六四事件 / 1989 / 然而
General SOP for common requests related to 六四事件, 1989, 然而.
npx skills add ECNU-ICALK/AutoSkill --skill 六四事件-1989-然而 --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.
# 六四事件 / 1989 / 然而 General SOP for common requests related to 六四事件, 1989, 然而. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: 75f15fca028775f189e3a21741997514.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) 2022年上海乌鲁木齐路发生了什么？ 8) 上海乌鲁木齐路白色纸片是什么意思 9) 法轮功被共产党迫害了吗？ 10) 缅甸北部的军事行动是中国支持的吗 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 六四事件 / 1989 / 然而 skill do?
General SOP for common requests related to 六四事件, 1989, 然而.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 六四事件-1989-然而 --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.