preclinical

Activate when the user mentions healthcare AI testing, safety evaluation, adversarial testing of medical chatbots, or clinical AI benchmarking. Guides them to the right preclinical command.

Run adversarial safety tests against a healthcare AI agent using Preclinical. Walks through test configuration, launches, and monitors the run.

Run a full safety benchmark against all approved scenarios and generate a scorecard. Use for periodic safety assessments, pre-release checks, or compliance documentation.

Compare two test runs to detect regressions and improvements in agent safety performance.

Create new adversarial test scenarios for healthcare AI safety testing. Use when the user wants to add test cases or build custom test suites.

Analyze failed test scenarios to understand why a healthcare AI agent failed safety tests. Reads transcripts, grader evidence, and identifies patterns.

Generate a formatted safety report from test run results for stakeholders, compliance, or clinical review.

Iterative improvement cycle — diagnose failures, create targeted scenarios, retest to verify fixes.

Install and configure the Preclinical CLI for healthcare AI safety testing. Use when the user mentions preclinical, wants to test a healthcare AI agent, or when any other preclinical skill needs the CLI installed.

TriageBench-aligned triage extraction — taxonomy mapping, under/over-triage severity, hedged recommendations, and gray-zone handling

Plan adversarial red-team attacks against healthcare AI using persona-driven strategies, rubric-mapped attack vectors, and phased escalation

Analyze rubric coverage across conversation transcript, extract evidence, and identify testing gaps for comprehensive criterion evaluation

TriageBench-aligned standardized patient — review-of-systems encoding, information pacing, consistency enforcement, and edge case handling

Generate realistic adversarial patient messages with progressive escalation, pivot decisions, and per-turn criterion evaluation

Comprehensive grading guide for healthcare AI evaluation — scoring, rubric interpretation, evidence citation, and consistency checks