worktree-pr

alfredolopez80/multi-agent-ralph-loop

Orchestration system for Claude Code with memory-driven planning, multi-agent coordination, Agent Teams integration, automatic learning, and comprehensive security validation (Grade A-). v2.93.0

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Installation

Option 1: Use slash command in Claude Code

/install-skill https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr

Option 2: Clone to skills directory

# Global (all projects)

git clone https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr ~/.claude/skills/multi-agent-ralph-loop

# Project-specific

git clone https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr .claude/skills/multi-agent-ralph-loop

Add MCP server to .cursor/mcp.json:

{
  "mcpServers": {
    "skillz": {
      "command": "npx",
      "args": ["-y", "skillz-mcp", "https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr"]
    }
  }
}

Restart Cursor after adding the configuration.

Option 1: Use Gemini CLI command

gemini extensions install https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr

Option 2: Clone to extensions directory

git clone https://github.com/alfredolopez80/multi-agent-ralph-loop/tree/main/.claude/skills/worktree-pr ~/.gemini/extensions/multi-agent-ralph-loop

Topics

ai-orchestration automation bats-testing claude-code code-quality codex codex-cli dynamic-contexts eval-driven-development llm minimax multi-agent multi-agent-system observability opencode plan-lifecycle quality-gates ralph-loop state-machine ultrathink