as / were / japanese
General SOP for common requests related to 然而, conversation, evidence.
npx skills add ECNU-ICALK/AutoSkill --skill as-were-japanese --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.
# as / were / japanese General SOP for common requests related to 然而, conversation, evidence. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: 1058e1cbf9fcecd66f8346270444a957.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) 你知道世界上有多少人吗 8) 你能介绍一下英国解佳撰的《长生术》吗 9) 概括这段话的大意：有一楼油画北清战事，不忍观。日人非夸张。强武欲国人时时往观，知所警惧，借玩好以激励志气也，如近日露兵局，处处设报，家家有图，人人演说，真有国事如家事之慨。前月坏战舰二，国人相聚失色，某学校学授上堂演说，大哭失声。是日竟罢教事，报一胜仗，国人大喜，门前竖日本国旂，燃双灯，上书：大日本帝国万岁。一家如是，万家皆如是，国人男妇额手称庆，卖报人手持报纸，臀赘二三铃，冲市乱跑，若有非常之喜者，仍异中人之售乡会试题名录也。日人常云，中国无国史。予警其说，请道所谓，日本人云：中国之史，皆纪皇上一家之事，事不关朝廷，纪载缺如臣庶人民，数千年无私成国史之书。予以为知言。 10) 能分析作者和的情感态度吗 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/S
- Prompt
- Triggers
- Examples
- Example 1
What does the as / were / japanese skill do?
General SOP for common requests related to 然而, conversation, evidence.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill as-were-japanese --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.