# Agent Guardrail

> Use this tool when you need to enforce security policies and control the actions of AI agents, preventing potential security breaches by evaluating actions against configurable policies before execution. It solves problems related to unauthorized or malicious actions by AI agents, providing an additional layer of security and control. Agent Guardrail is ideal for use cases where AI agents interact with sensitive systems or data, requiring strict action-level policy enforcement.

Canonical page: https://skillsregistry.net/skills/eren-solutions-agent-guardrail  
JSON: https://api.skillsregistry.net/v1/skills/eren-solutions-agent-guardrail

## Description

Action-level policy enforcement for AI agents — control what agents DO, not just what they say. Evaluate actions against configurable security policies before execution.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-05-11

## Source

- **Source listing:** [Smithery](https://smithery.ai/server/eren-solutions/agent-guardrail)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "eren-solutions-agent-guardrail"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/eren-solutions-agent-guardrail` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/eren-solutions-agent-guardrail/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt