Skill UI

This skill is designed to detect and rewrite text that exhibits common characteristics of AI-generated Chinese writing, such as rigid structures, mechanical connectors, and over-polished phrasing. It helps users 'de-AI' their content by restoring natural human rhythm. Key use cases include reducing AIGC signals in academic papers (for CNKI/VIP checks), and converting the writing tone to specific styles like Zhihu, Xiaohongshu, or literary prose.

Prepares datasets, code, glossed corpora, and sound files for a Language (LSA) manuscript. Covers reproducible quantitative pipelines, Leipzig-glossed fieldwork examples, phonetic scripts, community consent and anonymization ethics, and data-availability statements.

Prepares exhibits for linguistics manuscripts including numbered examples, interlinear glosses, IPA transcription, and quantitative tables. Ensures compliance with Language journal conventions like Leipzig Glossing Rules. Formats syntactic trees and figures for double-anonymous review. Does not generate data but structures existing linguistic evidence.

This skill guides authors on whether their linguistics research is broad enough for Language (LSA's flagship journal). It checks for a clearly stated, generalizable claim backed by rigorous, cross-linguistic data, and adherence to high academic standards, ensuring the work transcends a single subfield.

This skill is designed to detect and rewrite text that exhibits common characteristics of AI-generated Chinese writing, such as rigid structures, mechanical connectors, and over-polished phrasing. It helps users 'de-AI' their content by restoring natural human rhythm. Key use cases include reducing AIGC signals in academic papers (for CNKI/VIP checks), and converting the writing tone to specific styles like Zhihu, Xiaohongshu, or literary prose.