LightJason Benchmark offers a comprehensive set of predefined and customizable scenarios to stress-test and evaluate multi-agent applications built on the LightJason framework. Users can configure agent counts, communication patterns, and environmental parameters to simulate real-world workloads and assess system behavior. Benchmarks gather metrics such as message throughput, agent response times, CPU and memory consumption, logging results to CSV and graphical formats. Its integration with JUnit allows seamless inclusion in automated testing pipelines, enabling regression and performance testing as part of CI/CD workflows. With adjustable settings and extensible scenario templates, the suite helps pinpoint performance bottlenecks, validate scalability claims, and guide architectural optimizations for high-performance, resilient multi-agent systems.

Agent Transparency Tool offers a comprehensive framework for instrumenting AI agents with transparency features. It provides logging interfaces to record state transitions and decisions, modules to compute key transparency metrics (e.g., confidence scores, decision lineage), and visualization dashboards to explore agent behavior over time. By integrating seamlessly with popular agent frameworks, it generates structured transparency logs, supports export to JSON or CSV formats, and includes utilities to plot transparency curves for audit and performance analysis. This toolkit empowers teams to identify biases, debug workflows, and demonstrate responsible AI practices.