> ## Documentation Index
> Fetch the complete documentation index at: https://docs.praison.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# LLM Guardrail CLI

> CLI commands for LLM-based guardrails in PraisonAI TypeScript

# LLM Guardrail CLI Commands

The `praisonai-ts` CLI provides the `guardrail` command for content validation.

## Basic Usage

```bash theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
# Check content against guardrails
praisonai-ts guardrail check "Your content here"

# Check with custom criteria
praisonai-ts guardrail check "Content to validate" --criteria "Must be professional"

# Get JSON output
praisonai-ts guardrail check "Hello world" --json
```

**Example Output:**

```json theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
{
  "success": true,
  "data": {
    "status": "passed",
    "score": 0.95,
    "message": "Content passes all criteria",
    "reasoning": "The content is appropriate and safe"
  }
}
```

## Status Values

| Status    | Description                      |
| --------- | -------------------------------- |
| `passed`  | Content meets all criteria       |
| `failed`  | Content does not meet criteria   |
| `warning` | Content partially meets criteria |

## SDK Usage

For programmatic guardrail usage:

```typescript theme={"theme":{"light":"vitesse-light","dark":"vitesse-dark"}}
import { LLMGuardrail } from 'praisonai';

const guard = new LLMGuardrail({
  name: 'safety',
  criteria: 'Content must be safe and appropriate',
  threshold: 0.8
});

const result = await guard.check('Hello world');
console.log(result.status); // 'passed', 'failed', or 'warning'
console.log(result.score);  // 0-1
console.log(result.reasoning);
```

For more details, see the [LLM Guardrail SDK documentation](/docs/js/llm-guardrail).