add shared brain vault skill
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# Agent-Hub Skill Deployment Notes
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Use when making the Shared Brain Vault workflow available to cross-agent tools through the AGENTS/agent-hub repository.
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## Target layout
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Copy the complete skill directory, not only `SKILL.md`:
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```text
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/var/lib/hermes/workspace/agent-hub/.agents/skills/shared-brain-vault/
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SKILL.md
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references/
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scripts/
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```
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Source of the active Hermes-installed skill is usually:
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```text
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/var/lib/hermes/.hermes/skills/knowledge-management/shared-brain-vault/
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```
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## Safe deployment sequence
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```bash
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cd /var/lib/hermes/workspace/agent-hub
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mkdir -p .agents/skills/shared-brain-vault
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cp -a /var/lib/hermes/.hermes/skills/knowledge-management/shared-brain-vault/. \
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.agents/skills/shared-brain-vault/
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chmod +x .agents/skills/shared-brain-vault/scripts/*.py 2>/dev/null || true
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```
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Then stage only the shared-brain skill files so unrelated dirty Agent-Hub work is not mixed into the commit:
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```bash
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git add .agents/skills/shared-brain-vault
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git diff --cached --stat
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git diff --cached --name-status
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git commit -m "add shared brain vault skill"
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```
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## Verification
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Run the vault link audit against the actual vault path:
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```bash
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python3 .agents/skills/shared-brain-vault/scripts/audit-wikilinks.py /var/lib/hermes/m3ta-brain
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```
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If Agent-Hub has its repo check script, run it too:
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```bash
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./scripts/check-agent-hub.sh
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```
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Before claiming success, confirm the committed files and current status:
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```bash
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git status --short
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git log -1 --oneline
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```
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If `git remote -v` prints nothing, do not claim a push happened; report that the local commit exists and that no remote is configured.
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## Pitfalls
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- Do not assume a skill installed in `~/.hermes/skills/` is present in Agent-Hub. Check `.agents/skills/<name>/` separately.
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- Do not copy only `SKILL.md`; supporting `references/` and `scripts/` carry reusable detail and verification helpers.
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- Do not mix pre-existing Agent-Hub changes into the skill commit. Stage the skill path explicitly.
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- Keep the active Hermes-installed copy and Agent-Hub copy in sync when patching durable workflow guidance.
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# Knowledge Management Landscape Research (2026-06-29)
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Research conducted when designing the m3ta-brain vault. Condensed for future reference.
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## 1. Karpathy LLM Wiki Pattern (April 2026)
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Andrej Karpathy published a "pattern gist" for LLM-maintained personal knowledge bases.
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**Core idea**: Instead of RAG (re-derive from raw docs every query), the LLM builds and maintains a **persistent, compounding wiki** — cross-references already there, contradictions already flagged, synthesis already done.
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**Three layers**:
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- Raw sources (`raw/`) — original articles, papers, transcripts
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- LLM Wiki (`wiki/`) — entity pages, concepts, comparisons, synthesis (LLM writes ALL of this)
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- Schema (`CLAUDE.md` / `AGENTS.md`) — tells the LLM how the wiki is structured
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**Key quote**: *"Obsidian is the IDE, the LLM is the programmer, the wiki is the codebase."*
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**What we adopted**: AGENTS.md as schema, structured directories, LLM-maintained notes, Obsidian as viewer.
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**What we extended**: Added project state, decisions, people, learnings — not just research concepts.
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Source: https://gist.github.com/karpathy/442a6bf555914893e9891c11519de94f
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## 2. Daniel Miessler PAI / Personal AI Infrastructure (v5.0, May 2026)
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PAI ("Life Operating System") is the most comprehensive personal AI system design.
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**7 Architecture Components**: Intelligence, Context (Memory), Personality, Tools, Security, Orchestration, Interface.
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**Key insight — Scaffolding > Model**: "When Kai gives me a result I don't want, it's almost never because Claude is dumb. It's because my scaffolding didn't provide the right context."
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**Memory System v7.6 — three tiers by PURPOSE, not chronology**:
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- `MEMORY/WORK/` — active task tracking, ISAs (Ideal State Artifacts)
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- `MEMORY/KNOWLEDGE/` — typed graph (People, Companies, Ideas, Research)
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- `MEMORY/LEARNING/` — meta-patterns, signals, failures, corrections
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- `MEMORY/RELATIONSHIP/` — DA-Principal relationship notes
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- `MEMORY/OBSERVABILITY/` — every tool call, hook firing, satisfaction signal
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**Signal capture**: Every interaction generates signals — explicit ratings, implicit sentiment, failure captures (ratings 1-3 trigger full-context saves).
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**Principles adopted**: "Text over opaque storage" (if you can't `cat` it, don't store it), filesystem as context (no RAG), memory structured by purpose.
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**What we adopted**: Purpose-based directory structure (Telos/Preferences/Projects/Decisions/People/Learning), write policy with review gates, learning patterns and corrections as first-class citizens.
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**What we skipped**: ISA/ISC verification system, Pulse dashboard, hooks, voice — too Claude-Code-specific.
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Source: https://danielmiessler.com/blog/personal-ai-infrastructure, github.com/danielmiessler/PAI
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## 3. qmd — Query Markup Documents (Tobi Lütke, 26K stars)
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Fully local CLI search engine for markdown. BM25 + Vector + LLM Reranking, all on-device.
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**Three search modes**:
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- `qmd search` — BM25 keyword (fast, no LLM)
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- `qmd vsearch` — Vector semantic (embeddings)
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- `qmd query` — Hybrid: query expansion + parallel retrieval + RRF fusion + LLM reranking
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**Key features**: Collections (named indexed directories), Context (human descriptions attached to paths), MCP server mode, multiple output formats (`--json`, `--md`, `--files`).
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**Local models** (~2GB total): embeddinggemma-300M, qwen3-reranker-0.6b, qmd-query-expansion-1.7B.
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**Our plan**: Install as retrieval layer over m3ta-brain + tech wiki + nemoti wiki. Collections: `brain`, `tech-wiki`, `nemoti-wiki`. Not yet installed (requires Node.js/Bun on server).
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Source: github.com/tobi/qmd, npm: `@tobilu/qmd`
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## 4. Obsidian MCP Integration Landscape
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Multiple MCP servers connect AI agents to Obsidian vaults:
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| Server | Transport | Key Feature |
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| Local REST API plugin | HTTP (localhost:27124) | Built-in MCP at `/mcp/`, the foundation |
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| yanxue06/obsidian-mcp | stdio/HTTP | Graph-aware: backlinks, multi-hop, safe rename |
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| lstpsche/obsidian-mcp (Rust) | stdio/HTTP | Single binary, filesystem-native, works without Obsidian running |
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| Vasallo94/obsidian-mcp-server | stdio | Explicit Hermes support documented |
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| cyanheads/obsidian-mcp-server | stdio/HTTP | 14 tools, surgical section editing, read/write path scoping |
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**Key limitation for us**: MCP over localhost requires Obsidian on same machine as agent. Hermes runs server-side, Obsidian runs on Sascha's desktop. So Git-sync is Phase 1, MCP is Phase 2 (optional).
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## 5. Shared Memory Platforms
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| Platform | Architecture | Key Differentiator |
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| Open Second Brain | Obsidian-native, Hermes-first | Nightly "dream" passes, preferences with confidence bands |
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| Agentkeep | Git-backed markdown vault | Content-hash compare-and-swap, safe two-driver editing |
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| Noosphere | PostgreSQL + Redis | REST API, scoped access, Obsidian export/import |
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**What we adopted from these**: Git as the sync/merge mechanism (Agentkeep), draft-then-review pattern for sensitive notes (Open Second Brain), plain markdown as the substrate (all three).
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## Design Decisions Summary
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| Decision | Chosen | Rejected | Rationale |
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| Sync mechanism | Git (Gitea) | Syncthing | Versioned, auditable, conflict diffs, Gitea already exists |
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| Link format | Standard Markdown links (`[text](relative/path.md)`) | Obsidian-only `[[wikilinks]]` | Works in both Gitea and Obsidian; current vault rules supersede the initial design note |
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| Language | German + EN tech | English only | Match how Sascha communicates |
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| Agent instructions | `AGENTS.md` | Agent-specific config | Multi-agent compatible (Pi, OpenCode, Claude Code, Hermes) |
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| Memory model | Purpose-based dirs | Chronological | Inspired by PAI v7.6 (WORK/KNOWLEDGE/LEARNING pattern) |
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| Retrieval | qmd (planned) | RAG/black-box | Local, hybrid search, no cloud dependency |
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