Guardrail Prompt Wrappers

Expert

Wrap model calls with input/output validation layers to enforce safety policies.

01 The Concept

Guardrail wrappers add validation layers before and after the main model call. Input guardrails check for toxic content, PII, or injection attempts. Output guardrails verify the response meets safety, format, and content policies before returning it to the user.

02 Weak vs. Strong

EX 01Guardrail Wrapper Pipeline

# Input Guardrail if contains_pii(user_input): user_input = redact_pii(user_input) if is_toxic(user_input): return SAFE_REFUSAL_MESSAGE # Main Model Call response = call_llm(user_input) # Output Guardrail if contains_pii(response) or violates_policy(response): return SAFE_FALLBACK_MESSAGE return response

→ Why it works

Guardrails prevent both malicious inputs and problematic outputs from reaching production users.

03 Key Points

01Input sanitization: Scanning user messages for toxic content or PII before model processing.

02Output validation: Checking model responses against content policies before delivery.

03PII redaction: Automatically masking personal data (emails, phone numbers, SSNs).

04Topic blocking: Preventing the model from engaging with prohibited subjects.

05Fallback responses: Returning safe default messages when guardrails trigger.

04 Model-Specific Notes

Claude handles Guardrail Prompt Wrappers tasks with excellent instruction compliance and structured output formatting.

05 For Your Role

Think of Guardrail Prompt Wrappers as organizing your work systematically so every step is clear and repeatable.

Next: Evaluation-Driven Prompt Design →