?”
Cross-source label consistency check
“I have records from three data sources (groups 'source-1', 'source-2', 'source-3') with actual and predicted task-type labels. Please run a group-level evaluation on these 180 records so I can see where each source's predictions diverge most from the actual labels.”
Classifier iteration benchmarking
“After retraining our task classifier, I want to compare how well it labels documents as research, writing, analysis, or implementation — split by project group. Here are 120 records with actual and predicted labels; please give me per-group accuracy metrics and a naive-Bayes baseline to compare against.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-sector-ml-task-type-group-evaluation?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have your own labelled dataset of up to 200 text records with actual and predicted task-type labels and need group-stratified evaluation metrics plus a naive-Bayes baseline — without needing a hosted model or foundation-model training. It is ideal for lightweight offline-style benchmarking where you supply all the data and just need structured performance analysis broken down by a categorical group variable.
Side effects
- More than 200 records supplied — exceeds the bounded limit and may be rejected
- Missing required fields (id, text, actual, predicted, group) on any record causes validation error
- Invalid enum values for actual or predicted labels outside the four permitted classes
- Empty records array returns no evaluation output
- Text exceeding 1000 characters per record may be truncated or rejected
- Payment failure via x402 protocol prevents response delivery
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| records | array |
Tags
x402
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