Anthropic donates Agent Skills to the Linux Foundation’s Agentic AI Foundation

Saturday, 24 October 2026By Sridhar Mukkandi1 min read

Anthropic said on 22 October that it is donating Agent Skills, the open standard for giving AI agents specialised knowledge and workflows, to the Agentic AI Foundation, which operates under the Linux Foundation. A skill is a folder with a SKILL.md file and any supporting scripts or reference material. The donation includes the standard, its name and logo, the GitHub organisation and the agentskills.io domain.

Anthropic says more than 70 agent platforms, including ChatGPT, Cursor, GitHub Copilot and VS Code, have integrated Agent Skills, with 1 million published skills and nearly 280 million installs. Engineers from Anthropic, Google, OpenAI and other companies will maintain it as individuals. Anthropic co-founded the foundation with Block and OpenAI and has also donated the Model Context Protocol to it.

So what

Nothing changes for builders today: skills you write keep working. Neutral governance makes the format a safer long-term bet, and the planned security guidance for skill authors and installers is worth following before you install third-party skills.

SourceAnthropicwww.anthropic.com/news/donating-agent-skills-to-the-agentic-ai-f Go deeper · EssayRead-only first: how much access should an agent get?

Drafted with AI from the original source, then checked and edited by Sridhar Mukkandi. Spotted a mistake? Write to hello@tarkika.com and we'll correct it here.

More from The Signal

Research Microsoft’s ThinkingBox turns database checks into rewards for training agentsChecking the state an agent leaves behind is a more honest test than reading its transcript, and the same check doubles as a training reward. Start with the three actions your agent takes most often. Microsoft and Hugging Face Agents Bayer Crop Science runs 22 read-only agents over its ML decision engine on AWSRead-only agents with narrowly scoped tools, launched to a small group first, is a pattern worth copying. So is testing a new model against your own tool calls before you switch: newer isn't always compatible. AWS Machine Learning Blog Tools AWS lets you write your own model-training loop on SageMaker without managing GPUsCustom reinforcement learning used to mean renting and babysitting GPUs. If you can write a check for a good outcome, you can now train on it without running the infrastructure yourself. AWS Machine Learning BlogAll stories