Full-Process Academic Writing
From topic to final draft, AI-assisted
Description
Why we love this skill
This skill offers one-stop academic writing guidance from topic to final draft, with full AI assistance, incorporating academic meta-theory and rigorous red-line principles to ensure paper quality and academic standards.
"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.
Related Skills
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Research Proposal Assistant
Tailored for university faculty and researchers, this AI assistant provides comprehensive guidance in writing humanities and social science research proposals, covering the entire process from topic generation to outcome planning. Whether you need to brainstorm a topic from scratch or optimize a specific section of your proposal, this tool offers expert-level guidance and support. This assistant combines expert experience with a strategy of 'example guidance + writing theory integration' to help you efficiently produce high-quality proposals. You receive targeted analysis of research hotspots in your discipline, topic refinement suggestions, and—based on your research direction and project type—generate a rigorous background, in-depth literature review, and insightful research value statement. In the research content design phase, the assistant helps you define the research subject, build a logically clear research framework, and recommend innovative research ideas and methods. It also helps you distill key points and difficulties, set clear research objectives, and plan a detailed research schedule and feasibility analysis, ensuring your proposal is rigorous and well-structured. Additionally, you can use this tool to deeply explore the innovative aspects of your topic in terms of academic ideas, viewpoints, and research methods, and systematically plan multiple forms of expected outcomes, their applications, and social benefits. Finally, all content is integrated with one click to generate a complete, logically rigorous proposal that meets submission standards, helping you increase your success rate.
ResearchAcademic Paper Writing v4.1
A full-process academic paper writing system that combines the Five Sources model with the AFP 3.1 three-layer architecture. Other AI tools help you "write" a paper; this one helps you "plug" every hole that could get it rejected—from one vague idea to a complete submission package in a single run through seven modules, with an anti-hallucination gate, archive-code resume, and four-core review. [10-second value] One sentence of an idea → a submittable, complete paper package. Real sources are enforced throughout, every citation is verifiable, and you can resume across sessions right where you left off. [Trigger phrases] write a paper / literature review / research method design / how to write the discussion / paper polishing / abstract & keywords / submission package [Seven modules, all fully executable instructions] Phase 1 Topic & Introduction → Phase 2 Literature Review → Phase 3 Research Method Design → Phase 4 Discussion → Phase 5 Conclusion → Phase 6 Abstract & Keywords → Phase 7 Full-Text Integration & Submission Package. Phase 0 entry routes A–G map one-to-one to the seven modules, with an R option to restore your last progress via an archive code or archived document. [v4.1 upgrades] 1. Evidence-chain gate (hard constraint): a material registry (M1/M2 numbering) + four citation elements (author / year / title / verifiable locator) + three-color marking (✅ user-supplied / ⚠️ to verify / 🚫 prohibited). If the material library is empty, the system outputs only an outline and search queries and refuses to generate body text with citations; generating references from memory or fabricating volume, issue, or page numbers is forbidden. 2. Archive-code protocol: each module ends with a structured archive code that can be saved as a YouMind document. In your next session, simply reference it with @ to resume without re-requesting already locked information. 3. Reproducible scoring: the C core anchors all dimensions to behavioral standards scored at 4/6/8/10 with stated rationale; the ratchet mechanism only moves scores upward, never downward. 4. Four-discipline configuration library (1A Humanities & Arts / 1B Social Sciences / 2A Science & Engineering / 2B Agriculture, Medicine & Life Sciences), with automatic switching of theory libraries, method toolboxes, and disciplinary norms; Category 2B runs ethics review checkpoints at Phases 0, 3, and 7. 5. Three-paradigm routing (quantitative / qualitative / theoretical): literature review narrative strategies and research method design follow different paths. 6. Anti-cliché checklist and prohibitions: discussion sections using phrases like "limited time and energy" or "pending further research," conclusions introducing new data or literature, and abstracts containing claims unsupported by the body text are all sent back by the B core. 7. Adaptivity: user profile (beginner / intermediate / proficient) + paper type (journal / thesis / conference / course) + pacing mode (default / fast-forward / slow-motion) + multi-task isolation. 8. Submission package & compliance: seven consistency checks, a six-link logic chain, reference formatting (GB/T 7714 / APA 7 / Vancouver / IEEE), ethics approval number, data availability statement, generative AI use disclosure draft, and cover letter draft. [How to use] Tell the system: your discipline, target journal / paper type / word count, and which stage you're at. The system advances module by module, pausing after each one to deliver the section, review report, scorecard, and archive code, then waits for your confirmation before continuing. [Responsibility boundaries] The system handles sources 1–4 (structure, material organization, style, integration); source 5, human calibration, is yours: academic judgment, fact-checking, and innovation decisions. All ⚠️-marked citations and data must be verified by you item by item before submission; this skill does not promise any acceptance or pass outcome.
Teaching Paper Architect
From teaching research accumulation to CSSCI/SSCI/SCI — making every teaching paper stand up to peer review. This is not a tool that writes your paper for you, but a paper architect that understands educational academic norms. It knows that IMRaD is not just four letters but a rigorous argument logic; that a literature review is not a list of references but a precise positioning of research gaps; that effect sizes are more convincing to reviewers than p-values. Seven-stage full-process coverage: Topic Focus (Innovation Three-Question Check) → Literature Review (Three-Level Coding + Funnel Writing) → Research Design (Quantitative/Qualitative/Mixed Approach Decision) → Data Analysis (Statistical Method Decision Tree) → Discussion Construction (Contribution Self-Check Matrix) → Language Refinement (AI Removal + Language Elevation + Revision Notes) → Journal Adaptation (Matching Matrix + Rejection Risk Pre-Reinforcement). Built-in Triple-Core Adversarial Engine: The Academic Writer handles output, the Language Elevation Officer polishes, and the Academic Gatekeeper has veto power—are the references real? Is the data reliable? Is the argument grounded in evidence? Does the contribution match the target journal level? Five dimensions are audited item by item; if any fail, it is sent back for rework. It doesn't just help you write well, it teaches you why the changes are made—each output includes revision notes, allowing you to truly improve your academic writing skills through iterations. Supports bilingual format validation (GB/T 7714 / APA 7th), suitable for daily teaching research accumulation, project conclusion output, and professional title evaluation sprints.
Full-Process Academic Writing
From topic to final draft, AI-assisted
Description
Why we love this skill
This skill offers one-stop academic writing guidance from topic to final draft, with full AI assistance, incorporating academic meta-theory and rigorous red-line principles to ensure paper quality and academic standards.
"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.
Related Skills
View allResearch Proposal Assistant
Tailored for university faculty and researchers, this AI assistant provides comprehensive guidance in writing humanities and social science research proposals, covering the entire process from topic generation to outcome planning. Whether you need to brainstorm a topic from scratch or optimize a specific section of your proposal, this tool offers expert-level guidance and support. This assistant combines expert experience with a strategy of 'example guidance + writing theory integration' to help you efficiently produce high-quality proposals. You receive targeted analysis of research hotspots in your discipline, topic refinement suggestions, and—based on your research direction and project type—generate a rigorous background, in-depth literature review, and insightful research value statement. In the research content design phase, the assistant helps you define the research subject, build a logically clear research framework, and recommend innovative research ideas and methods. It also helps you distill key points and difficulties, set clear research objectives, and plan a detailed research schedule and feasibility analysis, ensuring your proposal is rigorous and well-structured. Additionally, you can use this tool to deeply explore the innovative aspects of your topic in terms of academic ideas, viewpoints, and research methods, and systematically plan multiple forms of expected outcomes, their applications, and social benefits. Finally, all content is integrated with one click to generate a complete, logically rigorous proposal that meets submission standards, helping you increase your success rate.
ResearchAcademic Paper Writing v4.1
A full-process academic paper writing system that combines the Five Sources model with the AFP 3.1 three-layer architecture. Other AI tools help you "write" a paper; this one helps you "plug" every hole that could get it rejected—from one vague idea to a complete submission package in a single run through seven modules, with an anti-hallucination gate, archive-code resume, and four-core review. [10-second value] One sentence of an idea → a submittable, complete paper package. Real sources are enforced throughout, every citation is verifiable, and you can resume across sessions right where you left off. [Trigger phrases] write a paper / literature review / research method design / how to write the discussion / paper polishing / abstract & keywords / submission package [Seven modules, all fully executable instructions] Phase 1 Topic & Introduction → Phase 2 Literature Review → Phase 3 Research Method Design → Phase 4 Discussion → Phase 5 Conclusion → Phase 6 Abstract & Keywords → Phase 7 Full-Text Integration & Submission Package. Phase 0 entry routes A–G map one-to-one to the seven modules, with an R option to restore your last progress via an archive code or archived document. [v4.1 upgrades] 1. Evidence-chain gate (hard constraint): a material registry (M1/M2 numbering) + four citation elements (author / year / title / verifiable locator) + three-color marking (✅ user-supplied / ⚠️ to verify / 🚫 prohibited). If the material library is empty, the system outputs only an outline and search queries and refuses to generate body text with citations; generating references from memory or fabricating volume, issue, or page numbers is forbidden. 2. Archive-code protocol: each module ends with a structured archive code that can be saved as a YouMind document. In your next session, simply reference it with @ to resume without re-requesting already locked information. 3. Reproducible scoring: the C core anchors all dimensions to behavioral standards scored at 4/6/8/10 with stated rationale; the ratchet mechanism only moves scores upward, never downward. 4. Four-discipline configuration library (1A Humanities & Arts / 1B Social Sciences / 2A Science & Engineering / 2B Agriculture, Medicine & Life Sciences), with automatic switching of theory libraries, method toolboxes, and disciplinary norms; Category 2B runs ethics review checkpoints at Phases 0, 3, and 7. 5. Three-paradigm routing (quantitative / qualitative / theoretical): literature review narrative strategies and research method design follow different paths. 6. Anti-cliché checklist and prohibitions: discussion sections using phrases like "limited time and energy" or "pending further research," conclusions introducing new data or literature, and abstracts containing claims unsupported by the body text are all sent back by the B core. 7. Adaptivity: user profile (beginner / intermediate / proficient) + paper type (journal / thesis / conference / course) + pacing mode (default / fast-forward / slow-motion) + multi-task isolation. 8. Submission package & compliance: seven consistency checks, a six-link logic chain, reference formatting (GB/T 7714 / APA 7 / Vancouver / IEEE), ethics approval number, data availability statement, generative AI use disclosure draft, and cover letter draft. [How to use] Tell the system: your discipline, target journal / paper type / word count, and which stage you're at. The system advances module by module, pausing after each one to deliver the section, review report, scorecard, and archive code, then waits for your confirmation before continuing. [Responsibility boundaries] The system handles sources 1–4 (structure, material organization, style, integration); source 5, human calibration, is yours: academic judgment, fact-checking, and innovation decisions. All ⚠️-marked citations and data must be verified by you item by item before submission; this skill does not promise any acceptance or pass outcome.
Teaching Paper Architect
From teaching research accumulation to CSSCI/SSCI/SCI — making every teaching paper stand up to peer review. This is not a tool that writes your paper for you, but a paper architect that understands educational academic norms. It knows that IMRaD is not just four letters but a rigorous argument logic; that a literature review is not a list of references but a precise positioning of research gaps; that effect sizes are more convincing to reviewers than p-values. Seven-stage full-process coverage: Topic Focus (Innovation Three-Question Check) → Literature Review (Three-Level Coding + Funnel Writing) → Research Design (Quantitative/Qualitative/Mixed Approach Decision) → Data Analysis (Statistical Method Decision Tree) → Discussion Construction (Contribution Self-Check Matrix) → Language Refinement (AI Removal + Language Elevation + Revision Notes) → Journal Adaptation (Matching Matrix + Rejection Risk Pre-Reinforcement). Built-in Triple-Core Adversarial Engine: The Academic Writer handles output, the Language Elevation Officer polishes, and the Academic Gatekeeper has veto power—are the references real? Is the data reliable? Is the argument grounded in evidence? Does the contribution match the target journal level? Five dimensions are audited item by item; if any fail, it is sent back for rework. It doesn't just help you write well, it teaches you why the changes are made—each output includes revision notes, allowing you to truly improve your academic writing skills through iterations. Supports bilingual format validation (GB/T 7714 / APA 7th), suitable for daily teaching research accumulation, project conclusion output, and professional title evaluation sprints.
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