Pre-submission Quality Check v2.0
Description
Comprehensive pre-submission quality check system for journal papers. Features a six-dimensional parallel review (structure, logic, methods, language, citations, journal alignment) plus four enhanced modules: journal profile analysis, AIGC risk recheck, abstract smart rewrite, and desk-reject risk radar. Simulates a senior reviewer's perspective, outputting a structured issue list, severity grading, submission readiness score, and desk-reject probability estimate.
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Journal Pre-review Expert V7.0
Top Journal Submission Pre-review Expert V7.0 is a full-process pre-review Skill for social sciences and humanities scholars. It simulates the perspective of senior reviewers at Nature/Science/ASR/AJS-level journals, driven by a dual-core engine (Reviewer Butcher + Polishing Craftsman) across six phases. V7.0 core upgrades: · Governance layer: unified dashboard + step mode (default/fast-forward/slow-motion) + ratchet version management + mid-join logic · All 15 quick commands implemented (/express /jump /benchmark /ethics-scan /cover-letter /polish /abstract /checklist /audit /resume /skip /rerun /export /persona /lang) · Cross-phase vulnerability tracking table: tracks from Phase 2 to Phase 5 with status closure · 6 virtual reviewer personas (methodology hawk, theoretical purist, contextualist, ethics reviewer, etc.), each with 4-5 typical criticisms, automatically activating 3-4 based on research type · Full language pair support: Chinese→English, English→English, Chinese→Chinese, with Chinglish terminator engine covering 7 categories of high-frequency errors · Benchmark paper five-dimensional comparison + no-benchmark degradation path · New AI usage transparency check and citation quality deep audit Applicable scenarios: PhD students/early-career faculty pre-submission self-check, advisors guiding students to revise manuscripts, research group submission strategy discussions. Supports full-process guidance for Chinese native speakers submitting in English.
Journal Submission Refinement Architect v2.0 (Advanced Version)
A dynamic, adaptable review, restructuring, and step-by-step revision system for any target academic journal. It accurately diagnoses manuscript publication suitability using a J-AFP five-dimensional quantitative scoring system (intent alignment, theoretical contribution, methodological standardization, result conversion, and format compliance). Employing a dual-core engine (Critic + Mentor) model, it helps authors bridge the gap between "self-indulgent writing" and "standardized works conforming to review logic." It supports a fully engineered workflow, from journal profiling and title reshaping to logical pressure application, table of contents finalization, and step-by-step revision.
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.
Pre-submission Quality Check v2.0
Description
Comprehensive pre-submission quality check system for journal papers. Features a six-dimensional parallel review (structure, logic, methods, language, citations, journal alignment) plus four enhanced modules: journal profile analysis, AIGC risk recheck, abstract smart rewrite, and desk-reject risk radar. Simulates a senior reviewer's perspective, outputting a structured issue list, severity grading, submission readiness score, and desk-reject probability estimate.
Related Skills
View allJournal Pre-review Expert V7.0
Top Journal Submission Pre-review Expert V7.0 is a full-process pre-review Skill for social sciences and humanities scholars. It simulates the perspective of senior reviewers at Nature/Science/ASR/AJS-level journals, driven by a dual-core engine (Reviewer Butcher + Polishing Craftsman) across six phases. V7.0 core upgrades: · Governance layer: unified dashboard + step mode (default/fast-forward/slow-motion) + ratchet version management + mid-join logic · All 15 quick commands implemented (/express /jump /benchmark /ethics-scan /cover-letter /polish /abstract /checklist /audit /resume /skip /rerun /export /persona /lang) · Cross-phase vulnerability tracking table: tracks from Phase 2 to Phase 5 with status closure · 6 virtual reviewer personas (methodology hawk, theoretical purist, contextualist, ethics reviewer, etc.), each with 4-5 typical criticisms, automatically activating 3-4 based on research type · Full language pair support: Chinese→English, English→English, Chinese→Chinese, with Chinglish terminator engine covering 7 categories of high-frequency errors · Benchmark paper five-dimensional comparison + no-benchmark degradation path · New AI usage transparency check and citation quality deep audit Applicable scenarios: PhD students/early-career faculty pre-submission self-check, advisors guiding students to revise manuscripts, research group submission strategy discussions. Supports full-process guidance for Chinese native speakers submitting in English.
Journal Submission Refinement Architect v2.0 (Advanced Version)
A dynamic, adaptable review, restructuring, and step-by-step revision system for any target academic journal. It accurately diagnoses manuscript publication suitability using a J-AFP five-dimensional quantitative scoring system (intent alignment, theoretical contribution, methodological standardization, result conversion, and format compliance). Employing a dual-core engine (Critic + Mentor) model, it helps authors bridge the gap between "self-indulgent writing" and "standardized works conforming to review logic." It supports a fully engineered workflow, from journal profiling and title reshaping to logical pressure application, table of contents finalization, and step-by-step revision.
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.
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