Agent evaluation
Find the right agent and model for the job.
AgentSky's Agent Playground benchmarks agent harnesses and models against the same real tasks, measuring quality, speed, and cost in a live cloud runtime. Teams pick the configuration that performs best on their work, then start a compatible cloud agent from the same platform without building a separate runtime.
Teams pick an agent stack once on gut feel, then rebuild when it underperforms on real work.
How it works
One job. One complete cloud agent.
Performance is visible across task categories
Compare harness and model pairs across coding, research, support, and other real task categories.
Quality, speed, and cost balance before committing
Balance all three instead of assuming one agent stack wins every task.
Move from ranking to running in one step
Start the compatible cloud agent without building a separate runtime.
You choose
- Task category
- Agent harness
- Compatible model
AgentSky runs
- Sandbox
- Persistent session
- Usage and cost tracking
Agent Playground
AgentSky ranks agent harnesses and models by quality, speed, and cost across real task categories. The rankings are generated from live runs against actual work — not benchmarks written for the purpose.
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