Anthropic is donating the Agent Skills standard to the Agentic AI Foundation.
Skills package task instructions and resources; the foundation will provide a vendor-neutral home for the standard.
Reusable workflows can travel across compatible agent tools.
Document one repeatable task as a short checklist.
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Sign in to join the conversationOpen-source Bark can generate speech, music, laughter, and sound effects from a single text prompt. The source says it supports 13 languages and more than 100 voice presets, but it may alter wording or add unexpected sounds. Bark generates audio clips of about 13–14 seconds and is released under the MIT license. The source reports about 12 GB of GPU memory for the full models, with smaller variants available for lower-memory use.
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AutoTrust Labs released JEV-27B v1.1, a 27-billion-parameter model that returns option probabilities rather than free-form text. The company reports a score of 67.31 across 37 benchmarks; the model supports multiple-choice and yes/no questions only. The model selects among supplied options and returns a probability distribution. It stands out on tool selection and intent classification, but is weaker on open-ended reasoning and some other tests.
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In Vals AI’s simulated tests, Deepseek V4.1 Flash 1017 came close to a leading closed model in some scenarios. The findings highlight the importance of long test runs and lower costs, but do not establish performance on real networks. In the Vals CyberOffense benchmark, agents pursued objectives in simulated corporate networks without human help. GPT-6 Sol Daybreak averaged 15.7/21 objectives in Nova and reached 27/31 in Lighthouse; Deepseek V4.1 Flash 1017 scored 16.3/21 and 21/31. Vals reports approximate run costs of $22 and $3, respectively.
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