Multi-Source Writing Assistant
Integrate materials into admin documents
Description
Why we love this skill
Designed for university admins, this skill integrates complex materials, intelligently generates standardized documents, offers multi-version output and rigorous data verification, greatly boosting efficiency.
Designed specifically for higher education administrative staff. It integrates scattered reporting materials from various units and formats—documents, spreadsheets, PDFs, PPTs, images, web links—into well-structured, accurate, and formally written documents. Supports six types of texts: administrative summaries, special topic summaries, activity summaries, project applications/conclusion reports, typical case compilations, and information briefs. Built-in data conflict verification, source tracing annotation, language normalization, omission reminders, and multi-version output (detailed/simplified/key points). Materials can be added at any time throughout the process. AI processes silently—users only need to submit materials and receive the completed document.
Related Skills
View all
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.
Counselor Log, Summary & Cases
A comprehensive work assistant for college counselors, supporting natural language work recording, automatic classification and archiving, generating monthly/semester summaries and performance reports, extracting educational cases, and generating data charts. With a hybrid input mode, the AI automatically recognizes intent and guides users through the complete workflow loop: record → summary → case.
Research Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
Multi-Source Writing Assistant
Integrate materials into admin documents
Description
Why we love this skill
Designed for university admins, this skill integrates complex materials, intelligently generates standardized documents, offers multi-version output and rigorous data verification, greatly boosting efficiency.
Designed specifically for higher education administrative staff. It integrates scattered reporting materials from various units and formats—documents, spreadsheets, PDFs, PPTs, images, web links—into well-structured, accurate, and formally written documents. Supports six types of texts: administrative summaries, special topic summaries, activity summaries, project applications/conclusion reports, typical case compilations, and information briefs. Built-in data conflict verification, source tracing annotation, language normalization, omission reminders, and multi-version output (detailed/simplified/key points). Materials can be added at any time throughout the process. AI processes silently—users only need to submit materials and receive the completed document.
Related Skills
View allResearchAcademic 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.
Counselor Log, Summary & Cases
A comprehensive work assistant for college counselors, supporting natural language work recording, automatic classification and archiving, generating monthly/semester summaries and performance reports, extracting educational cases, and generating data charts. With a hybrid input mode, the AI automatically recognizes intent and guides users through the complete workflow loop: record → summary → case.
Research Report Generator
📝 Value in one sentence: Enter a topic or upload materials, and AI handles the entire process from organizing sources to drafting. 🔍 Core features: Smart source integration: Upload multiple documents and AI automatically extracts key viewpoints, critical data, and representative cases, while removing duplicates and flagging conflicts. Automatic outline generation: Based on the topic or source content, it creates a logically clear and well-structured article outline. One-click draft writing: Generates content section by section according to the outline, with every data point and case study source-tagged and traceable. Five writing styles: Supports formal reports, WeChat articles, Xiaohongshu notes, academic papers, and business briefings. Transparent citations: Every figure and viewpoint is marked with its source—no fabrication or invention. Automated content workflow: Source parsing → viewpoint extraction → outline generation → writing in five styles. 🎯 Use cases: 📊 Industry research: Enter "Humanoid Robot Industry 2026" to generate a draft analysis report with data and case studies. 📝 Content creation: Upload 3 related articles to combine into an in-depth WeChat article. 📚 Academic writing: Upload multiple paper abstracts to create a literature review draft. 📋 Competitor analysis: Upload several competitor documents to instantly generate a comparative analysis report. 🧠 Personal learning: Enter a new-domain topic to quickly generate a knowledge overview. 💼 Business decisions: Input business data and background information to produce a decision brief for the CEO. 👩💼 Who it's for: Researchers, analysts, content creators, product managers, students, and consultants—anyone who needs to quickly produce high-quality first drafts.
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