Execute AI agent benchmarks in sandboxed environments and generate scored trajectories.
npx skills add https://github.com/benchflow-ai/benchflow --skill benchflow
Please help me install this Agent Skill. Skill: benchflow Source: https://github.com/benchflow-ai/benchflow/tree/main/.agents/skills/benchflow Command: npx skills add https://github.com/benchflow-ai/benchflow --skill benchflow
BenchFlow solves the fragmentation in AI agent evaluation by providing a unified, hardened contract to run agents against sandboxed environments and score their performance.
Run the benchflow skill to execute a benchmark suite on the specified task directory using the default sandbox environment.
High-intent search queries and answers about installing and using this skill.
To run AI agent benchmarks, you execute them against containerized sandboxes like Docker, Daytona, or Modal. This ensures isolated, reproducible task execution and generates scored trajectories alongside performance metrics.
Evaluating multi-agent performance against token spend requires multi-pattern benchmarking. You can execute single-agent, multi-agent, or multi-round patterns to measure agent capability and cost efficiency.
Sandboxing prevents reward hacking during AI evaluation by providing a robust verification layer. This hardened verifier ensures deterministic scoring by isolating task execution and preventing agents from manipulating the environment.
Yes, you can use custom task sources for AI agent benchmarking. The framework supports universal benchmarking, allowing you to run any AI agent against bespoke harnesses or standardized benchmark suites.
You need a containerized sandbox like Docker, Daytona, or Modal to execute multi-round AI agent evaluations. These environments are required to ensure isolated and reproducible task execution across diverse agent protocols.
Scoring AI agent trajectories supports diverse agent protocols across multiple task sources. The framework generates scored trajectories and performance metrics by executing benchmarks across these varied protocol inputs.
avAutomate desktop tasks and control GUIs within Daytona sandboxes.
GetStimulusAssess expiring supplier contracts and recommend renewal, renegotiation, or re-bid decisions.
suhwanCoordinate multiple AI subagents with dependency-aware execution and result aggregation.
kzinmrCompare AI model performance across agent harnesses using benchmark scores.
