同义句转换 / 习近平强调 / conversation
General SOP for common requests related to 同义句转换, 习近平强调, conversation.
npx skills add ECNU-ICALK/AutoSkill --skill 同义句转换-习近平强调-conversation --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.
# 同义句转换 / 习近平强调 / conversation General SOP for common requests related to 同义句转换, 习近平强调, conversation. ## Prompt Follow this SOP (replace specifics with placeholders like <PROJECT>/<ENV>/<VERSION>): 1) Offline OpenAI-format conversation source. 2) Title: 613b8f1020f5ebfaa53e4d40f9e8898f.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) 在坚定中国特色社会主义大方向的基础上，中国不断探索多样化的道路，全面考虑不断变化的党情、国情和世情。 同义句转换 8) 随着中国特色社会主义制度的不断完善和发展，以及国家治理体系和治理能力现代化水平的不断提高，“中国方案”所蕴含的“中国道路”的优势必将更加明显，所蕴含“问题意识”更加突显出“中国特色”的实践优势和“社会主义”的方向优势。 9) 同义句转换 10) 习近平强调，每一次人类社会的重大进步、每一次人类文明的重大发展，都与哲学社会科学的知识变革与正确的思想引领密不可分。 同义句转换 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 同义句转换 / 习近平强调 / conversation skill do?
General SOP for common requests related to 同义句转换, 习近平强调, conversation.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill 同义句转换-习近平强调-conversation --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.