# Personal Knowledge Companion / Life View Dashboard## What It IsA persistent knowledge layer across all agents that:1. Maps what -topher knows, what's being learned, and where the gaps are2. **Proactively tells him about those gaps** before he realizes he needed them3. Groups knowledge by life domain (School/Work/Play)Not a passive archive. An active learning companion that watches activity, builds a model of knowledge edges, and surfaces learning opportunities without being asked.## Core Components### 1. memory-wiki (OpenClaw Plugin)Built into OpenClaw. Plain `.md` files, Obsidian-compatible.- **Vault layout:** `entities/`, `concepts/`, `syntheses/`, `sources/`, `reports/`- **Structured claims** with evidence, confidence, contradictions- **Per-agent vault mode** — separate wiki per agent, isolated knowledge domains- **Bridge mode** — pulls from active memory plugin- Built-in dashboards: open questions, contradictions, low-confidence claims, stale pages, relationship graphs- Tools: `wiki_search`, `wiki_get`, `wiki_apply`- Docs: `https://docs.openclaw.ai/plugins/memory-wiki`**Gap detection is the key feature:** The wiki tracks topics covered, topics stale, topics never explored. Reports surface automatically.### 2. Domain Separation- 🏫 **School** — 2890 bot (robotics team)- 🏭 **Work** — PSB bots (brewery ops)- 🎮 **Play** — crash-bot / HHS-Hackers crewEach domain has its own vault that can cross-reference the others.### 4. Professor Agent (The Teacher) — Scales to AnyoneSame knowledge graph, different personal layers per person.- Person entities: confidence scores, scale preferences, learning style, delivery channel- When Kyle wants CEH prep → professor creates entity/kyle.md, assesses current knowledge, builds a learning path- When Bruno needs PathPlanner → professor creates entity/bruno.md, starts from his mechanical strength, fills gaps- Each person's learning path compounds into the shared knowledge graph for the next person- Access control maps to existing Discord structure (HHS-Hackers, 2890, DMs)### 4. Playful Visual Layer (Inspired by Claw Empire)- Claw Empire: pixel-art office simulator, agents as employees in a virtual company- Adapted for personal life context instead of a coding shop- Could visualize domains, agent status, knowledge flow- Not full Claw Empire — just the playfulness and visual mapping## Related Concepts- **Karpathy's LLM Wiki pattern** — raw/ notes → AI synthesizes → wiki pages with auto-links- **AgentWiki** (agentwiki.org) — shared knowledge base for AI agents, JSON-RPC API- **Obsidian** — same plain-Markdown vault format, compatible- **SamurAIGPT/llm-wiki-agent** — personal knowledge base that builds itself- **kytmanov/obsidian-llm-wiki-local** — 100% local, Ollama-powered## Claw Empire Reference- GitHub: `GreenSheep01201/claw-empire`- "Command Your AI Agent Empire from the CEO Desk"- Pixel-art office metaphor, git worktrees, agent meetings and deliverables- Not a coding shop fit — over-engineered for -topher's use case- Inspiration for visual/playful layer, not the architecture## Life View Project FileSee: `projects/life-view-dashboard.md`## The ThreadNeeds its own Discord channel: `#personal-knowledge-companion` or `#life-view`## StatusConcept stage. Not built yet. Needs:- [x] Discord channel (#personal-knowledge-companion)- [ ] memory-wiki configuration- [ ] Professor agent (replaces librarian)- [ ] Gap detection logic (driven by wiki claims + confidence scores)- [ ] Learning path delivery (Discord training threads)- [ ] Knowledge graph visualization (Obsidian)## Why It MattersCurrent agents are mostly command-and-reply. They don't do research, self-direct, or maintain persistent context between sessions. They feel like fancy autocomplete, not assistants.This gives them continuity, memory, and proactivity — and gives -topher a way to see his whole digital life at a glance and understand where his knowledge gaps are.