Optimize LaTeX theses to reduce AI-detection and plagiarism while polishing writing.
npx skills add https://github.com/Haimbeau1o/thesis-optimizer --skill thesis-optimizer
Please help me install this Agent Skill. Skill: thesis-optimizer Source: https://github.com/Haimbeau1o/thesis-optimizer/tree/main Command: npx skills add https://github.com/Haimbeau1o/thesis-optimizer --skill thesis-optimizer
Thesis-optimizer automates the optimization of academic theses to reduce AI-detection and plagiarism risk while elevating scholarly writing quality, enabling researchers to meet publication standards with traceable workflow.
Provide the path to your thesis LaTeX source and ask me to start AI-detection reduction, plagiarism reduction, and polishing.
High-intent search queries and answers about installing and using this skill.
Thesis optimization reduces AI-detected generation in computer science theses by applying three-dimensional optimization across full documents or individual chapters while preserving core technical content. It tracks optimization state explicitly so progress remains traceable throughout the workflow.
Plagiarism reduction for LaTeX theses uses a two-tier document architecture with explicit state tracking and progress visualization. You provide the LaTeX source path, and the workflow generates chapter-level task documents with centralized progress management for traceable optimization.
Per-chapter refinement is supported alongside full-document optimization. The workflow generates chapter-level task documents and applies AI-detection reduction, plagiarism reduction, and polishing to individual chapters while maintaining centralized progress management and traceable state tracking.
Thesis optimization is designed for computer science and related theses. It handles full-document and per-chapter refinement with explicit state tracking, but its optimization for AI-detection reduction, plagiarism reduction, and polishing is tailored to computer science contexts and related technical writing.
Progress tracking during plagiarism and AI-detection reduction uses a two-tier document architecture with explicit state tracking and progress visualization. The workflow automatically generates chapter-level task documents and manages progress centrally, providing traceable updates throughout the optimization process.
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