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ComplexMCP Finds Tool-State Gaps
ComplexMCP is a useful benchmark because it tests the part of tool use that simple function-calling tasks avoid: one action changes the state that the...
ToolGrad Turns Tool Failures Into Data
Google's ToolGrad reframes tool-use training data as an execution problem before it is a prompt-writing problem. Instead of asking a model to invent a...
Can Next-Turn Metrics Test Workflows?
The paper *When Better Turns Do Not Make Better Agents* tests a quiet failure in agent evaluation: a model can improve at predicting the next local action...
Hyper-Tau Bench Tests Agent Building
Hyper-Tau Bench changes the unit of evaluation from an agent using tools to a coding system building a deployable customer-service agent [Hyper-Tau...
Mid-Range Tasks Cut Agent Eval Cost
Efficient Benchmarking of AI Agents asks a practical release question: can teams compare agent systems without rerunning every expensive interactive task...
Messier Maps Agent Benchmark Drift
Messier, revised on 30 August 2026, treats agent evaluation as a data-integration problem rather than another leaderboard race...
Tool Parallelism Has A Scheduling Problem
PeakBench is a useful benchmark because it tests a failure that rarely appears in tool-use leaderboards: an agent can choose the right calls, respect the...
VAKRA Shows API Reasoning Decay
VAKRA is an August 2026 benchmark for checking whether systems can reason across APIs, retrieved documents and natural-language tool policies in one...
ScrambleToolBench Finds Tool-Map Inertia
ScrambleToolBench is a 3 August 2026 benchmark for a practical tool-use failure: a system can learn what hidden tools do, then fail to revise that map...
ParEvalLayer Makes Partial Evals Decidable
ParEvalLayer is a 3 August 2026 proposal for a practical agent-evaluation problem: teams often see early task outcomes before a full benchmark run...