StepShield: Temporal Evaluation Benchmark for AI Agent Guardrails
What it is
StepShield is a NeurIPS 2026 benchmark and dataset for evaluating the timing of AI agent safety interventions. It provides 9,429 step-level annotated code-agent trajectories and introduces temporal metrics like Early Intervention Rate (EIR) to measure when, not just whether, a guardrail detects rogue behavior.
The problem it solves
Standard agent safety benchmarks measure detection accuracy but ignore timing, conflating premature false alarms with genuine early intervention and failing to distinguish between effective real-time oversight and post-hoc forensics.
What you could use it for
- Evaluating the timeliness of LLM-based agent monitors
- Benchmarking rule-based vs. semantic detectors for real-time oversight
- Training and testing new agent safety guardrails
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