guardrails

Configure and enforce content safety guardrails for TrueFoundry AI Gateway.

2|1|Updated Feb 26, 2026
One-click install
npx skills add https://github.com/passionseed/ps_app --skill guardrails-passionseed
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: guardrails
Source: https://github.com/passionseed/ps_app/tree/main/.agents/skills/truefoundry-guardrails
Command: npx skills add https://github.com/passionseed/ps_app --skill guardrails-passionseed

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

Guardrails provide configurable safety controls for TrueFoundry AI Gateway, including PII filtering, content moderation, prompt-injection detection, and custom rules, to reduce risk in model and tool interactions.

Core Features & Use Cases

  • PII filtering and content moderation across LLM inputs/outputs and MCP tool calls
  • Prompt-injection detection and secret detection with optional custom rules
  • Two-step deployment workflow: configure guardrail providers and gateway guardrails config
  • Guidance to deploy guardrails servers using the official template to ensure gateway compatibility

Quick Start

Install and configure a guardrail by creating a Guardrail Config Group with provider integrations, then attach it to a Gateway Guardrails Config and apply to a gateway.

Frequently Asked Questions about guardrails

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I add content safety guardrails to an AI Gateway?

To add content safety guardrails to an AI Gateway, you configure a Guardrail Config Group with provider integrations, then attach it to a Gateway Guardrails Config and apply it to the gateway deployment to filter PII and enforce policy compliance.

Can I filter PII and detect prompt injections across LLM inputs and tool calls?

Yes, you can filter PII and detect prompt injections across LLM inputs and outputs and MCP tool calls by configuring content moderation, secret detection, and custom rules within the gateway guardrails config.

What is the process to configure policy compliance for MCP tool calls?

Configuring policy compliance for MCP tool calls involves creating a Guardrail Config Group with the necessary provider integrations and attaching it to a Gateway Guardrails Config to enforce custom rules during tool interactions.

Do I need to deploy a guardrails server before attaching a config to a gateway?

Yes, you need to deploy guardrails servers using the official template before attaching the config to ensure gateway compatibility and that provider references resolve to valid config integrations.

What limitations exist when enforcing custom rules on LLM outputs?

Custom rule enforcement for LLM outputs depends on valid provider references resolving to existing config integrations, and you must deploy the guardrails server using the official template to maintain gateway compatibility and prevent unsafe outputs.