Rnix

# You know Unix? You already know Rnix.
rnix -i "Analyze the project structure"
rnix strace 1        # See exactly what your agent did
rnix dashboard       # Multi-pane real-time monitoring
rnix gdb 1           # Breakpoints, stepping, context inspection

Design Philosophy

Rnix brings 50 years of proven OS abstractions directly into the world of AI agents. Not a framework. Not a library. A runtime.

Everything is a Process — Every agent is a first-class process with its own PID, state machine, and resource table. Use ps to list, kill to terminate, strace to trace — manage agents the same way you manage system processes. Processes can be paused, resumed, suspended, and restarted from checkpoints.

Everything is a File — LLMs, filesystem, shell, memory, web search, LSP code intelligence, MCP tools — all unified as VFS devices, accessed through Open/Read/Write/Close. Adding a new capability is just mounting a new device.

Observability Built In — Not a logging layer bolted on after the fact. strace shows every syscall, gdb provides breakpoints and stepping, dashboard offers multi-pane monitoring with process tree, timeline, context heatmap, and LLM conversation replay.

Orchestration is Process Management — Supervisor trees auto-restart crashed processes. Compose DAGs declare dependencies between agents. Budget Pools manage token allocation. The Intent system decomposes high-level goals into sub-task DAGs. These are OS-level primitives, not application-layer wrappers.

Quick Start

# Install
go install github.com/rnixai/rnix/cmd/rnix@latest

# Initialize configuration
rnix init

# Run your first agent
rnix -i "Analyze the project structure"

# Trace syscalls
rnix strace 1

# Real-time dashboard
rnix dashboard

Core Concepts

Architecture

┌─────────────────────────────────────────────────────────┐
│  CLI & AgentShell                                       │
│  rnix -i / strace / gdb / ps / compose / dashboard      │
├─────────────────────────────────────────────────────────┤
│  Agent + Skill Definitions                              │
│  agent.yaml + instructions.md + SKILL.md                │
├─────────────────────────────────────────────────────────┤
│  Microkernel                                            │
│  Process Model / VFS / Context Mgmt / IPC / 50+ Syscalls│
├─────────────────────────────────────────────────────────┤
│  Driver Layer                                           │
│  /dev/llm/* · /dev/fs · /dev/shell · /dev/memory/*      │
│  /dev/web · /dev/lsp · /dev/tasks · /dev/tty · /dev/cron│
├─────────────────────────────────────────────────────────┤
│  Host OS + Multi-LLM Providers                          │
│  Claude · Gemini · Qwen · Anthropic SDK · OpenAI-compat │
└─────────────────────────────────────────────────────────┘

Highlights

• 7 LLM Drivers — Claude CLI / Cursor CLI / Qwen CLI / Anthropic SDK / Gemini / OpenAI Official / OpenAI-compatible (Ollama, Groq, DeepSeek, etc.)
• 14 VFS Devices — LLM, filesystem, shell, memory (commit/recall/profile), web, LSP, tasks, TTY, cron, ProcFS, MCP
• Agent Memory — Persistent cross-session knowledge with security scanning and async writeback
• 50+ Syscalls — Stable ABI covering process, context, VFS, IPC, signal, capability, and supervisor
• Interactive Debugging — gdb-style debugger + time-travel event navigation + fork-based continuation (not deterministic replay)
• Multi-Pane Dashboard — Process tree, timeline, heatmap, LLM conversation replay, debug mode
• Token Economy — Budget pools (compose quota engine + per-process runtime budgets), post-hoc SLA contract evaluation feeding agent reputation scoring, skill synergy matrix
• Adaptive Security — Behavioral monitoring, anomaly detection, and auto-suspension

License

MIT — see LICENSE.

Full documentation at docs.rnix.ai.