By quabug
Multi-agent orchestration plugin. Bundles skills that coordinate configurable AI agents in parallel for questions, code reviews, PR fixes, and panel discussions. Agents are configured via CLAUDE.md or auto-detected from PATH.
Ask configured AI agents a question in parallel and display their responses. Optionally target a specific agent or model. Use when the user says "ask all agents", "ask codex", "ask gemini", "ask glm-5", or wants AI perspectives on a question.
This skill should be used when the user asks to "fix a PR", "fix pull request", "fix PR issues", "review and fix PR", or wants an iterative multi-agent review + fix loop that automatically resolves issues found in a GitHub pull request.
This skill should be used when the user asks to "review a PR", "review pull request", "PR review", or wants a multi-agent code review of a GitHub pull request using configurable AI tools in parallel.
Host a multi-agent round-table discussion. Spawns configurable external CLI agents as panelists with distinct roles and moderates a structured multi-round debate. Use when the user says "round-table", "multi-AI discussion", or "panel discussion".
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npx claudepluginhub quabug/multi-agents-plugin --plugin multi-agentsMulti-agent collaboration plugin for Claude Code. Spawn N parallel subagents that compete on code optimization, content drafts, research approaches, or any problem that benefits from diverse solutions. Evaluate by metric or LLM judge, merge the winner. 7 slash commands, agent templates, git DAG orchestration, message board coordination.
Intelligent orchestration platform for AI coding tools — routes tasks to the best model, learns from outcomes, and enforces quality through multi-model consensus. 46 MCP tools for agent management, research, memory, consensus voting, codebase intelligence, and a full dev pipeline.
Multi-agent deliberation for AI coding assistants
Repowire mesh usage skills for AI coding agents: cross-agent review and planning, delegate, usage patterns, and install/update. Backend-agnostic and parameterised on the agent you choose.
Delegate tasks to Codex, Gemini, and OpenCode AI agents via Owlex MCP
Multi-agent orchestration via li o flow and li o fanout