Will using this tool compromise my technical accuracy?

No, the skill has strict 'hard rules' to never change technical content, factual claims, or citations. It focuses purely on stylistic and structural improvements.

How does Writing De-AI detect AI-generated patterns?

It evaluates text using 10 specific metrics, including hedging overuse, superlative claims, passive voice ratios, and sentence length variance to calculate an overall 'AI-likeness' score.

Does it work with LaTeX files?

Yes, it is designed to scan LaTeX structures like main.tex and section inputs, as well as standard Markdown drafts.

Will this skill automatically change my research paper?

No, the skill follows a 'suggest, don't apply' rule. It generates a report with suggested rewrites, allowing you to maintain full control over the final manuscript.

Writing De-AI

Name: Writing De-AI
Author: jacazjx

byjacazjx

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Gestión de Contenido

Detects and refines AI-generated patterns in academic drafts to restore authentic human voice and improve prose quality.

Writing De-AI is a specialized skill designed to help researchers identify and mitigate telltale signs of LLM-generated text in academic manuscripts. By analyzing text across ten distinct categories—such as hedging overuse, formulaic transitions, and uniform sentence length—the skill generates a comprehensive score and a detailed report. It identifies the most significant 'AI-likeness' issues and provides context-aware rewrite suggestions that preserve technical accuracy and citations while enhancing the authorial voice, making it an essential final check before journal submission.

Características Principales

01Preservation of technical claims and citation integrity

02Automated scanning of LaTeX (.tex) and Markdown (.md) paper drafts

03Targeted rewrite suggestions for the top 5 worst stylistic offenders

04Context-aware identification of generic fillers and formulaic transitions

051 GitHub stars

06Comprehensive 50-point scoring system across 10 detection categories

07Detailed reporting including sentence-level issue logging and scoring

Casos de Uso

01Identifying robotic or monotonous sentence structures in long-form technical content

02Humanizing the introduction and discussion sections of academic manuscripts

03Polishing AI-assisted research paper drafts before peer review

Características Principales

01Preservation of technical claims and citation integrity

02Automated scanning of LaTeX (.tex) and Markdown (.md) paper drafts

03Targeted rewrite suggestions for the top 5 worst stylistic offenders

04Context-aware identification of generic fillers and formulaic transitions

051 GitHub stars

06Comprehensive 50-point scoring system across 10 detection categories

07Detailed reporting including sentence-level issue logging and scoring

Casos de Uso

01Identifying robotic or monotonous sentence structures in long-form technical content

02Humanizing the introduction and discussion sections of academic manuscripts

03Polishing AI-assisted research paper drafts before peer review