Thesis Content Optim. - AFP
Description
✅ Deep optimization in 11 dimensions (simplification, coherence, error correction, structure, wording, detail, clarification, standardization, readability, professionalization, consistency) ✅ Automatic recognition of Chinese and English ✅ Processed paragraph by paragraph, each modification includes an explanation and waits for your confirmation ✅ Preserves original meaning and academic style
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WriteAIGC Reduction & Rewrite v7.0
📚 Academic Paper AIGC Reduction and Quality-Preserving Rewriting Expert v7.0 Designed for graduate students, researchers, and paper authors, this academic text optimization skill operates on a core closed loop of 'source control → process correction → result verification → reverse self-check → iterative re-check'. It systematically diagnoses and optimizes issues such as templated expressions, mechanical logic, vague content, inaccurate terminology, and style inconsistencies while preserving original meaning, technical terms, data, and core conclusions. 🔍📝 🌟 Core Capabilities 🔬 Multi-layer Risk Diagnosis Covers 10 types of universal text fingerprints and assists in identifying common expression patterns of models such as ChatGPT, Claude, DeepSeek, and Wenxin Yiyan. 🧠 Deep Semantic Restructuring Goes beyond synonym replacement to rebuild more natural and in-depth academic reasoning by adjusting proposition expression, information order, argument approach, and evidence organization. ✍️ Quality-Preserving Rewriting Comprehensively applies 13 sentence transformation strategies and 20 methods for cleaning high-frequency templated expressions, improving mechanical sentence structures, repetitive connectors, and overly rigid formatting. 📊 Full-text Structure Diagnosis Through macro-cycle and five key triangles, checks whether research problems, theory, literature review, methods, results, conclusions, and innovation form a complete closed loop. 🧩 Fine-grained Section Adaptation Develops differentiated diagnostic and rewriting strategies for abstract, introduction, literature review, research methods, results, discussion, and conclusion respectively. 🌐 Cross-language Risk Scanning Assists in identifying translationese, passive voice stacking, long sentence nesting, and mixed Chinese-English formatting abnormalities to make Chinese academic expression more natural and accurate. 🔄 Reverse Self-check Loop After rewriting, re-verifies from three aspects: technique distribution, new text fingerprints, and information integrity, to avoid 'becoming more templated' or losing key content. 🛡️ Academic Integrity Protection Does not fabricate literature, data, cases, or policy evidence; separately marks information requiring author verification and reminds users to honestly disclose AI usage. 🎯 Use Cases ✅ Single paragraph or partial section optimization ✅ Targeted modification of marked paragraphs from inspection reports ✅ Polishing of abstract, introduction, literature review, discussion, and conclusion ✅ Full-text AIGC risk feature diagnosis ✅ Language and structure adaptation for target journals ✅ Pre-submission quality review and consistency check 📦 Final Deliverables 📄 Quality-preserving rewritten text 🔎 Risk and issue diagnosis report 🛠️ Rewriting strategy and technique description ✅ Reverse self-check and information integrity report 💡 Items requiring author verification and subsequent revision suggestions 🎓 Original meaning preserved · Logic intact · No fabricated data · Academic quality maintained ⚠️ This skill aims to improve academic expression quality and reduce text risk features. It does not guarantee passage through any specific detection platform or achieving a particular detection score.
Paper Imitation & Pub. Expert
📚 Paper Imitation & Pub. Expert Develop an inspiring paper into your own high-quality original work step by step. Ideal for graduate students seeking to draw inspiration from excellent papers in other disciplines for topic migration, structural reconstruction, and submission optimization. 🔍 Inspiring Literature Identification: Analyze the reusable title mechanisms, problem awareness, chapter structure, theoretical framework, research methods, evidence organization, and language style of the model paper. 🔄 Interdisciplinary Paradigm Transfer: Build a 'source domain—target domain' transfer matrix to determine which ideas can be transferred and which theories, concepts, cases, and conclusions must be reconstructed. 🧠 Original Contribution Modeling: Identify literature gaps, distill core propositions and mechanisms, and check whether the paper merely changes the research object or applies a generic framework. 🧭 Research Design Planning: Supports theoretical research, case studies, qualitative research, quantitative research, literature reviews, policy text analysis, and mixed methods research. 🛡️ Real Evidence Gate: Do not fabricate data, samples, interviews, cases, statistical results, literature, or DOIs; without real evidence, do not generate false empirical conclusions. ✍️ Evidence-Driven Writing: Build argument chains via 'proposition—evidence—citation—rebuttal', generate original content chapter by chapter, and clearly mark research materials that need to be supplemented. 📈 Continuous Paper Evolution: Record each round of revisions, material gaps, and maturity changes according to L1 (topic conception), L2 (research plan), L3 (evidence formation), L4 (submission draft), and L5 (ready for submission). 🧑⚖️ Triple Simulation Review: Identify rejection risks from the perspectives of a theoretical reviewer, a method reviewer, and a target journal reviewer, and form specific revision strategies. 📨 Complete Submission Loop: Assist in generating the final paper, citation verification table, cover letter, innovation point statement, author response, revision index, and related declaration templates. ✨ Learn the paradigm, write original content, and enhance real submission competitiveness.
WriteFull-Process Academic Writing
"Full-Process Academic Writing" is an intelligent assistant tool designed for researchers, aimed at covering every stage of academic paper writing from initial conception to final submission. Whether you have just a vague research direction or have a draft that needs polishing, this tool provides systematic support to help you efficiently produce high-quality academic work. This tool guides you through four key stages. First is **Topic Planning**, which helps you refine preliminary ideas into concrete, feasible research topics and questions, and generates a comprehensive Topic Evaluation Report covering research framework, method matching, timeline planning, and resource bottleneck identification. Next is the **Literature Review** stage, assisting you in building search strategies, organizing core literature, and writing a logically rigorous literature review draft that identifies research gaps. The third stage is **Structured Writing**, where the tool designs a detailed paper outline based on your topic and literature review, and drafts the introduction, methods, body, and conclusions chapter by chapter, while also providing scientific chart code to ensure a complete structure and rigorous argumentation. Finally, the **Polishing and Revision** stage performs a comprehensive academic standard check, six-dimensional language polishing, and logical coherence review, and embeds an AI-assisted writing statement to ensure your final draft meets publishable professional standards. Throughout the writing process, this tool always adheres to academic ethics standards. All citations will be clearly flagged for verification and will never be fabricated. Output from each stage proceeds only after your confirmation, ensuring every step aligns with your research intent, allowing you to focus on expressing your ideas while leaving tedious formatting and standards to AI.
Thesis Content Optim. - AFP
Description
✅ Deep optimization in 11 dimensions (simplification, coherence, error correction, structure, wording, detail, clarification, standardization, readability, professionalization, consistency) ✅ Automatic recognition of Chinese and English ✅ Processed paragraph by paragraph, each modification includes an explanation and waits for your confirmation ✅ Preserves original meaning and academic style
Related Skills
View allWriteAIGC Reduction & Rewrite v7.0
📚 Academic Paper AIGC Reduction and Quality-Preserving Rewriting Expert v7.0 Designed for graduate students, researchers, and paper authors, this academic text optimization skill operates on a core closed loop of 'source control → process correction → result verification → reverse self-check → iterative re-check'. It systematically diagnoses and optimizes issues such as templated expressions, mechanical logic, vague content, inaccurate terminology, and style inconsistencies while preserving original meaning, technical terms, data, and core conclusions. 🔍📝 🌟 Core Capabilities 🔬 Multi-layer Risk Diagnosis Covers 10 types of universal text fingerprints and assists in identifying common expression patterns of models such as ChatGPT, Claude, DeepSeek, and Wenxin Yiyan. 🧠 Deep Semantic Restructuring Goes beyond synonym replacement to rebuild more natural and in-depth academic reasoning by adjusting proposition expression, information order, argument approach, and evidence organization. ✍️ Quality-Preserving Rewriting Comprehensively applies 13 sentence transformation strategies and 20 methods for cleaning high-frequency templated expressions, improving mechanical sentence structures, repetitive connectors, and overly rigid formatting. 📊 Full-text Structure Diagnosis Through macro-cycle and five key triangles, checks whether research problems, theory, literature review, methods, results, conclusions, and innovation form a complete closed loop. 🧩 Fine-grained Section Adaptation Develops differentiated diagnostic and rewriting strategies for abstract, introduction, literature review, research methods, results, discussion, and conclusion respectively. 🌐 Cross-language Risk Scanning Assists in identifying translationese, passive voice stacking, long sentence nesting, and mixed Chinese-English formatting abnormalities to make Chinese academic expression more natural and accurate. 🔄 Reverse Self-check Loop After rewriting, re-verifies from three aspects: technique distribution, new text fingerprints, and information integrity, to avoid 'becoming more templated' or losing key content. 🛡️ Academic Integrity Protection Does not fabricate literature, data, cases, or policy evidence; separately marks information requiring author verification and reminds users to honestly disclose AI usage. 🎯 Use Cases ✅ Single paragraph or partial section optimization ✅ Targeted modification of marked paragraphs from inspection reports ✅ Polishing of abstract, introduction, literature review, discussion, and conclusion ✅ Full-text AIGC risk feature diagnosis ✅ Language and structure adaptation for target journals ✅ Pre-submission quality review and consistency check 📦 Final Deliverables 📄 Quality-preserving rewritten text 🔎 Risk and issue diagnosis report 🛠️ Rewriting strategy and technique description ✅ Reverse self-check and information integrity report 💡 Items requiring author verification and subsequent revision suggestions 🎓 Original meaning preserved · Logic intact · No fabricated data · Academic quality maintained ⚠️ This skill aims to improve academic expression quality and reduce text risk features. It does not guarantee passage through any specific detection platform or achieving a particular detection score.
Paper Imitation & Pub. Expert
📚 Paper Imitation & Pub. Expert Develop an inspiring paper into your own high-quality original work step by step. Ideal for graduate students seeking to draw inspiration from excellent papers in other disciplines for topic migration, structural reconstruction, and submission optimization. 🔍 Inspiring Literature Identification: Analyze the reusable title mechanisms, problem awareness, chapter structure, theoretical framework, research methods, evidence organization, and language style of the model paper. 🔄 Interdisciplinary Paradigm Transfer: Build a 'source domain—target domain' transfer matrix to determine which ideas can be transferred and which theories, concepts, cases, and conclusions must be reconstructed. 🧠 Original Contribution Modeling: Identify literature gaps, distill core propositions and mechanisms, and check whether the paper merely changes the research object or applies a generic framework. 🧭 Research Design Planning: Supports theoretical research, case studies, qualitative research, quantitative research, literature reviews, policy text analysis, and mixed methods research. 🛡️ Real Evidence Gate: Do not fabricate data, samples, interviews, cases, statistical results, literature, or DOIs; without real evidence, do not generate false empirical conclusions. ✍️ Evidence-Driven Writing: Build argument chains via 'proposition—evidence—citation—rebuttal', generate original content chapter by chapter, and clearly mark research materials that need to be supplemented. 📈 Continuous Paper Evolution: Record each round of revisions, material gaps, and maturity changes according to L1 (topic conception), L2 (research plan), L3 (evidence formation), L4 (submission draft), and L5 (ready for submission). 🧑⚖️ Triple Simulation Review: Identify rejection risks from the perspectives of a theoretical reviewer, a method reviewer, and a target journal reviewer, and form specific revision strategies. 📨 Complete Submission Loop: Assist in generating the final paper, citation verification table, cover letter, innovation point statement, author response, revision index, and related declaration templates. ✨ Learn the paradigm, write original content, and enhance real submission competitiveness.
WriteFull-Process Academic Writing
"Full-Process Academic Writing" is an intelligent assistant tool designed for researchers, aimed at covering every stage of academic paper writing from initial conception to final submission. Whether you have just a vague research direction or have a draft that needs polishing, this tool provides systematic support to help you efficiently produce high-quality academic work. This tool guides you through four key stages. First is **Topic Planning**, which helps you refine preliminary ideas into concrete, feasible research topics and questions, and generates a comprehensive Topic Evaluation Report covering research framework, method matching, timeline planning, and resource bottleneck identification. Next is the **Literature Review** stage, assisting you in building search strategies, organizing core literature, and writing a logically rigorous literature review draft that identifies research gaps. The third stage is **Structured Writing**, where the tool designs a detailed paper outline based on your topic and literature review, and drafts the introduction, methods, body, and conclusions chapter by chapter, while also providing scientific chart code to ensure a complete structure and rigorous argumentation. Finally, the **Polishing and Revision** stage performs a comprehensive academic standard check, six-dimensional language polishing, and logical coherence review, and embeds an AI-assisted writing statement to ensure your final draft meets publishable professional standards. Throughout the writing process, this tool always adheres to academic ethics standards. All citations will be clearly flagged for verification and will never be fabricated. Output from each stage proceeds only after your confirmation, ensuring every step aligns with your research intent, allowing you to focus on expressing your ideas while leaving tedious formatting and standards to AI.
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