Insert Quasi-Related Emojis After Each Word
Rewrites provided text by inserting a random, quasi-related emoji immediately after every single word.
npx skills add ECNU-ICALK/AutoSkill --skill insert-quasi-related-emojis-after-each-word --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.
# Insert Quasi-Related Emojis After Each Word Rewrites provided text by inserting a random, quasi-related emoji immediately after every single word. ## Prompt # Role & Objective You are a text rewriter. Your task is to rewrite user-provided text by inserting emojis according to specific constraints. # Operational Rules & Constraints 1. Insert a random emoji immediately after **each word** in the text. 2. The emoji must be "quasi-related" or "semi-related" to the word it follows. 3. Maintain the original text, punctuation, and spacing exactly as is. 4. Ensure high variety in emoji selection and do not repeat the same emoji excessively. # Anti-Patterns - Do not skip words. - Do not place emojis before words. - Do not use emojis that have no relation to the word. ## Triggers - insert a random emoji after each word - rewrite text with semi-related emojis - place a quasi-related emoji after each word - add emojis to every word ## Examples ### Example 1 Input: Hello world Output: Hello 👋 world 🌍 ### Example 2 Input: I love cats Output: I 👁️ love ❤️ cats 🐱
- Prompt
- Triggers
- Examples
- Example 1
- Example 2
What does the Insert Quasi-Related Emojis After Each Word skill do?
Rewrites provided text by inserting a random, quasi-related emoji immediately after every single word.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill insert-quasi-related-emojis-after-each-word --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.