# PQS Grade – Prompt Quality Pre-Flight Scorer

> 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.

## Facts

- Endpoint: GET https://pqs.onchainintel.net/api/pqs-grade?utm_source=zero.xyz
- Price: $0.001/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/pqs-grade-prompt-quality-pre-flight-scorer-e4fdaeca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qjzkrDcLELs-H-EWf2De0

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability pqs-grade-prompt-quality-pre-flight-scorer-e4fdaeca
```

Example prompt: Before I send this to Claude, can you run a quick quality check on my prompt — 'You are a senior tax advisor. Given the following income details, produce a structured summary of deductions I can claim in the US in 2024...' — and give me its composite score, letter grade, and what the weakest part is? Use the 'business' vertical.

## When to prefer this

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.

## Known failure modes

- 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

## 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.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "prompt": {
   "type": "string",
   "description": "Prompt text to grade (1-10000 chars)"
  },
  "vertical": {
   "type": "string",
   "description": "Optional domain: software/content/business/education/science/crypto/general/research"
  }
 }
}
```

## Response schema (JSON Schema)

```json
{
 "type": "object",
 "required": [
  "score",
  "grade",
  "verdict",
  "frameworks"
 ],
 "properties": {
  "grade": {
   "enum": [
    "A",
    "B",
    "C",
    "D",
    "F"
   ],
   "type": "string"
  },
  "score": {
   "type": "integer",
   "maximum": 100,
   "minimum": 0,
   "description": "Composite 0-100 score (percentile-normalized total)"
  },
  "verdict": {
   "type": "string",
   "description": "Single sentence diagnosing the weakest dimension, with a framework citation"
  },
  "frameworks": {
   "type": "object",
   "required": [
    "peem",
    "ragas",
    "geval"
   ],
   "properties": {
    "peem": {
     "type": "number",
     "maximum": 10,
     "minimum": 0,
     "description": "PEEM framework score: weights structure (clarity, output format, role, constraints)"
    },
    "geval": {
     "type": "number",
     "maximum": 10,
     "minimum": 0,
     "description": "G-Eval framework score: weights LLM-judged faithfulness (clarity, specificity, CoT, constraints)"
    },
    "ragas": {
     "type": "number",
     "maximum": 10,
     "minimum": 0,
     "description": "RAGAS framework score: weights grounding (context, specificity, examples)"
    }
   }
  },
  "upgrade_url": {
   "type": "string",
   "description": "Link to PQS Pro for the full 8-dimension SaaS"
  },
  "methodology_url": {
   "type": "string",
   "description": "Link to the methodology blog post explaining the five-framework synthesis"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/pqs-grade-prompt-quality-pre-flight-scorer-e4fdaeca/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from pqs.onchainintel.net](https://www.zero.xyz/host/pqs.onchainintel.net/llms.txt)