Benchmark RadarToolBench-X
ToolBench-X evaluates tool-using agents on multi-step tasks with executable tools and automatic scoring, in environments that include recoverable reliability hazards such as specification drift, invocation errors, execution failures, output drift, and cross-source conflicts.
- Released
- 2026-06-24
- Readiness
- Runnable
- Primary field
- General AI
Why it matters
Existing tool-use benchmarks assume stable tool environments, leaving a gap in evaluating agent performance under realistic unreliability. ToolBench-X provides a way to measure and compare agents' ability to diagnose and recover from tool hazards, which is crucial for practical deployment.
Motivation
Large language models are increasingly deployed as agents that solve tasks by interacting with external tool environments.
Primary resources
Benchmark Radar records only publicly supported details and links back to primary sources for verification.