Autonomous research review loop using any OpenAI-compatible LLM API. Configure via llm-chat MCP server or environment variables. Trigger with "auto review loop llm" or "llm review".
Unraid
Unraid is an open-source backend skill for Claude Code, Codex, and Gemini CLI, published by dinglebear-ai. Its author describes it as: “Query, monitor, and manage Unraid servers via GraphQL API through MCP tools. Supports system info, Docker, VMs, array/parity, notifications, plugins, rclone, and live telemetry.”. The project has 102 stars on GitHub and is available under the MIT license. Add it to your setup with `/plugin marketplace add dinglebear-ai/unraid`.
Installation
Add Unraid to your agent with:
/plugin marketplace add dinglebear-ai/unraidAlways review a skill's source before installing it. This command comes from the skill's public repository; the linked repo is the source of truth for exact setup steps.
When to use it
Reach for Unraid when you want backend help from Claude Code without writing the same instructions every session. Load the skill and the agent picks it up automatically for relevant tasks.
Strengths
- Clear MIT license — safe to read and adapt
- Established project with 102 GitHub stars
- Declares compatibility with Claude Code, Codex, Gemini CLI
- Actively maintained (recent commits)
Topics
Frequently asked questions
- What does Unraid do?
- Query, monitor, and manage Unraid servers via GraphQL API through MCP tools. Supports system info, Docker, VMs, array/parity, notifications, plugins, rclone, and live telemetry.
- How do I install Unraid?
- Run /plugin marketplace add dinglebear-ai/unraid in your agent, then reload your skills. Review the source at https://github.com/dinglebear-ai/unraid before installing.
- Is Unraid free to use?
- Yes. Unraid is free and open source under the MIT license, so you can read, run, and adapt it within that license's terms.
- Which agents does Unraid work with?
- Unraid declares compatibility with Claude Code, Codex, and Gemini CLI. Agent Skills use a portable SKILL.md format, so other compatible clients can usually load it too.
Related skills
More Backend →
The Ultimate guide to PostgreSQL Optimization for AI Code Generation in 2026
MCP server and Claude plugin for Postgres skills and documentation. Helps AI coding tools generate better PostgreSQL code.
Fast tokenizers optimized for research and production. Rust-based implementation tokenizes 1GB in <20 seconds. Supports BPE, WordPiece, and Unigram algorithms. Train custom vocabularies, track alignments, handle padding/truncation. Integrates seamlessly with transformers. Use when you need high-performance tokenization or custom tokenizer training.
Meta's 7-8B specialized moderation model for LLM input/output filtering. 6 safety categories - violence/hate, sexual content, weapons, substances, self-harm, criminal planning. 94-95% accuracy. Deploy with vLLM, HuggingFace, Sagemaker. Integrates with NeMo Guardrails.