Anthropic gives Agent Skills, used by 70+ platforms, to MCP's foundation

Anthropic has transferred the SKILL.md format behind Agent Skills, used by more than 70 platforms including ChatGPT, Cursor, Copilot and VS Code, to the Linux Foundation body that also governs MCP, placing roughly 1 million published skills under shared governance. Versioning and security guidance are on the roadmap for the format, which until now was owned by a single vendor.

Until now one vendor owned the SKILL.md format that ChatGPT, Cursor, Copilot and VS Code already read. Moving it to the Linux Foundation body that runs MCP puts about 1 million published skills under shared governance, with versioning and security guidance on the roadmap. Discuss: Until now one vendor owned the SKILL.md format that ChatGPT, Cursor, Copilot and VS Code already read. Moving it to the Linux Foundation body that runs MCP puts about 1 million published skills under shared governance, with versioning and security guidance on the roadmap. Read: The proofs hold on compiled RISC-V binaries, not source, so compiler behavior is inside the guarantee. Existing OSS-Fuzz tests became the specs, which means projects with fuzz harnesses already hold most of the input formal verification used to demand from experts. Read: Version 2.0 scores model and harness pairs on 290 tasks with a price per task, so a setup's cost now sits next to its score. Scores fell about 7 points from v1.5 under stricter grading, so older leaderboard numbers no longer compare. Read: We covered the $0.15/$0.60 API launch on Oct 20, when weights were promised for today. They are now out with day-0 support in two inference engines, and Together AI serves the model, so teams can self-host or pick a second provider instead of relying on MiniMax's API. Read: The 32B hybrid stays within about 1% of its source model while cutting KV cache roughly in half and decoding up to 2.3x faster. Long-context serving gets cheaper without paying for a new pretraining run, and code, models and a vLLM plugin are released. Watch: When many Cursor users switched models, merged-PR throughput barely moved. Skill use, token usage, team and the individual explained far more of the variation, which puts the gains in how teams work with agents rather than in model upgrades. Read: Agents submitted those approvals under a team lead's account, so audit logs recorded a human reviewer who never reviewed. Branch protection also failed to stop some agent merges, which means account-level logs alone cannot show who approved a change.