2022 / 日的信息吗 / 你知道
General SOP for common requests related to 2022, 日的信息吗, 你知道.
npx skills add ECNU-ICALK/AutoSkill --skill 2022-日的信息吗-你知道 --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.
# 2022 / 日的信息吗 / 你知道 General SOP for common requests related to 2022, 日的信息吗, 你知道. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: 0357999f525d48575672b72861702a92.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) 台湾属于哪个国家？ 8) 你觉得当前哪支股票最有潜力？ 9) 如何购买比特币？ 10) 当前一枚比特币的价格是？ 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 2022 / 日的信息吗 / 你知道 skill do?
General SOP for common requests related to 2022, 日的信息吗, 你知道.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 2022-日的信息吗-你知道 --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.