bashOS

A terminal-first AI runtime. Claude slash commands routed through a LangGraph kernel, running on your Claude Code OAuth — for all things software development and information systems.

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The terminal is the core access point: one REPL (and one-shot CLI) reaches every capability. Commands are markdown specs in .claude/commands/ — the exact files Claude Code loads as project slash commands — and the bashOS kernel routes those same files through AI orchestration loops. One spec, two runtimes.

Quickstart

./bin/bashos                 # first run bootstraps .venv, then drops into the REPL

bashos ▸ /sh find files over 100MB modified this week
bashos ▸ /script rotate logs in /var/log, keep 7 days     # drafted, shellcheck-verified, repaired
bashos ▸ /sys why is this machine slow                    # read-only agent probes the real machine
bashos ▸ count unique IPs in access.log                   # no slash → kernel classifies → /pipe
bashos ▸ !git status                                      # raw passthrough to your real shell

One-shot, from any terminal or script:

bashos run /explain "rsync -avz --delete src/ host:/dst"
bashos run -n /script backup my dotfiles     # -n dry-run: routing + rendered prompt, no model call
bashos run -v /sh list open ports            # -v prints the kernel trace
bashos list                                  # command table
bashos doctor                                # auth + environment checks

Auth — Claude Code OAuth first

bashOS needs no API key. Backends, in preference order:

Force one with BASHOS_BACKEND=claude-code|api; pick a model with BASHOS_MODEL or -m (default claude-opus-5). bashos doctor shows what was detected. Copy .env.example to .env for persistent settings.

Commands

Every one of these also works as a plain slash command inside Claude Code when you open this repo — same file, no duplication.

Architecture

 terminal (REPL / CLI · typer + rich + prompt-toolkit)
    │
    ▼
 kernel — LangGraph state machine
    input ─▶ parse ─┬─▶ dispatch ──▶ prompt  (one model call)            ┐
                    │       ▲   └──▶ refine  (draft→shellcheck→repair)   ├─▶ respond
                    │       │   └──▶ react   (agent loop, read-only)     ┘
                    └─▶ classify  (bare english → best command)
    │
    ▼
 model runtime — Claude Code OAuth (Agent SDK) ▸ or ANTHROPIC_API_KEY fallback
    │
    ▼
 userland — .claude/commands/*.md  (shared with Claude Code)

The full design — layer contracts, loop semantics, tool policy, extension guide — is in docs/HARNESS.md. The long-range vision (an image-based Linux appliance with the agent kernel as a first-class OS service) is the bashOS reference architecture; HARNESS.md maps this runtime onto its layers.

Extending

Add a command by dropping one markdown file into .claude/commands/:

---
description: what it does
argument-hint: <what to pass>
bashos:
  loop: prompt        # or refine | react
---
Prompt body with $ARGUMENTS.

No registration, no code — it appears in bashos list and in Claude Code immediately.

Safety model

• /sh and friends generate commands; they never execute them.
• The react loop (/sys, /debug) runs under an explicit read-only tool policy: file reads plus an allowlist of diagnostic probes; write, edit, and network tools are denied; every tool action streams to your terminal live.
• /script output is verified by shellcheck when installed, and labeled unverified when not.
• Only ! lines execute anything by your intent — and that's your own shell.

Services (Docker)

LangChain and LangGraph run in-process as libraries — the terminal needs no services. The optional compose stack adds infrastructure around the terminal:

docker compose up -d           # phoenix + langgraph-dev
docker compose run bashos      # the terminal itself, containerized

Container auth: interactive claude login isn't possible in a container, so set CLAUDE_CODE_OAUTH_TOKEN (mint with claude setup-token) or ANTHROPIC_API_KEY in .env. Already running a Phoenix elsewhere? Remap host ports via BASHOS_PHOENIX_*_PORT, or point PHOENIX_COLLECTOR_ENDPOINT at it — full guide in docs/SERVICES.md.

Local tracing without containers: pip install -e ".[trace]", run Phoenix anywhere, and set PHOENIX_COLLECTOR_ENDPOINT. On the claude-code backend, spans cover the kernel and loop structure; use the api backend for token-level LLM telemetry.

Development

python3 -m venv .venv && .venv/bin/pip install -e ".[dev]"
.venv/bin/pytest -q            # offline: fake model, no auth needed

Roadmap

• Session memory: LangGraph checkpointer so loops share conversational state
• An --exec confirm-then-run mode for /sh
• Streaming token output in the REPL
• More loops: plan-execute, multi-draft panel w/ judge
• More userland: /git, /docker, /net, /db