Agent Skills 标准捐献与技能编写六条铁律

Anthropic just donated the Agent Skills standard to the Linux Foundation, the same home MCP went to. Since it launched last October, 𝟭 𝗺𝗶𝗹𝗹𝗶𝗼𝗻 𝘀𝗸𝗶𝗹𝗹𝘀 have been published and installed nearly 280 million times, and 70+ agent platforms support it, including ChatGPT, Cursor, GitHub Copilot and VS Code. Over that year, how to write a skill settled into a standard method, and the official guide went to the foundation too. The 6 most useful rules from it: → Do the task with your agent for real first, then turn the steps that worked, the corrections you made, the input and output formats and the context you added into the skill. A model writing from general knowledge gives you filler like "handle errors appropriately" → Ask of every line: would the agent get this wrong without it? If not, cut it → At startup the agent reads only the name and description, so the description decides whether the skill ever gets used. Write it as "use this skill when...", lean pushy, list the cases users won't spell out, and stay under 1,024 characters → Keep SKILL.md under 500 lines and 5,000 tokens, move details into references/, and say when to read which file → Hard-code the exact command for fragile steps, explain the why where there's room for judgment, and when there are several ways to do something, give one default → In many skills the most valuable part is 𝘁𝗵𝗲 𝗴𝗼𝘁𝗰𝗵𝗮𝘀 𝗹𝗶𝘀𝘁: every time you have to correct the agent, add a line Right after your agent finishes a task you hand it often, send this to Claude Code in the same session to save how you did it as a standard skill 👇 "Following https://t.co/YN17Wv07wD, turn the task we just did into a skill. Use only the steps that worked in this conversation, the places I corrected you, and related fixes in CLAUDE.md, AGENTS.md and the git history; don't fill gaps from general knowledge. Write the description as 'use this skill when...', include cases I didn't spell out but that should trigger it, and keep it under 1,024 characters. Keep SKILL.md under 500 lines, move details into references/ with a note on when to read each file, and give the gotchas their own section. Use lowercase letters, numbers and hyphens for the name, matching the folder name. Finally, write 2-3 real test cases in evals/evals.json (prompt plus expected output), run each one, and show me the results and what you did."

We're donating Agent Skills to the Agentic AI Foundation (@AgenticAIFdn), the same foundation we donated MCP to. Since December 2025, 70+ agent platforms have integrated the standard, including ChatGPT, Cursor, GitHub Copilot, and VS Code. Here's what that means for you: