aiml-llamaguard-eval

What problem does it solve?

The AIML Guard evaluation template provides a reproducible framework to assess how frontier language models respond to safety tasks by distinguishing safe vs. unsafe outputs and validating guardrails in a controlled workflow.

Core Features & Use Cases

• Structured test harness and validation rules (including placeholder checks, minimum response length, and deterministic classification) to ensure consistent safety assessments.
• Reusable templates for prompt construction, response evaluation, and result aggregation across experiments.
• Use Case: researchers can rapidly compare multiple models or settings (e.g., different guardrails) on a common evaluation suite.

Quick Start

Run the test harness in this skill directory to validate the Llama-Guard templates against safe and unsafe responses.