Output Validator
Validate LLM outputs against custom rules
Validation Rules
All Validations Passed
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What is Output Validation?
Output validation checks LLM responses against predefined rules before displaying to users. This safety layer catches formatting issues, policy violations, and unexpected content that might slip through prompt-based controls.
This tool lets you test validation rules interactively. Define rules once, then apply them consistently across your AI application.
Available Rules
Length Limits
Enforce minimum and maximum character counts. Prevents empty responses or excessively long outputs.
No URLs
Block external links in responses. Prevents phishing or redirect attacks via LLM outputs.
FAQ
When should I validate outputs?
Always validate before displaying to users, especially for customer-facing chatbots, content generation, or structured data extraction.
What if validation fails?
Options include: retry with modified prompt, return fallback response, escalate to human review, or gracefully inform user.