Critical Writing Pipeline
From a vague idea to a rigorous argumentative essay
Description
From a vague idea to a rigorous argumentative essay with verifiable evidence chains — a full-pipeline AI writing system supporting both Chinese and English. Optimized with AFP 3.1: five-step nested architecture, Core B 9-dimension quantified audit, adaptive pacing, ratchet version management, cross-session state persistence, and material verification downgrade strategy.
Related Skills
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WriteJournal Paper Writing Engine
Input your research direction in one sentence, and the AFP step-by-step engine guides you through the entire process. P1 Topic Design — Davis Interesting Theory + Problematization’s Five-Level Topic Selection Method, extracting real problems from phenomena. P2 Introduction Writing — Five-Color Template Analysis Method, breaking down top journal model papers section by section: emotional appeal → knowledge gap → literature positioning → research space → value declaration, with embedded full deconstruction prompts. P3 Literature Review — Structured organization, distinguishing research threads and dialogue objects. P4 Theoretical Framework — Six theory integration templates embedded throughout (complementary, contrast, bridging, hierarchical, evolutionary, general), each containing six paragraphs: introduction → justification → sorting → premise → analysis → conclusion; plus a five-level deep-drill sentence skeleton for single-theory depth. P5 Research Methods — Automatically adapts strategies based on four paths: empirical quantitative, qualitative, speculative, and mixed. P6 Body Writing — 9-3-1 pyramid structure. P7 Conclusion Writing — Three-level conclusion processing (findings → dialogue → extension). P8 Submission Preparation — Eight methods to reduce AI detection rate. P9 Global Assembly — Compiles independent documents from each stage into a complete draft, supports cross-chapter bidirectional backfill, and allows interruption and iterative backtracking at any time. 🎯 Suitable for: Graduate students (master's and PhD) and early-career researchers aiming to submit to Chinese C-journals, core journals, or SSCI, especially those stuck on theoretical framework and introduction writing. ⚙️ Underlying Architecture: Five-Source Model × AFP Step-by-Step Human-Machine Relay Protocol, with heartbeat signals, mandatory stop points, and dual-core auditing.
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.
WriteWriting Terminator MAX
This Skill is designed to provide deep content creators with a complete workflow for writing speculative and argumentative essays, helping users transform vague ideas into well-structured, persuasively argued, and verifiable long-form articles. Whether you are a WeChat public account writer, knowledge blogger, graduate student, commentator, or a writer focused on social observation, cultural criticism, business commentary, or reflections on the AI era, this Skill offers reusable, scalable, and high-quality writing support. It helps you diagnose topics, refine problem consciousness, collect and organize materials, extract high-value insights, and generate high-quality drafts. The core advantage of this Skill lies in its rigorous evidence-chain construction and citation verification mechanism. It not only helps add source-level citations to your writing, but also verifies the accuracy and supporting strength of those citations, ensuring that your arguments are grounded in solid materials. In addition, it can polish the style of your draft, reduce “AI-like traces,” and enhance the depth of reflection and sharpness of expression. You may enter the workflow at any stage according to your current writing progress, including ideation, material collection, insight extraction, draft writing, citation insertion, citation verification, and final polishing. The final output may include the core argument, main text, detailed notes, source list, and citation self-check report, ensuring that your work combines intellectual depth with academic rigor.
Critical Writing Pipeline
From a vague idea to a rigorous argumentative essay
Description
From a vague idea to a rigorous argumentative essay with verifiable evidence chains — a full-pipeline AI writing system supporting both Chinese and English. Optimized with AFP 3.1: five-step nested architecture, Core B 9-dimension quantified audit, adaptive pacing, ratchet version management, cross-session state persistence, and material verification downgrade strategy.
Related Skills
View allWriteJournal Paper Writing Engine
Input your research direction in one sentence, and the AFP step-by-step engine guides you through the entire process. P1 Topic Design — Davis Interesting Theory + Problematization’s Five-Level Topic Selection Method, extracting real problems from phenomena. P2 Introduction Writing — Five-Color Template Analysis Method, breaking down top journal model papers section by section: emotional appeal → knowledge gap → literature positioning → research space → value declaration, with embedded full deconstruction prompts. P3 Literature Review — Structured organization, distinguishing research threads and dialogue objects. P4 Theoretical Framework — Six theory integration templates embedded throughout (complementary, contrast, bridging, hierarchical, evolutionary, general), each containing six paragraphs: introduction → justification → sorting → premise → analysis → conclusion; plus a five-level deep-drill sentence skeleton for single-theory depth. P5 Research Methods — Automatically adapts strategies based on four paths: empirical quantitative, qualitative, speculative, and mixed. P6 Body Writing — 9-3-1 pyramid structure. P7 Conclusion Writing — Three-level conclusion processing (findings → dialogue → extension). P8 Submission Preparation — Eight methods to reduce AI detection rate. P9 Global Assembly — Compiles independent documents from each stage into a complete draft, supports cross-chapter bidirectional backfill, and allows interruption and iterative backtracking at any time. 🎯 Suitable for: Graduate students (master's and PhD) and early-career researchers aiming to submit to Chinese C-journals, core journals, or SSCI, especially those stuck on theoretical framework and introduction writing. ⚙️ Underlying Architecture: Five-Source Model × AFP Step-by-Step Human-Machine Relay Protocol, with heartbeat signals, mandatory stop points, and dual-core auditing.
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.
WriteWriting Terminator MAX
This Skill is designed to provide deep content creators with a complete workflow for writing speculative and argumentative essays, helping users transform vague ideas into well-structured, persuasively argued, and verifiable long-form articles. Whether you are a WeChat public account writer, knowledge blogger, graduate student, commentator, or a writer focused on social observation, cultural criticism, business commentary, or reflections on the AI era, this Skill offers reusable, scalable, and high-quality writing support. It helps you diagnose topics, refine problem consciousness, collect and organize materials, extract high-value insights, and generate high-quality drafts. The core advantage of this Skill lies in its rigorous evidence-chain construction and citation verification mechanism. It not only helps add source-level citations to your writing, but also verifies the accuracy and supporting strength of those citations, ensuring that your arguments are grounded in solid materials. In addition, it can polish the style of your draft, reduce “AI-like traces,” and enhance the depth of reflection and sharpness of expression. You may enter the workflow at any stage according to your current writing progress, including ideation, material collection, insight extraction, draft writing, citation insertion, citation verification, and final polishing. The final output may include the core argument, main text, detailed notes, source list, and citation self-check report, ensuring that your work combines intellectual depth with academic rigor.
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