Maintainer of this skill?
Automated security scan — not a certification.
by razzant
Ouroboros — self-creating AI agent. Born Feb 16, 2026.
# Add to your Claude Code skills
git clone https://github.com/razzant/ouroborosLast scanned: 7/25/2026
{
"issues": [],
"status": "PASSED",
"scannedAt": "2026-07-25T06:17:17.512Z",
"npmAuditRan": true,
"pipAuditRan": false,
"promptInjectionRan": true
}See how ouroboros compares with popular alternatives.
ouroboros is an open-source ai agents skill for AI coding assistants such as Claude Code, Codex CLI, and ChatGPT, built by razzant. Ouroboros — self-creating AI agent. Born Feb 16, 2026. It has 1,574 GitHub stars.
Yes. ouroboros passed SkillsLLM's automated security scan — a dependency vulnerability audit plus prompt-injection heuristics — with no high-severity issues. You can read the full report in the Security Report section on this page.
Clone the repository with "git clone https://github.com/razzant/ouroboros" and add it to your Claude Code skills directory (see the Installation section above).
ouroboros is primarily written in Python. It is open-source under razzant on GitHub, so you can review or fork the full source.
Yes. SkillsLLM lists many other AI Agents skills you can browse and compare side by side. Open the AI Agents category from the badge at the top of this page, or use the Related Skills and comparison links further down to weigh ouroboros against similar tools.
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⚠️ Third-Party Software Notice
This skill is third-party open-source software developed and hosted independently on GitHub. SkillsLLM is an informational directory and does not control or maintain the underlying repository.
Any security checks, ratings, or warnings displayed by SkillsLLM are automated and limited in scope. They do not constitute a security certification or guarantee that the software is safe, error-free, or free from malicious code, vulnerabilities, compromised dependencies, or prompt-injection risks.
Review the source code, permissions, dependencies, and configuration before installing or running any third-party skill. Use is at your own risk. To the maximum extent permitted by applicable law, SkillsLLM is not liable for losses arising from third-party software.
Automated security scan — not a certification.
Ouroboros is an open-source, general-purpose AI agent whose identity, durable memory, and history continue across tasks and restarts. It works on external projects, coordinates a live swarm of specialist agents, and can rewrite the implementation it runs on, including its code, architecture, prompts, tools, and dependencies. Reflection can also change how it understands itself without severing that continuity.
It runs as a native desktop app or through a headless CLI. The runtime keeps its repository, durable memory, history, and interface on your machine, while model inference can use remote APIs you configure or a local GGUF model.
Ouroboros sends no telemetry by default, and the official project operates no usage or crash-report collection. A deployment can connect its own monitoring tools to its local records and choose what they receive; local history stays on the machine either way. Requests through OpenRouter carry the app name, which OpenRouter uses for its public app statistics.
Changing Ouroboros? Coding agents and people must read CONTRIBUTING.md before editing. It defines the required project context, verification, and separate-agent review flow.
Just want to use Ouroboros? Click the download for your platform below. You do not need to clone this repository or install Python or uv.
Desktop downloads bundle CPython 3.10.22 and SQLite 3.53.1. In-app Update replaces the repository and its packages, not that interpreter: install the app again to get this runtime.
Android (experimental, Magisk-rooted ARM64): Installation and qualification guide. Its USB setup requires Python and adb.
Files named SHA256SUMS, release-evidence.json, release-smoke-*.json, and sbom-*.cdx.json are verification evidence, not additional installers.
Ouroboros-<version>.dmg.Ouroboros.app onto the Applications shortcut.Ouroboros folder and run Ouroboros.exe..deb above and run sudo apt install ./ouroboros_*_amd64.deb..rpm above and run sudo dnf install ./ouroboros-*.x86_64.rpm. RED OS 8 has its own red80 package.chmod +x Ouroboros-*.AppImage, and run it. Git must already be installed.To run tasks, choose a connected Codex account as the Main model source, configure a supported remote provider API key, or use a local GGUF model. Claude Code and Cursor subscriptions can run delegated coding and review; they are not Main model sources. The first-run wizard guides model access, review policy, and budget setup.
The desktop packages already contain an optional CLI installer. On macOS, after copying the app to Applications, double-click Install CLI.command in the mounted DMG. On Linux use ./Ouroboros/bin/install-ouroboros-cli; on Windows use Ouroboros\bin\install-ouroboros-cli.cmd. These installers create a user-local ouroboros command without sudo. You do not need Python or uv.
Ouroboros bundles Claudexor as its local execution layer for delegated coding and hosted-agent review. Ouroboros owns the task, memory, review, and final integration, while Claudexor runs the selected connected coding harness and returns durable execution evidence. Explore Claudexor.
The technical report, Ouroboros: A Self-Developing Frontier Coding Agent with Reviewed Core Evolution, describes the reviewed core-evolution system, the 161-day Hope deployment, and the benchmark campaigns summarized below. Paper page · Hugging Face
Talk in Russian: an introduction to Ouroboros and its agent architecture at Practical ML Conf 2026.
The charts below are self-reported results on Terminal-Bench 2.1, OSWorld-Verified, and CL-Bench, measured against Codex, Claude Code, Cursor, and Hermes — on the same model where a matched pair was run, and against the public leaderboard where it was not.
Ouroboros first booted on February 16, 2026. During the following 48 hours, the repository advanced from the v4.1 line to v6.2.0. The self-authored record preserved from that period counts 32 evolution cycles. That first generation ran in Google Colab through Telegram and remains preserved on the legacy-google-colab branch and its original project page; the current generation carries the same identity into a native desktop and headless runtime.
⭐ Star Ouroboros to follow its next evolution. A star also helps more people find the project, trace its history, and take part in what it becomes.
Reviewed skills, transport bridges, tools, and widgets are available through OuroborosHub.