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FrostSkyNet JSONL Quality Judge
x402
FrostSkyNet JSONL Quality Judge is a paid API for AI agents from route-a-worker.frostskynet-api.workers.dev, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Scores JSONL rows using fixed rules, adding a _quality field; optionally detects/redacts PII and bad words, and filters rows below a score threshold.
Price / call$0.01
Success—
StatusUnknown
How this service works
Scores JSONL rows using fixed rules and adds _quality. Detects some PII and bad-word patterns; optional redaction and score filtering. Detection is incomplete and can produce false positives. No AI.
Output
Returns scored JSONL rows with an added `_quality` integer field (0–100). Optionally includes PII flags, redacted text (PII replaced), or masked bad words (replaced with ****). If filtering is enabled, rows scoring below `minScore` are dropped entirely.
Example use cases
Training data quality filtering
“I have a JSONL dataset I want to use for fine-tuning. Can you score every row for quality and drop anything that scores below 65? Here's the data: {jsonl_text}.”
PII redaction before sharing data
“Before I share this JSONL dataset with a third party, can you scan it for PII and redact any personal information you find? I want to keep all rows but just mask the sensitive parts.”
Profanity cleanup for content pipeline
“I'm processing user-submitted text stored as JSONL and I need to mask any bad language with asterisks before it goes downstream — can you run the bad-word filter on this data and return the cleaned rows?”
Technical details
Endpoint
POSThttps://route-a-worker.frostskynet-api.workers.dev/judge?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, deterministic, rule-based quality scoring and content moderation for JSONL datasets without relying on AI inference. Ideal for automated data pipelines where reproducibility and low latency matter more than nuanced understanding. Prefer this over AI-based moderation when cost predictability and speed are critical, or when you need a simple threshold-based filter for training data curation.
Side effects
- Empty input string — returns validation error
- Request body exceeds size limit — returns payload too large error
- Malformed JSON or non-JSONL input format — returns parse error
- Invalid options values (e.g. minScore out of 0–100 range) — returns schema validation error
- False positives on PII or bad-word detection due to rule-based (non-AI) approach
- False negatives where real PII or profanity is not caught by fixed rules
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| input | string | Nonempty input text. Limit applies to the entire UTF-8 JSON request body including options and escaping, not just this string. |
| options | object | Optional settings. |
Tags
x402
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