PQS Preflight – Prompt Quality & Endpoint Trust Check is a paid API for AI agents from pqs.onchainintel.net, paid per call via x402, $0.05/call, status unknown (last checked 2026-09-14).
Scores a prompt against an 8-dimension quality rubric (pass/fail at 28/80) and optionally retrieves on-chain trust signals for a target endpoint URL before committing to a paid LLM call.
Pass/Fail before you waste budget on a doomed call. Decide whether to make a paid LLM call before you make it. Preflight scores your prompt against an 8-dimension quality rubric (pass/fail at 28/80) and optionally pulls the target endpoint's on-chain trust signals — total payments, unique payers, last activity. Two-in-one circuit breaker for agents that don't want to waste budget on weak prompts or sketchy endpoints. (rev 2)
Returns a pass/fail verdict based on a quality score out of 80 (threshold at 28), plus dimensional breakdown scores across 8 rubric dimensions. If an endpoint URL was provided, also returns on-chain trust signals: total payments received, number of unique payers, and timestamp of last activity.
GEThttps://pqs.onchainintel.net/api/preflightUse this endpoint as a gate before any paid LLM or API call in an agentic workflow when you want to avoid wasting budget on poorly-formed prompts or unverified endpoints. It is uniquely valuable when you need both prompt quality validation AND on-chain reputation checks in a single cheap ($0.05) call, rather than calling two separate services. Prefer this over pure prompt-scoring endpoints when the target endpoint's trustworthiness is also uncertain.
{
"prompt": "Explain the key differences between machine learning and deep learning for a business audience",
"vertical": "education",
"endpoint_url": "https://api.example.com/ml-explainer"
}| Field | Type | Description |
|---|---|---|
| prompt | string | Prompt to preflight |
| vertical | string | Domain: software/content/business/education/science/crypto/general/research |
| endpoint_url | string | Optional endpoint URL for trust scoring |
{
"prompt": {
"grade": "F",
"score": 33,
"out_of": 80,
"feedback": [
"Specify output format and length (e.g., 500-word executive summary, bullet-point comparison table, or slide deck outline)",
"Add constraints for the business audience such as avoiding technical jargon, including ROI/cost implications, or focusing on specific industries",
"Provide context about the audience's current knowledge level and intended use case (e.g., board presentation, internal training, decision-making about AI adoption)"
],
"top_issue": "Specify output format and length (e.g., 500-word executive summary, bullet-point comparison table, or slide deck outline)",
"dimensions": {
"clarity": 8,
"context": 5,
"examples": 2,
"constraints": 4,
"specificity": 6,
"cot_structure": 2,
"output_format": 3,
"role_definition": 3
},
"threshold_met": true
},
"endpoint": {
"url": "https://api.example.com/ml-explainer",
"wallet": null,
"trust_label": "Unresolved",
"trust_score": null,
"activity_status": "UNKNOWN",
"resolution_source": "not_found",
"verified_on_chain": false
},
"clearance": "APPROVED",
"confidence": 0.41,
"pqs_version": "2.0",
"upgrade_url": "https://promptqualityscore.com"
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