SWARM Safety Eval

Multi-agent safety regressions are tracked by computing SWARM soft-metrics from ledger data and diffing results against prior evals. This flags degradation in toxicity, quality gap, or welfare, producing a machine-readable diff and a human-readable article.

SWARM soft-metrics evaluate fleet safety by quantifying toxicity, quality gap, and welfare within multi-agent dynamics. They grade safety performance by analyzing ledger data to produce a comprehensive evaluation report and notify operators of any degradation.

Compute toxicity and welfare metrics from multi-agent ledgers by running a scheduled safety evaluation. The process integrates with the SWARM bridge and reporting workflow to extract SoftMetrics, diff them against prior evals, and flag regressions.

Yes, SWARM Safety Eval requires the SWARM bridge and ledgers to function. It integrates directly with these components to extract ledger data, compute soft-metrics, and generate reporting workflows for tracking multi-agent safety dynamics.

Automate multi-agent safety reporting by applying the evaluation on a schedule to compare current metrics against prior evals. This scheduled process flags regressions in toxicity, quality gap, or welfare, and automatically publishes a human-readable article.

Notify operators about multi-agent welfare degradation by applying scheduled safety evaluations that diff current soft-metrics against prior evals. This workflow integrates with reporting systems to alert operators when regressions in toxicity, quality gap, or welfare occur.