Skill: daowuu/personal-os-framework (version 0.3.0)

--- name: personal-os-framework description: Build a second brain that AI can understand and maintain. This framework provides decision logging with follow-up tracking, periodic review generation, routing rules for information classification, task management with ownership and status, execution tracking for started tasks, decision support monitoring, and memory distillation for converting raw notes into structured knowledge. Use when you want AI to collaborate proactively by reading and updating your personal operating system through ongoing conversation. metadata: openclaw: prePublishChecks: - clawhub-release-auditor homepage: https://clawhub.ai --- # Personal OS Framework A methodology and toolset for building a second brain that AI can understand and maintain. ## The Core Idea The human does the work. The AI records it. The AI reads the records. The AI understands the human. The AI helps more effectively. This is not a standalone tool. It requires an AI collaborator that reads, updates, and maintains the system through ongoing conversation. ## What This Framework Provides ### Decision Log Record important decisions with rationale and follow-up actions. Every significant judgment gets a permanent record. ### Review Operator Generate daily, weekly, and monthly reviews from project state. Surface stale projects, identify blockers, generate follow-up actions. ### Routing Assistant Classify incoming information by type and destination. Every piece of information has a canonical home. ### Task Layer Define what a task looks like. Track status, ownership, and aging. ### Execution Layer Record when work begins. Identify started tasks that have gone stale. ### Decision Support Layer Monitor decision follow-ups and task health. Proactive monitoring without manual recounting. ### Memory Distiller Convert accumulated raw captures into structured knowledge. Raw notes become permanent knowledge after a 7-day aging period. ## Workflow ``` Capture → Structure → Execute → Reflect ``` Information enters the system. It gets classified. Work happens. Regular reviews keep everything current. ## How It Works ``` Human does something ↓ AI observes or is told ↓ AI records in personal-os ↓ AI reads personal-os ↓ AI understands the human ↓ AI provides better help ``` ## Key Principles The AI does not wait for commands. The AI reads the system, understands the human, and acts proactively. Reviews keep the system alive. Without regular reviews, the system becomes stale. Decisions are the most valuable content. Log them with context. ## Files Every personal-os has these core files: - `STATE.md` — current project states - `TODO.md` — active tasks - `DECISIONS.md` — decision log - `PENDING-DECISIONS.md` — blocked decisions - `HEARTBEAT-LOG.md` — system activity log ## For AI Collaborators Read the personal-os after each conversation. Update relevant files. The system stays current because the AI keeps it current. ## When to Use This Framework Use when: - You want to build a personal OS that AI can understand and maintain - You want decisions logged with context - You want regular reviews that surface stale projects - You want clear routing rules for information - You want AI to collaborate proactively Do not use when: - The work is too small to benefit from structure - There is no commitment to regular reviews - The human is not willing to work with an AI collaborator ## Success Metrics The framework is working when: - You can answer "what was the reasoning behind X decision?" - Reviews surface real stale items - Decisions have follow-up actions that get done - The AI understands your context - The system stays current without constant maintenance


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