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Daily Action Command Center

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MMoumou
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A complete personal efficiency and growth system that helps you coordinate the overall situation, conduct deep reflection, and continuously evolve. [Core Functions] Step 1: Morning task breakdown and energy management Based on your fixed time structure (10:00-10:30 clipping/10:30-12:00 morning/14:30-19:30 afternoon), intelligently break down tasks, estimate energy consumption, optimize sequencing, and provide off-screen rest suggestions. Step 2: Clip deep analysis system 5-layer analysis framework: multi-level information deconstruction → critical thinking assessment → knowledge network construction → practice transformation path → information lifecycle management. Automatically control daily clip count (suggested ≤5 articles) to ensure deep understanding. Step 3: Task completion deep review and growth tracking 6 dimensions: three-dimensional quality assessment → success pattern extraction → root cause-oriented improvement → intelligent historical comparison → energy calibration and motivation tracking → intelligent task recommendation. Every task completion is a growth opportunity. Step 4: Evening deep review 6-layer progressive exploration: curiosity root → thinking pattern decoding → value core return → problem of the problem → thinking trap diagnosis → psychological state and tomorrow's seeds. From surface to depth, fully decode a day's growth. Step 5: Periodic data insights Automatically generate reports on Friday/end of month: energy consumption patterns, curiosity evolution, psychological state trends, pitfall statistics, growth milestones, next week/month suggestions. [System Value] Not just a task management tool, but a cognitive upgrade engine + capability growth tracker + thinking pattern decoder. Helps you return from chaos to core, from execution to insight, from completion to evolution.

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Personal Memory System

💡 Core Value Explanation (30-second version) What is this? Personal Memory System is a smart tool that lets AI remember you persistently. No need to reintroduce yourself every conversation, no need to repeatedly explain work style and project background. Just 5 minutes to initialize, and AI will permanently remember who you are, your preferences, and your project status. What problems does it solve? Pain point 1: Repeated introductions wasting time ❌ Every new conversation: "I'm a product manager, working on an AI project, prefer concise style..." ✅ Set once, works forever—AI automatically remembers your full context Pain point 2: Fragmented context scattered everywhere ❌ Preferences in one conversation, projects in another Board, skill stack in yet another place ✅ 10-dimension structured storage, manage all personal context in one place Pain point 3: Recalibrating when switching scenarios ❌ Switch Boards and have to explain everything again, switch AI platforms and start from scratch ✅ Tiered export (L0-L3), migrate to any scenario in 2 minutes Pain point 4: Privacy concerns, afraid to share ❌ Not sure what info to give AI, worry about leaking privacy ✅ 4-level disclosure mechanism—you fully control the information boundary What value does it provide? Value 1: Save time ⏱️ Initial setup: 5-10 minutes Subsequent updates: 1-2 minutes Cross-scenario migration: 2 minutes Cumulative savings: 30+ minutes per week of repeated introductions Value 2: Improve quality 📈 AI fully understands your work style Output automatically matches your preferences Suggestions align with your skill level Result quality improves by 50%+ Value 3: Protect privacy 🔒 4-level disclosure: L0 public → L3 private Automatic anonymization: names, amounts, health info Local storage: full data control Privacy risk reduced by 80%+ Value 4: Continuous accumulation 📚 10-dimensional complete profile Version history traceable Cross-platform migratable Personal AI asset continuously appreciates Who is it for? ✅ Product managers: record work methodology, team structure, project status ✅ Independent developers: maintain skill stack archive, tech preferences ✅ Creators: save aesthetic principles, style rules ✅ Researchers: manage research background, knowledge system If you frequently collaborate with AI, you need this tool. 📸 4 Effect Demonstration Images Image 1: Intelligent extraction from chat history Function: Automatically analyze your chat history, extract key information Value: No manual entry needed, quickly build profile in 5 minutes Display: Chat history on left with highlighted keywords, automatically generated structured info cards on right Image 2: 10-dimension structured profile Function: Complete personal context model covering identity, rules, projects, skills, etc. Value: Manage all info in one place, no more scattered fragments Display: 10-dimension collapsible list, D2 Cognitive OS starred, progress indicator showing 3/10 complete Image 3: 4-level privacy protection Function: Tiered export, from public to private—you decide what to share Value: Different levels for different scenarios, full privacy control Display: L0-L3 card comparison, information density increasing left to right, with lock icons and token counts Image 4: Auto-sync MEMORY Function: PCA full profile ↔ MEMORY.md core summary auto-sync Value: Board Memory always up to date, no manual maintenance needed Display: Blue sync arrow between two documents, labeled "Auto Sync" and "Real-time Update"

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3500
Research

Extract a Book's Value 2.0

A deep-reading expert that helps you absorb knowledge efficiently, it focuses on transforming long books or documents into structured core-value reports. Whether you need to quickly grasp a book's main ideas or pursue systematic deep learning, it accurately analyzes the original content to extract key arguments, methodological frameworks, and inspiring actionable points. This skill offers two custom reading modes: Quick Mode generates concise summaries with mind-map structures, perfect for reviewing key points in a short time; Deep Mode provides detailed reading notes, including in-depth chapter analysis, core insight breakdowns, and notable quote excerpts, helping you build a complete personal knowledge base. It can process uploaded PDF or Word documents as well as directly parse web content, making sure no key details are missed. Beyond high-quality notes, it also turns book theory into immediately actionable recommendations for life or work. Whether you're doing academic research, exploring business, or pursuing personal growth, it becomes your most reliable partner for internalizing knowledge—ensuring every book's value is fully extracted.

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373100

Learning Plan Skill

Turn “I want to learn” into a systematic learning plan you can start today, with clear daily actions. Just provide your learning goal, current level, timeline, available study time, and learning preferences. The Skill will organize priorities around your real situation, identify strengths and gaps, and break your larger goal into verifiable milestones with clear criteria for measuring progress. The plan covers languages, programming, musical instruments, exams, fitness, and other skill-learning scenarios. It includes a prioritized knowledge framework, a phased roadmap, and daily execution templates tailored to weekday and weekend schedules. Each task specifies the learning content, practice method, time commitment, and completion standard. The plan also emphasizes combining input and output, helping you turn what you have “seen and heard” into skills you can actually use. It also organizes resources such as videos, audio, books, and tools according to your learning preferences, and verifies available links online. For challenges such as procrastination, losing motivation after a few days, perfectionism, lack of feedback, or unexpected interruptions, it provides safeguards to help you stay on track. The final deliverables include a Day 1 action checklist, a milestone review checklist, and a complete execution document. After you confirm the plan, it can also generate an offline-accessible HTML check-in tool for recording daily tasks, phase progress, milestones, and learning resources.

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71k

Information

Version
v1
Last updated
Runtime credits
Usage-based
Models
Auto

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