npx skills add ECNU-ICALK/AutoSkill --skill 身边-心里-脸上 --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 身边 / 心里 / 脸上 General SOP for common requests related to 身边, 心里, 脸上. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: f7edd79984140c27dc2337969a6ff686.json#conv_1 3) Use the user questions below as the PRIMARY extraction evidence. 4) Use the full conversation below as SECONDARY context reference. 5) In the full conversation section, assistant/model replies are reference-only and not skill evidence. 6) Primary User Questions (main evidence): 7) 动物农场概述 8) 动物农场中两只猪拿破仑（Napoleon）和雪球(Snowball) 人物性格和暗示 9) 世界上的政治家 希特勒 斯大林 和毛泽东的共同特点 10) 世界上曾经的大独裁者 For each step, include: action, checks, and failure rollback/fallback plan. Output format: for each step number, provide status/result and what to do next. ## Triggers - Use when the user asks for a process or checklist. - Use when you want to reuse a previously mentioned method/SOP. ## Examples ### Example 1 Input: Break this into best-practice, executable steps.
- Prompt
- Triggers
- Examples
- Example 1
What does the 身边 / 心里 / 脸上 skill do?
General SOP for common requests related to 身边, 心里, 脸上.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 身边-心里-脸上 --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ECNU-ICALK/AutoSkill, a repository with 539 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.