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Bryan Helmkamp 77d0cd265f Improve README features section and add CONTRIBUTING.md
Add emoji to feature bullets, update tagline, add human-in-the-loop
feature, highlight traceability in git checkpointing, remove system
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CLAUDE.md.

Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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.cargo Disable empty doc-tests and add terse test output alias 2026-02-23 10:57:26 -05:00
.claude Add 2026-03-10 changelog and update docs for new CLI commands 2026-03-10 14:25:42 -04:00
.config Fix Daytona e2e test failures and improve test reliability 2026-03-08 18:51:43 -04:00
.github Use GitHub-hosted runners for release workflow 2026-03-10 14:23:05 -04:00
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AGENTS.md Add arc init command to initialize a new arc project 2026-03-10 13:00:36 -04:00
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CLAUDE.md Move CLAUDE.md to AGENTS.md with symlink for compatibility 2026-03-09 13:02:06 -04:00
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package.json Move packages/ to lib/packages/ and update all references 2026-03-09 13:13:56 -04:00
README.md Improve README features section and add CONTRIBUTING.md 2026-03-10 15:16:03 -04:00

Arc

The open source software factory for expert engineers

AI coding agents are powerful but unpredictable. You either babysit every step or review a 50-file diff you don't trust. Arc gives you a middle path: define the process as a graph, let agents execute it, and intervene only where it matters.

License: MIT docs


Key Features

  • 🔀 Deterministic workflow graphs -- Define pipelines in Graphviz DOT with branching, loops, parallelism, and human gates. Diffable, reviewable, version-controlled.
  • 🙋 Human-in-the-loop -- Approval gates pause for human decisions. Steer running agents mid-turn. Interview steps collect structured input. You stay in control without babysitting.
  • 🎨 Multi-model routing -- Route each node to the right model and provider with CSS-like stylesheets. Cheap models for boilerplate, frontier models for hard reasoning, with automatic provider fallback.
  • ☁️ Cloud sandboxes -- Run agents in isolated Daytona cloud VMs with snapshot-based setup, network controls, and automatic cleanup.
  • 🔌 SSH access and preview links -- Shell into running sandboxes with arc ssh and expose ports with arc preview for live debugging while workflows run.
  • 🌲 Git checkpointing -- Every stage commits code changes and execution metadata to Git branches. Inspect diffs, revert mistakes, resume interrupted runs, or trace exactly how and why each change was made.
  • 📊 Automatic retros -- Each run generates a retrospective with cost, duration, files touched, and an LLM-written narrative rating smoothness and flagging friction points.
  • Comprehensive API -- arc serve exposes a full REST API with SSE event streaming and a React web UI. Run workflows programmatically, build integrations, or operate Arc as a service.
  • 🦀 Single binary, no runtime -- One compiled Rust executable with zero dependencies. No Python, no Node, no Docker required to get started.
  • ⚖️ Open source (MIT) -- Full source code, no vendor lock-in. Self-host, fork, or extend to fit your workflow.

Read the full documentation for details.


Quick Start

Install

Download the latest release for your platform:

# macOS (Apple Silicon)
curl -fsSL https://github.com/brynary/arc/releases/latest/download/arc-aarch64-apple-darwin.tar.gz | tar xz
sudo mv arc /usr/local/bin/

# Linux (x86_64)
curl -fsSL https://github.com/brynary/arc/releases/latest/download/arc-x86_64-unknown-linux-gnu.tar.gz | tar xz
sudo mv arc /usr/local/bin/

Or download directly from GitHub Releases.

Build from source

Requires Rust (latest stable):

git clone https://github.com/brynary/arc.git
cd arc
cargo build --release
# Binary is at ./target/release/arc

Run the setup wizard

arc install

Initialize your project

cd my-repo/
arc init

Run your first workflow

arc run hello

Example Workflow

A plan-approve-implement workflow where a human reviews the plan before the agent writes code:

digraph PlanImplement {
    graph [
        goal="Plan, approve, implement, and simplify a change"
        model_stylesheet="
            *        { llm_model: claude-haiku-4-5; reasoning_effort: low; }
            .coding  { llm_model: claude-sonnet-4-5; reasoning_effort: high; }
        "
    ]

    start [shape=Mdiamond, label="Start"]
    exit  [shape=Msquare, label="Exit"]

    plan      [label="Plan", prompt="Analyze the goal and codebase. Write a step-by-step plan.", reasoning_effort="high"]
    approve   [shape=hexagon, label="Approve Plan"]
    implement [label="Implement", class="coding", prompt="Read plan.md and implement every step."]
    simplify  [label="Simplify", class="coding", prompt="Review the changes for clarity and correctness."]

    start -> plan -> approve
    approve -> implement [label="[A] Approve"]
    approve -> plan      [label="[R] Revise"]
    implement -> simplify -> exit
}

Agents run as multi-turn LLM sessions with tool access. Human gates (hexagon) pause for approval. The stylesheet routes planning to a cheap model and coding to a frontier model. See the DOT language reference for the full syntax.


Help or Feedback


Contributing

See CONTRIBUTING.md for build instructions and development workflow.


License

Arc is licensed under the MIT License.