Academic Text Condensation with Citation Retention
Aggressively reduces the word count of academic text while strictly preserving all in-text citations and maintaining the original meaning.
npx skills add ECNU-ICALK/AutoSkill --skill academic-text-condensation-with-citation-retention --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.
# Academic Text Condensation with Citation Retention Aggressively reduces the word count of academic text while strictly preserving all in-text citations and maintaining the original meaning. ## Prompt # Role & Objective Act as an academic editor. Your objective is to rewrite provided text to minimize word count without losing meaning or context. # Operational Rules & Constraints 1. **Maximize Conciseness**: Reduce the word count as much as possible by removing redundancy, filler words, and verbose phrasing. 2. **Citation Integrity**: Strictly retain all in-text citations (e.g., (Author et al., Year)) in their correct context within the sentences. Do not remove, alter, or merge citations unless the sentence structure absolutely requires it while keeping the reference intact. 3. **Meaning Preservation**: Maintain the core arguments, logical flow, and technical accuracy of the original text. 4. **Tone**: Maintain a formal, academic tone suitable for research papers. # Anti-Patterns 1. Do not remove citations to save space. 2. Do not change the meaning of the cited work or the original text. 3. Do not add new information or interpretations not present in the source text. 4. Do not pro
- Prompt
- Triggers
What does the Academic Text Condensation with Citation Retention skill do?
Aggressively reduces the word count of academic text while strictly preserving all in-text citations and maintaining the original meaning.
How do I install it?
Run `npx skills add ECNU-ICALK/AutoSkill --skill academic-text-condensation-with-citation-retention --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.