By agentic-box
Delegate code review, debugging, architecture decisions, large codebase analysis, and security audits to specialized AI agents like Codex, Gemini, OpenCode, or multi-agent councils via Owlex MCP server. Start CLI sessions or use intelligent task routing with async result checks for focused, multi-perspective AI assistance.
npx claudepluginhub agentic-box/owlexDelegate code review, debugging, PRD writing, and implementation tasks to OpenAI Codex. Best for focused code analysis, bug finding, and technical writing.
Get multiple AI perspectives via Council deliberation. Use for architectural decisions, complex trade-offs, and when consensus or diverse viewpoints matter.
Delegate large codebase analysis, long document processing, and multimodal tasks to Google Gemini. Best for 1M token context, image/video analysis, and comprehensive exploration.
Intelligent task router that delegates to the optimal AI agent (Codex, Gemini, or Council) based on task characteristics. Use when unsure which agent is best.
Start an OpenAI Codex CLI session for deep reasoning and code analysis
Consult the AI council (Codex + Gemini + OpenCode) for multi-perspective answers
Council critique mode - agents find bugs and flaws in each other's answers
Start a Google Gemini CLI session with 1M context for large codebase analysis
Uses power tools
Uses Bash, Write, or Edit tools
Share bugs, ideas, or general feedback.
Consult multiple AI coding agents (Gemini, OpenAI, Grok, Perplexity, plus codex and gemini CLIs when installed) to get diverse perspectives on coding problems
Consult external AIs (Gemini 2.5 Pro, OpenAI Codex, Claude) for second opinions. Use for debugging failures, architectural decisions, security validation, or need fresh perspective with synthesis.
Hub plugin for cc-multi-cli-plugin: contains the companion runtime, subagents, setup wizard, and customization skills.
Collect and synthesize opinions from multiple AI Agents for Claude Code
Intelligent orchestration platform for AI coding tools — routes tasks to the best model, learns from outcomes, and enforces quality through multi-model consensus. 38 MCP tools for agent management, research, memory, consensus voting, codebase intelligence, and a full dev pipeline.