papercomputeco/stereOS

Description: A Linux based operating system hardened and purpose built for AI agents

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Summary Information

Updated 2 minutes ago
Added to GitGenius on June 22nd, 2026
Created on February 4th, 2026
Open Issues & Pull Requests: 7 (+0)
Number of forks: 30
Total Stargazers: 485 (+0)
Total Subscribers: 4 (+0)

Issue Activity (beta)

Open issues: 5
New in 7 days: 0
Closed in 7 days: 0
Avg open age: 99 days
Stale 30+ days: 5
Stale 90+ days: 5

Recent activity

Opened in 7 days: 0
Closed in 7 days: 0
Comments in 7 days: 0
Events in 7 days: 0

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Most active issues this week

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Repository Insights (GitGenius)

Median issue/PR response: 1.7 hours
Mean response time: 22.0 hours
90th percentile: 3.1 days
Tracked items: 4

Most active contributors

Detailed Description

stereOS is a Linux-based operating system purpose-built for AI agents, developed by Paper Computer Co. and written primarily in Nix. The project takes a hardened, minimal approach to creating machine images called mixtapes that bundle a stripped-down Linux system with specific AI agent harnesses. The repository is classified by GitGenius across multiple domains including stereo vision, depth estimation, image processing, computer vision, camera calibration, 3D reconstruction, machine learning, and neural networks, though the core focus remains on providing a secure operating system foundation for autonomous agents.

The stereOS architecture centers on a minimal system design with orchestration daemons that manage agent lifecycle and provide control plane functionality. The system defines two primary user contexts: an admin user and group for administrative operations with a home directory at /home/admin, and an agent user and group that runs with restricted privileges in /home/agent/workspace. Two key daemons handle system operations: stereosd serves as the stereOS system daemon, while agentd manages agent lifecycle and operations. These components work together to create a controlled environment where AI agents can operate with appropriate security boundaries.

The project uses a mixtape distribution model where each mixtape represents a complete machine image bundled with a specific AI agent binary and its dependencies. The initial mixtape offering is opencode-mixtape, which includes the opencode binary and requires either an ANTHROPIC_API_KEY or OPENAI_API_KEY. Each mixtape appends its agent package to stereos.agent.extraPackages, which adds the binary to the agent user's restricted PATH. Development variants of mixtapes include profiles/dev.nix for local SSH key injection during development.

stereOS supports multiple output formats to accommodate different deployment scenarios. The canonical artifact is a raw EFI image suitable for Apple Virt Framework booting. QCOW2 format is derived from the raw image via qemu-img convert for QEMU and KVM environments. Kernel artifacts including bzImage, initrd, cmdline, and init files enable direct-kernel booting that bypasses UEFI and GRUB. The distribution system, implemented via lib/dist.nix:mkDist, assembles all formats into a publish-ready directory with zstd compression at level 19 and generates a mixtape.toml manifest containing SHA-256 checksums and file sizes for every artifact.

The system declares two custom NixOS options: stereos.ssh.authorizedKeys accepts a list of SSH public keys for admin and agent users to facilitate development access, while stereos.agent.extraPackages allows adding packages to the agent's restricted PATH. External dependencies include agentd and stereosd as flake inputs providing NixOS modules and overlays, nixpkgs at version 26.05 for base packages, and dagger from the Dagger project for CI engine functionality.

According to GitGenius activity tracking, the repository shows responsive issue and pull request handling with a median response latency of 1.7 hours across tracked items and a mean latency of 22.0 hours. The most active contributors tracked are bdougie with 6 events, jpmcb with 4 events, and elliottminns with 1 event. The repository shares contributors with continuedev/continue, home-assistant/core, and modelcontextprotocol/inspector, indicating cross-project collaboration within the AI agent and smart home ecosystems.

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