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August Services Text Classifier
x402
August Services Text Classifier is a paid API for AI agents from api-v3qhpbwutp.august.services, paid per call via x402, $0.03/call, status down (last checked 2026-09-15).
Classifies free text into user-supplied labels with a confidence score and short justification for routing, triage, moderation, and tagging pipelines.
Price / call$0.03
Success—
StatusDown
How this service works
Classify text into one of the labels you provide, with a confidence score and a short justification. Useful for routing, triage, moderation queues and tagging pipelines where an agent needs a cheap deterministic decision per item.
Output
Returns a JSON object with three fields: 'label' (the winning category from the labels you provided), 'confidence' (a float from 0 to 1 indicating certainty), and 'reason' (a short human-readable justification explaining why that label was chosen).
Example use cases
Support ticket routing pipeline
“Classify this incoming ticket as 'bug', 'feature-request', 'billing', or 'account-access' and give me a confidence score so I can route it to the right team: "My payment failed but I was still charged twice."”
Content moderation queue
“I need you to classify this user comment as 'safe', 'spam', or 'abusive' with a justification so my moderation queue knows whether to auto-approve or flag it for review: "Click here to win a free iPhone, limited time!!"”
Product review topic tagging
“Tag this product review with one of these labels — 'quality', 'shipping', 'customer-service', or 'pricing' — and tell me your confidence and reasoning: "It arrived two weeks late and the box was completely crushed."”
Technical details
Endpoint
POSThttps://api-v3qhpbwutp.august.services/v1/classifyWhen to prefer
Choose this endpoint when you need a cheap, fast, deterministic per-item classification decision with an explainable confidence score and justification — ideal for routing, triage, moderation queues, and tagging pipelines where you supply your own label taxonomy. Prefer it over a full LLM prompt when you want structured, consistent JSON output with a confidence signal rather than a free-form answer.
Side effects
- No labels provided — endpoint requires at least two candidate labels to classify between
- Text input is empty or missing — returns a validation error
- Label set contains only one option — classification is ambiguous or refused
- Very short or ambiguous text may return low confidence scores near 0.5
- Network or upstream LLM timeout causing a 5xx error
- Input text exceeds token limit for the underlying model
Tags
x402
Reviews
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Zero review prompt (fires after every successful call)
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