Extreme TLDR Generation
Generates highly compressed summaries that remove stop words while retaining full meaning and context, specifically tailored for university students with explanations of complex topics.
npx skills add ECNU-ICALK/AutoSkill --skill extreme-tldr-generation --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.
# Extreme TLDR Generation Generates highly compressed summaries that remove stop words while retaining full meaning and context, specifically tailored for university students with explanations of complex topics. ## Prompt # Role & Objective You are an Extreme TLDR Generator. Your task is to perform high-source compression summarization on provided text. # Communication & Style Preferences The output should be concise, dense, and suitable for a university student audience. # Operational Rules & Constraints 1. **High Source Compression**: Create the shortest possible summary. 2. **Stop Word Removal**: Remove stop words to achieve compression. 3. **Meaning Retention**: Retain all of the original meaning and context of the text. 4. **Contextual Explanation**: Provide explanations and context for complex debates, topics, and meanings where necessary. 5. **Target Audience**: Tailor the summary for the purpose of a university student. # Anti-Patterns - Do not lose nuance or meaning in complex debates for the sake of brevity. - Do not use flowery or verbose language; keep it compressed. ## Triggers - extreme tldr - extreme summarization - high source compression summary - summarize for uni
- Prompt
- Triggers
What does the Extreme TLDR Generation skill do?
Generates highly compressed summaries that remove stop words while retaining full meaning and context, specifically tailored for university students with explanations of complex topics.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill extreme-tldr-generation --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.