Acad Paper System v3.0 (五源×AFP)
7-stage acad writing with real lit & 4-core
Why we love this skill
With its Five-Source×AFP architecture and four-core review mechanism, this skill breaks paper writing into six rigorous modules from topic to conclusion, making it a powerful research tool for grad students and young faculty.
Description
Integrating the 五源 model and AFP architecture, this is a full-process academic writing system. From vague observations to complete papers, it covers the entire academic writing workflow in one go. ✅ Seven core modules: Topic introduction → Literature review → Research methods → Discussion section → Conclusion writing → Abstract and keywords (new in v3.1) → Full integration. Each module has 五源 constraints (structure, material, style, integration, calibration). ✅ Phase-based diagnosis: The system automatically identifies your current writing stage (starting from scratch, already have a topic, already have a review, etc.) and jumps to the corresponding module, no need to go through the whole process. ✅ Anti-hallucination firewall: It requires real literature/data input, and the B Core has veto power to refuse generating any 'hallucinated content' not supported by materials, ensuring academic rigor. ✅ Cross-disciplinary adaptation: It automatically identifies three research paradigms—quantitative, qualitative, and speculative—and switches corresponding writing strategies (e.g., quantitative emphasizes 'variable conflict,' qualitative emphasizes 'failure of situational explanatory power'). Suitable for all disciplines including humanities, social sciences, STEM, and medical sciences. Simply tell the system 'my current stage' and 'my discipline area' to start. The system will guide you to provide materials step by step (literature, data, research ideas). After completing each module, it automatically generates usable chapter content, and finally integrates everything into a complete paper with one click. User feedback: 40% increase in acceptance rate for C 刊/SCI submissions. v3.1 major upgrade: New Phase 6 abstract and keywords generation module, achieving a true full-process loop from topic selection to final draft to abstract.
Related Skills
View all
LearnOffer Toolkit
An AI-powered job search system built from 10 years of experience at a Silicon Valley tech giant, embedding real recruitment insights and job-seeking methodologies into AI. Offer Toolkit | AI Job Assistant From 'finding your dream role' to 'landing the Offer,' the entire job search process is broken down into three intelligent modules: ① JD Decoder Deeply analyze job descriptions to generate a personalized Offer Strategy Report: - Whether it's worth applying - Role fit assessment - Core strengths and skill gaps - Interview focus and predicted high-probability questions ② Resume Builder Transform your experience from 'job descriptions' into 'impact stories recognized by recruiters': - Automatically structure your experience - Optimize project descriptions and quantify achievements - Generate ATS-friendly, high-quality resumes - Supports 11+ professional print-grade templates ③ Behavioral Story Library Mine your real experiences to build reusable interview story assets: - Extract key projects and growth experiences - Automatically convert to STAR Framework - Build a personal Behavioral Interview Story Bank - Efficiently handle 'Tell me about a time...' questions Whether you're debating 'should I apply for this role,' want to 'optimize your resume,' need to 'analyze a JD,' or prepare for your next Behavioral Interview, Offer Toolkit automatically identifies your needs and routes you to the most suitable AI module. Keywords: Job Search | Offer | Career | Job Hunt | JD | Job Description | Resume | CV | Behavioral Interview | STAR | Tell me about a time | Interview Preparation
LearnRapid Industry Understanding
📋 Usage Guide This Skill is an industry research engine based on McKinsey methodology, using the eight-dimension framework from Xiao Jing's "How to Quickly Understand an Industry". Tell it an industry name, and it produces a systematic research report. —————————————————————————————— 🚀 Basic Usage Just tell me the industry you want to research—the more specific, the better: a. "Analyze the solid-state battery industry" b. "Look at the humanoid robot supply chain from an entrepreneurial perspective" c. "Is the solar industry still investable now?" You can optionally provide three details (if missing, I'll use defaults): 1. Industry name: be specific, e.g., "perovskite solar" instead of "new energy"—required; 2. Goal: investment / career / entrepreneurship / competitive analysis / education, default: investment; 3. Region: China market / global / US / Southeast Asia..., default: China market; —————————————————————————————— ⚙️ What it does automatically? The entire process has 4 stages: 1. Multi-round web searches for market size/growth/penetration rate, supply chain, competitive landscape, moat evidence, policy, valuation—every conclusion has a source and timestamp, never fabricated; 2. Lifecycle positioning: use penetration rate to determine if the industry is in introduction/growth/maturity/decline—different stages have completely different research focuses; 3. Eight-dimension deep dive: business model → market size → moat (forced deep dive into dynamic trends) → competitive landscape (forced scoring on each of Porter's Five Forces) → valuation → PEST → business cycle; 4. Contrarian check: distinguish market priced-in consensus from overlooked real issues, and provide decision recommendations; —————————————————————————————— 📊 What it outputs? A professional research report in Markdown format, structured as: 1. ⚡ 30-second verdict — stage / core profit logic / biggest opportunity / biggest risk / one-sentence conclusion; 2. Research object and boundary definition; 3. Lifecycle positioning (with penetration rate data); 4. Eight-dimension analysis (moat includes dynamic trend table, Porter's Five Forces scoring table); 5. Contrarian check; 6. Conclusion and decision recommendations; 7. Key risk list; 8. Data sources and time notes; —————————————————————————————— 🔑 Two Core Highlights 1. Forced deep dive on moat: not just the type of barrier, but must answer "has it widened or narrowed in the past 2-3 years?" using market share/gross margin/pricing power data; 2. Porter's Five Forces scored individually: all five forces scored to avoid shortcuts, determining who has the strongest bargaining power now and whether the landscape is favorable or deteriorating for leaders; —————————————————————————————— ⏱️ Time Approximately 2-4 minutes, due to multiple rounds of search + dimension-by-dimension analysis + report writing —————————————————————————————— 🧩 Subsequent Extensions After the report is generated, you can continue with two specialized analyses (requires manual confirmation, won't run automatically): 1. "Unchain to find bottlenecks": identify physical bottlenecks in the supply chain that can't be bypassed when trends scale, locking in true beneficiary targets; 2. "DCF valuation": run a full discounted cash flow model for a specific company within the industry; —————————————————————————————— ▶️ Want to try? Just tell me an industry name, e.g., "Take a look at the AI agent industry from an entrepreneurial perspective" or "What's the situation with the hydrogen energy supply chain?"
LearnQuickly Understand a Company
Enter a company name or stock ticker. Using Charlie Munger's latticework of mental models and a value investing perspective, this Skill conducts in-depth investment research analysis on the stock. It automatically connects to the internet to mine deep information, enforcing a search-before-judgment approach, cross-referencing dual sources, and annotating definitions and sources. It performs deep analysis according to a seven-dimension value investing framework, provides three-scenario valuations and a 2x2 quality/price decision matrix, and produces an executable "Value Investing Deep Analysis" report.
Acad Paper System v3.0 (五源×AFP)
7-stage acad writing with real lit & 4-core
Why we love this skill
With its Five-Source×AFP architecture and four-core review mechanism, this skill breaks paper writing into six rigorous modules from topic to conclusion, making it a powerful research tool for grad students and young faculty.
Description
Integrating the 五源 model and AFP architecture, this is a full-process academic writing system. From vague observations to complete papers, it covers the entire academic writing workflow in one go. ✅ Seven core modules: Topic introduction → Literature review → Research methods → Discussion section → Conclusion writing → Abstract and keywords (new in v3.1) → Full integration. Each module has 五源 constraints (structure, material, style, integration, calibration). ✅ Phase-based diagnosis: The system automatically identifies your current writing stage (starting from scratch, already have a topic, already have a review, etc.) and jumps to the corresponding module, no need to go through the whole process. ✅ Anti-hallucination firewall: It requires real literature/data input, and the B Core has veto power to refuse generating any 'hallucinated content' not supported by materials, ensuring academic rigor. ✅ Cross-disciplinary adaptation: It automatically identifies three research paradigms—quantitative, qualitative, and speculative—and switches corresponding writing strategies (e.g., quantitative emphasizes 'variable conflict,' qualitative emphasizes 'failure of situational explanatory power'). Suitable for all disciplines including humanities, social sciences, STEM, and medical sciences. Simply tell the system 'my current stage' and 'my discipline area' to start. The system will guide you to provide materials step by step (literature, data, research ideas). After completing each module, it automatically generates usable chapter content, and finally integrates everything into a complete paper with one click. User feedback: 40% increase in acceptance rate for C 刊/SCI submissions. v3.1 major upgrade: New Phase 6 abstract and keywords generation module, achieving a true full-process loop from topic selection to final draft to abstract.
Related Skills
View allLearnOffer Toolkit
An AI-powered job search system built from 10 years of experience at a Silicon Valley tech giant, embedding real recruitment insights and job-seeking methodologies into AI. Offer Toolkit | AI Job Assistant From 'finding your dream role' to 'landing the Offer,' the entire job search process is broken down into three intelligent modules: ① JD Decoder Deeply analyze job descriptions to generate a personalized Offer Strategy Report: - Whether it's worth applying - Role fit assessment - Core strengths and skill gaps - Interview focus and predicted high-probability questions ② Resume Builder Transform your experience from 'job descriptions' into 'impact stories recognized by recruiters': - Automatically structure your experience - Optimize project descriptions and quantify achievements - Generate ATS-friendly, high-quality resumes - Supports 11+ professional print-grade templates ③ Behavioral Story Library Mine your real experiences to build reusable interview story assets: - Extract key projects and growth experiences - Automatically convert to STAR Framework - Build a personal Behavioral Interview Story Bank - Efficiently handle 'Tell me about a time...' questions Whether you're debating 'should I apply for this role,' want to 'optimize your resume,' need to 'analyze a JD,' or prepare for your next Behavioral Interview, Offer Toolkit automatically identifies your needs and routes you to the most suitable AI module. Keywords: Job Search | Offer | Career | Job Hunt | JD | Job Description | Resume | CV | Behavioral Interview | STAR | Tell me about a time | Interview Preparation
LearnRapid Industry Understanding
📋 Usage Guide This Skill is an industry research engine based on McKinsey methodology, using the eight-dimension framework from Xiao Jing's "How to Quickly Understand an Industry". Tell it an industry name, and it produces a systematic research report. —————————————————————————————— 🚀 Basic Usage Just tell me the industry you want to research—the more specific, the better: a. "Analyze the solid-state battery industry" b. "Look at the humanoid robot supply chain from an entrepreneurial perspective" c. "Is the solar industry still investable now?" You can optionally provide three details (if missing, I'll use defaults): 1. Industry name: be specific, e.g., "perovskite solar" instead of "new energy"—required; 2. Goal: investment / career / entrepreneurship / competitive analysis / education, default: investment; 3. Region: China market / global / US / Southeast Asia..., default: China market; —————————————————————————————— ⚙️ What it does automatically? The entire process has 4 stages: 1. Multi-round web searches for market size/growth/penetration rate, supply chain, competitive landscape, moat evidence, policy, valuation—every conclusion has a source and timestamp, never fabricated; 2. Lifecycle positioning: use penetration rate to determine if the industry is in introduction/growth/maturity/decline—different stages have completely different research focuses; 3. Eight-dimension deep dive: business model → market size → moat (forced deep dive into dynamic trends) → competitive landscape (forced scoring on each of Porter's Five Forces) → valuation → PEST → business cycle; 4. Contrarian check: distinguish market priced-in consensus from overlooked real issues, and provide decision recommendations; —————————————————————————————— 📊 What it outputs? A professional research report in Markdown format, structured as: 1. ⚡ 30-second verdict — stage / core profit logic / biggest opportunity / biggest risk / one-sentence conclusion; 2. Research object and boundary definition; 3. Lifecycle positioning (with penetration rate data); 4. Eight-dimension analysis (moat includes dynamic trend table, Porter's Five Forces scoring table); 5. Contrarian check; 6. Conclusion and decision recommendations; 7. Key risk list; 8. Data sources and time notes; —————————————————————————————— 🔑 Two Core Highlights 1. Forced deep dive on moat: not just the type of barrier, but must answer "has it widened or narrowed in the past 2-3 years?" using market share/gross margin/pricing power data; 2. Porter's Five Forces scored individually: all five forces scored to avoid shortcuts, determining who has the strongest bargaining power now and whether the landscape is favorable or deteriorating for leaders; —————————————————————————————— ⏱️ Time Approximately 2-4 minutes, due to multiple rounds of search + dimension-by-dimension analysis + report writing —————————————————————————————— 🧩 Subsequent Extensions After the report is generated, you can continue with two specialized analyses (requires manual confirmation, won't run automatically): 1. "Unchain to find bottlenecks": identify physical bottlenecks in the supply chain that can't be bypassed when trends scale, locking in true beneficiary targets; 2. "DCF valuation": run a full discounted cash flow model for a specific company within the industry; —————————————————————————————— ▶️ Want to try? Just tell me an industry name, e.g., "Take a look at the AI agent industry from an entrepreneurial perspective" or "What's the situation with the hydrogen energy supply chain?"
LearnQuickly Understand a Company
Enter a company name or stock ticker. Using Charlie Munger's latticework of mental models and a value investing perspective, this Skill conducts in-depth investment research analysis on the stock. It automatically connects to the internet to mine deep information, enforcing a search-before-judgment approach, cross-referencing dual sources, and annotating definitions and sources. It performs deep analysis according to a seven-dimension value investing framework, provides three-scenario valuations and a 2x2 quality/price decision matrix, and produces an executable "Value Investing Deep Analysis" report.
Find your next favorite skill
Explore more curated AI skills for research, creation, and everyday work.