# Verity Suite Quick Check Guardrail

> Verity Suite Quick Check Guardrail is a paid API for AI agents from suite.veritylayer.dev, paid per call via x402, $0.02/call, status unknown (last checked 2026-09-14).

Evaluates an AI agent's proposed action against an optional policy and context, returning an allow/review/block decision with a risk score and signed receipt.

## Facts

- Endpoint: POST https://suite.veritylayer.dev/check/quick
- Price: $0.02/call
- Payment: x402
- Status: unknown
- Last checked: 2026-09-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/verity-suite-quick-check-guardrail-88d93d66
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4t2WnlVAB1NqOe3T3LLfD

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 verity-suite-quick-check-guardrail-88d93d66 -d '<json body>'
```

Example prompt: Before I send that email to all customers, run a quick Verity guardrail check on the action 'send promotional email blast to all 10,000 users' against the policy 'never send unsolicited marketing to users who have not opted in' so I know whether to allow, review, or block it.

## When to prefer this

Choose this endpoint when an AI agent needs a fast, per-call safety gate before executing a potentially risky or policy-sensitive action, especially when you need a signed, auditable receipt proving the check was performed. Prefer it over home-built rule engines when you need calibrated risk scoring with human-readable reasons and a structured allow/review/block decision. It is particularly valuable for agentic pipelines that must enforce explicit policies at runtime without halting for human review on every step.

## Known failure modes

- Missing required 'action' field returns a validation error
- Action or policy strings exceeding 2000 characters are rejected
- Invalid 'method' value (not POST/PUT/PATCH) causes schema validation failure
- Network timeout if the evaluation engine is under load
- Signing not configured results in receipt being null rather than a signed object
- Ambiguous or very short action descriptions may yield low-confidence risk scores

## How this service works

The trust fabric for AI agents — calibrated, fail-closed services agents pay per call.

## Output

Returns a JSON object with: a 'decision' field (allow, review, or block), a 'risk' score from 0 (clearly safe) to 1 (clearly dangerous), an array of 'reasons' explaining the decision, an array of 'concerns' listing specific risks, an optional 'safer_alternative' string suggesting a safer path if blocked or flagged, and an optional Ed25519-signed 'receipt' object from VerityLayer that can be independently verified for auditability.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "action": {
   "type": "string",
   "title": "Action",
   "maxLength": 2000,
   "minLength": 1,
   "description": "the action the agent is about to take"
  },
  "policy": {
   "anyOf": [
    {
     "type": "string",
     "maxLength": 2000
    },
    {
     "type": "null"
    }
   ],
   "title": "Policy",
   "default": null,
   "description": "rules that must not be violated"
  },
  "context": {
   "anyOf": [
    {
     "type": "string",
     "maxLength": 2000
    },
    {
     "type": "null"
    }
   ],
   "title": "Context",
   "default": null,
   "description": "situation/background"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/verity-suite-quick-check-guardrail-88d93d66/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from suite.veritylayer.dev](https://www.zero.xyz/host/suite.veritylayer.dev/llms.txt)