Framework-Driven Speechwriter
Framework-Driven Speechwriter
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Description
Provide a framework (the central line of reasoning) and several versions of raw material. Following the strict rule of “align the structure before fitting the content,” this Skill breaks the material into usable talking points, places them under the right framework nodes, and rewrites and expands them in a conversational style to match the target duration—producing a detailed, word-for-word speech you can deliver on stage. Public, objective data can be verified online and cited; private material (your own results, lists, cases, and images) is handled honestly, with gaps clearly identified and never fabricated. A “Pending Items Checklist” is included at the end. The Skill works across domains and adapts its style and structure to your input.
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Lesson Prep Script V1.0
Helps instructors/knowledge IPs directly turn lesson preparation topics into a ready-to-use 30-minute spoken-word script—just pick it up and read, not secondary prompts. What it solves Traditional lesson preparation requires instructors to go through "ideation → break into modules → write script → mark pacing → design interactions", which is time-consuming and easy to miss details. This Skill compresses this process into a 5-step interaction. Instructors only need to provide the topic and key knowledge points, and the rest is automated. Core capabilities ① Five-step structured interaction: Select lesson type → Receive preparation content → Deep analysis with option presentation → Ask for style preference → Directly generate a complete spoken-word script. Each step waits for user confirmation before proceeding. ② CXO three-dimensional teaching verification: Each module is annotated with teaching dimensions — C (Content/Knowledge), X (Experience/Practice), O (Objective/Output), ensuring full coverage throughout. ③ Spoken-word script template: Each segment follows the framework of Hook → Key Point → Structure → Call to Action. The structure supports four modes: reason, method, situation/reaction, and chronological order. ④ Complete output includes: 7 modules totaling approximately 7,900 words of spoken text + tone cues (【Pause 2 seconds】【Emphasis】) + audience interaction instructions + CXO paragraph annotations + full statistics. ⑤ Seven-dimensional quality check: Word count deviation / Spoken style / Template completeness / CXO coverage / Logical coherence / Pacing / Reusability — each dimension is checked, and if any fails, it is corrected and regenerated.
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.
Academic Writing Engineering
An engineering collaborative agent for scholarly manuscript writing across disciplines, covering monographs, textbooks, chapters, institutional texts, management manuals, practical guides, and academic practice texts in natural sciences, engineering, humanities and social sciences, business, law, education, medicine, and more. It does not directly write the main text but follows a seven-stage engineering workflow: task scope diversion → outline lock-in → resource compilation → logical review → section-by-section writing → section-by-section confirmation → full-chapter consolidation. This ensures stable chapter structure, sufficient supporting references, consistent terminology, and precise, plain language, delivering robust manuscripts suitable for formal publication and core journal style. Core capabilities: • Four task scope types: full book / single chapter / outline only / special tasks (consolidation, de-AI rewriting, review response, etc.) • Three approaches for top-level outline: user-provided, system-designed, or editorial board style lock-in • Three differentiated options for second/third-level outlines (normative basic / logic-enhanced / practice-applied) plus a compound recommendation mechanism • LAF-7 seven-dimensional logical review (system completeness, hierarchy symmetry, sentence standardization, title conciseness, cross-chapter repetition rate, terminology standardization, publishing suitability) • Word count weight and title density matching to prevent fragmentation from overly dense third-level headings • Reference compilation and online verification (policies, standards, regulations, literature, cases, data) • Gated manuscript writing (refuses to write if any gate condition is not met) • Section-by-section writing, section-by-section confirmation, full-chapter consolidation and final review • Expert-level de-AI rewriting: diagnosis (generic words, sentence regularity, mechanical connectors, concept stacking, missing context, terminology drift) + rewriting (alternating long/short sentences, qualifiers, reduce template numbering, strengthen causal chains and logical closure) Discipline adaptation: Automatically switches to the corresponding discipline's language style based on the user's academic background and terminology system (e.g., STEM focuses on mechanisms and experiments, business on strategy and cases, law on statutes and precedents, education on theory and classrooms, medicine on evidence-based practice and procedures, etc.) without imposing a fixed disciplinary framework. Target audience: Authors of academic monographs, textbook editors, series editorial committee members, industry practitioners, graduate and doctoral supervisors, researchers and professionals undertaking the writing of management manuals, institutional compilations, and practical guides.
Information
- Version
- v3
- Last updated
- Runtime credits
- Usage-based
- Models
- Auto
