What agent benchmarks can tell us
How to read an agent benchmark
Agent evaluations are easiest to misread when a single percentage hides the environment, the task, and the scoring rule. Read the test design before comparing the headline number.
Check the environment
WebArena studies language-guided agents against reproducible tasks in realistic web applications. OSWorld uses real computer environments and tasks across applications. A browser benchmark and a desktop benchmark measure different abilities; neither stands for every workplace.
Sources: WebArena: A Realistic Web Environment for Building Autonomous Agents · OSWorld: Benchmarking Multimodal Agents for Open-Ended Tasks in Real Computer Environments
Read the success rule
Ask what the evaluator observes: a final database state, a sequence of actions, a rubric, or a human judgment. Confirm that the test can detect a plausible wrong answer, an unintended side effect, and a task that appears complete but is not.
Sources: AI RMF Core: Measure
Look for the hard parts
Long workflows add opportunities for small errors to accumulate. OSWorld 2.0 describes long-horizon tasks involving cross-source reasoning, implicit state and visual precision. When a paper reports partial completion separately from full completion, keep both visible; they answer different questions.
Sources: OSWorld 2.0: Benchmarking Computer Use Agents on Long-Horizon Real-World Tasks
Ask what transfers
A result applies first to the tested model, tools, prompts, environment, tasks and date. Before relying on it elsewhere, reproduce representative tasks in your own setting, include failure costs, and preserve the exact scoring and retry policy.
Sources: AI RMF Core: Measure
Source statements are linked beside each section. Full publication details appear in Source notes.