create-agentfs
v0.3.0
Published
Scaffold your Obsidian vault as a filesystem-based OS for AI agents
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AgentFS
One config. Every AI agent. Persistent memory.
AgentFS turns your Obsidian vault into a unified operating system for AI agents. Define your identity, memory, and security rules once — compile to native formats for Claude Code, Cursor, OpenClaw, and others.
The Problem: Context Fragmentation
AI agents today are silos. Claude Code needs CLAUDE.md, Cursor needs .cursor/rules/, and OpenClaw needs .openclaw/. You maintain the same rules, identity, and context in three different places. Agents don't share memory. They don't respect the same security policies. They start from zero every session.
Most importantly: Agents lack a "Persistent State." They can't "pause" and "resume" tasks across sessions or hand off context to other agents without major manual intervention.
The Solution: AgentFS (The Agent OS Infrastructure)
AgentFS introduces a Kernel Space (.agentos/) — a single source of truth for who you are, what you know, and what's off-limits. One command compiles it into native configs for every agent you use.
- Persistent State: Agents can maintain state across toolchains and sessions.
- Inter-Agent Sync: A shared filesystem where different agents exchange context without API overhead.
- Secure Context Isolation: Deterministic security rules that agents actually respect across environments.
AgentFS isn't just a config generator; it's the missing infrastructure layer for autonomous AI agents. While others build the agents, AgentFS builds the environment they live in.
.agentos/ CLAUDE.md
manifest.yaml agentfs .claude/settings.json
init.d/ --------> .cursor/rules/*.mdc
memory/ compile .openclaw/
security/ AGENT-MAP.mdInstall
# Install globally from npm
npm install -g create-agentfs
# Verify
agentfs --versionOr use without installing:
npx create-agentfs my-vaultUpdate
# Update to latest version
npm install -g create-agentfs@latest
# Upgrade existing vault to new version
agentfs upgrade --dir ~/my-vaultUninstall
npm uninstall -g create-agentfsQuick Start
agentfs init my-vault
cd my-vault
agentfs compileThat's it. Your vault now has a kernel, and every supported agent gets native configuration.
For detailed setup with interactive onboarding, modules, and profiles — see the Quick Start Guide.
Two Ways to Use AgentFS
Persistent Agents (full power)
Long-lived agents like Cowork, OpenClaw, or Cursor in background mode get the complete experience: memory accumulates between sessions, cron jobs consolidate knowledge, the agent "grows" over time.
agentfs compile # compile kernel → native configs
agentfs memory consolidate # snapshot session memory
agentfs sync # sync memory back to kernelThe agent reads semantic.md on boot, writes episodic memories, runs consolidation at session end. Full read-write cycle.
Session Agents (instant context)
Short-lived sessions (Claude Code in terminal, one-off Cursor tasks) use AgentFS as a smart context loader. The agent starts knowing who you are, your stack, your preferences, your security rules — no warm-up questions.
npx create-agentfs my-project # scaffold once
agentfs compile # compile once
# now every Claude Code session in this directory starts with full contextThe agent consumes context but doesn't write back. That's fine — even read-only access to your identity and memory saves 2-3 rounds of "what framework do you use?" per session.
Give Your Agent the Prompt
After running agentfs compile, paste this into your agent's first message (or add it to your workflow):
Read the file AGENT-MAP.md in the project root. It contains the vault structure,
your identity, memory, security rules, and operating instructions. Follow them.
If you see .agentos/memory/semantic.md — read it first. It contains facts and
preferences that persist across sessions. If you learn something new about me
or my project, append it to semantic.md in the correct format:
FACT: [active] description
PREF: [active] description
AVOID: description of what NOT to do
Never modify files in .agentos/init.d/, .agentos/security/, or .agentos/cron.d/
unless I explicitly ask you to "update the kernel".For a comprehensive AI agent manual, see docs/ai-manual.md.
CLI Commands
# Scaffold & Setup
agentfs init [dir] # scaffold vault (same as npx create-agentfs)
agentfs onboard # interactive interview → identity + memory
agentfs migrate # migrate existing vault to AgentFS structure
# Compile
agentfs compile [agent] # compile kernel → native configs (all or specific agent)
agentfs compile --dry-run # preview changes without writing
# Memory
agentfs memory show # display semantic memory
agentfs memory add "fact" # add a fact to long-term memory
agentfs memory consolidate # snapshot current session
# Security & Secrets
agentfs security mode <mode> # enforce | complain | disabled
agentfs security add <module> # add domain-specific security module
agentfs secret set <key> # manage SOPS/age encrypted secrets
# Maintenance
agentfs doctor # vault health check
agentfs triage # classify Inbox/ files
agentfs sync # bidirectional memory sync
agentfs cron run <job> # manually trigger a cron jobAll commands support --json, --config, and --output json flags for non-interactive use by AI agents.
Key Concepts
Kernel Space (.agentos/) — single source of truth: manifest, identity, memory, security, cron jobs. Never edited by agents directly.
Compile Pipeline — translates kernel into native formats: CLAUDE.md + .claude/settings.json for Claude, .cursor/rules/agentfs-global.mdc for Cursor, .openclaw/ for OpenClaw.
Memory System — based on Tulving's taxonomy: semantic (facts, always loaded), episodic (events, lazy), procedural (skills, lazy). Confidence scoring with decay.
Security — AppArmor-style policies in policy.yaml. Compiles to real deny rules for Claude Code, advisory text for agents without enforcement.
Three Profiles — personal (solo), company (team with RBAC), shared (multi-user collaborative).
For the full architecture deep-dive, see docs/architecture.md.
Documentation
| Document | For | |----------|-----| | Quick Start Guide | Humans — setup in 5 minutes | | AI Agent Manual | AI agents — operating instructions | | Architecture | Deep-dive into the full design | | Internals | Memory system, boot sequence, security model, FHS mapping | | Contributing | Adding compilers, security modules, commit conventions |
Roadmap
| Quarter | Milestone |
|---------|-----------|
| Q2 2026 | Stable core (v0.2), 3+ example vaults, auto-compile (file watcher + git hooks), first community module |
| Q3 2026 | AgentFS Cloud MVP (hosted vault, sync, team profiles), MemPalace integration |
| Q4 2026 | Module Marketplace beta, Security Marketplace (agentfs-security-{domain}), Obsidian companion plugin |
| Q1 2027 | Multi-vault sync, Product Hunt launch |
Strategic Integrations
AgentFS is an infrastructure layer — its value grows with every integration.
MemPalace — Long-term Agent Memory
github.com/milla-jovovich/mempalace
The highest-scoring open source memory system for AI: 96.6% on LongMemEval with zero cloud calls. AgentFS defines where and when to store memory (.agentos/memory/), MemPalace solves how to search and compress it. AAAK encoding provides 30x context compression — agents get the same knowledge at ~170 tokens instead of 650K. Direct API cost savings for users.
Cognithor — Local-first AI OS
Cognithor builds a local operating system for AI agents (executor layer). AgentFS occupies the kernel layer: manifest, security policy, and memory standards. The "Kernel (AgentFS) + Executor (Cognithor)" stack delivers fully autonomous agents with zero cloud dependency.
Plugin System — Community-driven Extensibility
The agentfs-module-{name} architecture enables community-built modules for specific domains: agentfs-module-github, agentfs-module-slack, agentfs-security-hipaa, agentfs-security-fintech. Each module is a reusable package of rules, integrations, and security policies — creating network effects as the ecosystem grows.
License
MIT
