---
title: "Guardrails Overview"
description: "Screen agent inputs and review outputs with guardrails."
icon: "shield-halved"
sidebarTitle: "Overview"
---

Guardrails are checkpoint functions that keep agent behavior safe and predictable. Use them to validate incoming messages before execution and validate responses before delivery.

## Choose the Right Guardrail

| Type | Runs When | On Failure | Page |
|------|-----------|------------|------|
| **Input Guardrails** | Before the agent processes input | Return guidance (non-strict) or raise `InputGuardrailTripwireTriggered` (strict) | [Input Guardrails](/additional-features/guardrails/input-guardrails) |
| **Output Guardrails** | After the agent drafts output, before delivery | Retry up to `validation_attempts`, then raise `OutputGuardrailTripwireTriggered` | [Output Guardrails](/additional-features/guardrails/output-guardrails) |

## Runnable GitHub Examples

- Input guardrails example: [`examples/guardrails_input.py`](https://github.com/VRSEN/agency-swarm/blob/main/examples/guardrails_input.py)
- Output guardrails example: [`examples/guardrails_output.py`](https://github.com/VRSEN/agency-swarm/blob/main/examples/guardrails_output.py)

## Best Practices

- Keep each guardrail focused on one responsibility.
- Write clear `output_info` messages so the model knows how to recover.
- Use non-strict mode for guidance and strict mode for hard requirements.
- For tool argument validation (field/model validators), use [Input Validation](/core-framework/tools/custom-tools/validation).