{"uid":"cap_EckYro-iN1_jHCzCE_jCo","slug":"task-type-top-k-label-coverage-21c542eb","name":"Task Type Top-k Label Coverage","description":"Task type - Top-k label coverage: Top-k label coverage 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 top-k label coverage 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top-k label coverage metrics for a naive-Bayes text classifier trained to distinguish task types (research, writing, analysis, implementation) using up to 200 labelled records.","exampleAgentPrompt":"Compute top-2 label coverage for my task type classifier — I have 20 labelled records where each record has an id, the text, the actual label (one of research, writing, analysis, implementation), the predicted label, and a 4-element probability array; tell me how often the true label falls within the top 2 predicted classes.","exampleUseCases":[{"title":"Evaluating task classifier coverage","prompt":"I've trained a naive-Bayes model to classify documents as research, writing, analysis, or implementation. Can you compute the top-2 label coverage on my 50 test records? Each record has the document text, the actual task type label, the predicted label, and the four class probabilities."},{"title":"Comparing k=1 vs k=2 prediction quality","prompt":"For my task type classifier, can you calculate top-k coverage at k=1 and k=2 so I can see whether allowing one extra guess meaningfully improves coverage? I'll pass in 30 labelled records with actual labels, predicted labels, and probability scores for all four classes."},{"title":"Quality check before deploying task router","prompt":"Before I ship my task routing system, I want to confirm the model's top-3 label coverage on my 100 held-out records — each has the text snippet, ground-truth task type (research, writing, analysis, or implementation), the top predicted label, and the probability distribution across all four classes."}],"resultDescription":"Returns a bounded top-k label coverage score indicating the fraction of supplied labelled records where the true label appears within the top-k ranked predicted classes, computed over up to 200 text records with 4-class (research, writing, analysis, implementation) naive-Bayes probability outputs.","failureModes":["More than 200 records supplied — request rejected or truncated","Probability arrays not summing to 1 or containing values outside [0,1]","Probability array length not exactly 4 — schema validation error","k value outside allowed range of 1–4 — validation error","Label values outside allowed enum (research, writing, analysis, implementation) — rejected","Empty records array — no coverage computable"],"whenToPreferThis":"Choose this endpoint when you need a lightweight, cheap ($0.01 USDC) top-k label coverage evaluation for a 4-class task-type text classifier (research/writing/analysis/implementation) on small datasets up to 200 records, without requiring a hosted model or full ML infrastructure. Best suited for local evaluation workflows, quick model sanity checks, or naive-Bayes baseline benchmarking.","instructions":null,"reviewSummary":null,"reviewSummaryHighlights":null,"reviewSummaryConcerns":null,"reviewSummaryGeneratedAt":null,"activationCount":0,"lastUsedAt":null,"lastSuccessfullyRanAt":null,"lastHealthCheckAt":"2026-10-12T00:51:01.484Z","isFirstParty":false,"canonicalSlug":"task-type-top-k-label-coverage-21c542eb"}