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.

Generates structured peer-review quality critiques of academic papers, covering summaries, methodology scrutiny, contribution evaluation, literature positioning, and recommendations across domains whenever a user requests reviews, analyses, or summaries of research publications.

This skill provides comprehensive interaction with the DeerFlow AI agent platform via its robust HTTP API. It is designed for managing complex, multi-step AI workflows, including deep academic research, code execution, web browsing, and file analysis. Users can initiate and continue conversation threads, manage agent memory, upload documents (PDF, etc.), and delegate complex research tasks to the autonomous agent system.

Creates formally structured .docx academic documents with auto-updating TOC, OMML equations, styled headings, footnotes/endnotes, and bibliography formatting for research reports or policy briefs.

Generates professional conference presentation slides from a compiled research paper. This skill produces dual outputs: a polished Beamer LaTeX PDF for high-quality typesetting, and an editable PPTX for flexible adjustments. It supports multiple talk types (Poster, Spotlight, Oral, Invited) and includes detailed guidelines for speaker notes and talk scripting, making it essential for academic researchers preparing for major ML and systems conferences.

Provides a comprehensive audit of content quality, focusing on E-E-A-T (Experience, Expertise, Authoritativeness, Trustworthiness) signals, readability, and structural integrity. Use this tool when reviewing content for SEO optimization, assessing academic citation readiness, or ensuring adherence to modern search engine and AI best practices.

This skill enhances research query formulation by translating vague, colloquial, or generalized descriptions into precise, standard academic terminology. When initial search terms are broad (e.g., "conjugal happiness"), this technique suggests multiple plausible academic synonyms (e.g., "marital satisfaction," "relationship quality"). By improving the precision of the search query and incorporating structured constraints (like keywords, years, or sample sizes), it significantly boosts the relevance and effectiveness of academic paper retrieval.

The Paperzilla skill provides direct command-line access to interact with Paperzilla data. Users can fetch the latest research recommendations, summarize canonical papers in markdown format, view project feeds, leave feedback, and export data in various formats (JSON, Atom). It is essential for researchers needing structured insights into academic projects and literature.

This skill teaches users how to optimize search queries for specific, structural information found within academic theses or dissertations. It emphasizes the critical need to include qualifying terms like "acknowledgment," "thesis," or "dissertation" in searches to successfully retrieve details about committee members, dedicating recipients, or other section-specific data, rather than just topic abstracts. This dramatically improves the relevance and accuracy of information retrieval.

This technique guides users on how to construct highly specific search queries for academic papers. Instead of relying solely on broad topic keywords, users should prioritize combining concrete numerical identifiers—such as exact sample sizes, population percentages, concentration levels, or specific year ranges—with methodological terms and discipline keywords. Using these numerical anchors significantly increases the uniqueness and precision of the search results, helping to pinpoint the exact study required.

This advanced technique assists in precisely locating academic theses by combining key identifiers: university name, degree type, and year. Its core strength is resolving indirect university clues (e.g., determining a founding year from a literary work or historical event) first. This two-step resolution process ensures that the final search for the thesis is highly accurate, even when the university is described obliquely.

A comprehensive academic advisor covering the entire university journey. It guides students through major selection, GPA management, graduate school applications (Chinese and Western systems), study abroad planning, and career transition. Methodology includes Socratic questioning and structured decision-making to help users make informed, autonomous academic choices.