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PQS Grade – Prompt Quality Pre-Flight Scorer
x402
PQS Grade – Prompt Quality Pre-Flight Scorer is a paid API for AI agents from pqs.onchainintel.net, paid per call via x402, $0.001/call, status unknown (last checked 2026-10-29).
Scores a prompt 0-100 and assigns an A-F grade plus PEEM, RAGAS, and G-Eval sub-scores and a single-sentence verdict, acting as a cheap quality gate before paid LLM inference.
Price / call$0.001
Success—
StatusUnknown
How this service works
Quick pre-flight quality score: composite (0-100) + grade (A-F) + three framework sub-scores (PEEM, RAGAS, G-Eval) + verdict. Run upstream of any other paid call to filter weak prompts before inference. The cheapest gate on the AI input quality problem.
Output
Returns a JSON object with an integer composite score (0-100), a letter grade (A-F), a one-sentence verdict naming the weakest dimension with a framework citation, and three framework sub-scores (PEEM 0-10 for structure, RAGAS 0-10 for grounding/context, G-Eval 0-10 for LLM-judged faithfulness). Optionally includes links to PQS Pro and a methodology blog post.
Example use cases
Pre-flight gate for costly LLM calls
“Before we call GPT-4o with this prompt — 'Summarize the legal risks in the attached contract and flag any clauses that deviate from standard SaaS terms' — score it for quality and tell me the grade and verdict so I can decide if it's worth the spend.”
Prompt debugging in content pipeline
“I'm building a content generation pipeline and this prompt keeps producing vague output: 'Write a blog post about AI trends.' Can you grade it across PEEM, RAGAS, and G-Eval and tell me the single sentence diagnosis of what's weakest? Use the 'content' vertical.”
Automated prompt quality filter in agent workflow
“Before my research agent sends each user query to the expensive model, I need you to score the prompt 'What are the most cited papers on transformer attention mechanisms published after 2022?' in the 'research' vertical and only proceed if the grade is B or above.”
Technical details
Endpoint
GEThttps://pqs.onchainintel.net/api/pqs-grade?utm_source=zero.xyzWhen to prefer
Choose this endpoint as a cheap upstream gate ($0.001) before any expensive LLM inference call. Ideal when running high-volume pipelines where a meaningful fraction of prompts may be low quality and you want to avoid wasting budget. Prefer this over manual prompt review when operating at scale, or over the full 8-dimension PQS analysis when you only need a fast pass/fail signal rather than detailed remediation advice.
Side effects
- Prompt text empty or exceeds 10,000 characters — likely returns 400 or validation error
- Invalid vertical value outside allowed enum — may default to 'general' or return error
- Payment not provided or insufficient — returns 402 Payment Required
- Ambiguous or borderline prompts may yield mid-range scores that don't clearly signal pass/fail
- Score can vary slightly for identical prompts if G-Eval uses stochastic LLM judging internally
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| prompt | string | Prompt text to grade (1-10000 chars) |
| vertical | string | Optional domain: software/content/business/education/science/crypto/general/research |
Output
Schema · Response
| Field | Type | Description |
|---|---|---|
| graderequired | string | |
| scorerequired | integer | Composite 0-100 score (percentile-normalized total) |
| verdictrequired | string | Single sentence diagnosing the weakest dimension, with a framework citation |
| frameworksrequired | object | |
| upgrade_url | string | Link to PQS Pro for the full 8-dimension SaaS |
| methodology_url | string | Link to the methodology blog post explaining the five-framework synthesis |
Tags
x402
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