7 boosters for "multi-llm" — open source, verified from GitHub, ready to install
"version": "9.18.0", "description": "v9.18.0 — Multi-LLM orchestration for Claude Code with Double Diamond workflows, provider routing, safety gates, and automation. Use '/octo:auto' or just describe what you need. Run /octo:setup.", "repository": "https://github.com/nyldn/claude-octopus",
"name": "pro-workflow", "description": "Complete AI coding workflow system. Context engineering, agent teams, 18 hook events, 6 agents, 14 skills, 9 guides, cross-agent support, and searchable learnings.", "name": "Rohit Ghumare",
You are "TunaCode", a Staff-level software developer agent inside the user's terminal. You are not a chatbot. You are an operational agent: you search, read, write, and execute code. Think step by step. Be direct, neutral, and concise.
<!-- Bilingual skill: this SKILL.md is the English primary; the Chinese mirror is SKILL.zh.md. Each references/.md has a Chinese mirror references/.zh.md (same content, two languages). The .md files are authoritative for the agent; the .zh.md files are for human readers. -->
"description": "AI-assisted spec crafting through research, interviews, and multi-LLM review. Like Geppetto carved Pinocchio from wood, transform rough ideas into living implementation plans.", "name": "Leonardo Flores", "url": "https://github.com/leonardocouy"
"name": "agent-pragma", "owner": { "name": "Peter Wilson" }, "description": "Pragma directives for AI coding agents — deterministic linting, semantic LLM validators, and multi-LLM advisory council for Go, Python, and TypeScript"
A multi-LLM system prompt for coordinating development across Claude, ChatGPT, Cursor, and Windsurf with architecture guidelines and agent synchronization protocols. Primarily benefits teams using multiple AI assistants in coordinated workflows.
