Recursive self-improvement engine. Think from first principles, let insights emerge.
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Select your agent
Option 1: Install via CLI (recommended)
Recommended (no pre-install needed)
npx clawhub@latest --dir ~/.claude/skills install ralph-evolverOr via clawhub CLI (if already installed)
clawhub --dir ~/.claude/skills install ralph-evolverβ οΈ Requires Node.js 18+. No Node? Use Option 2 below to download the ZIP instead. Install Node.js β
Option 2: Manual install (no Node required)
Download the ZIP, extract it, and place the folder at the path below. Restart your agent to activate.
Install path
~/.claude/skills/ralph-evolver/π‘Extract and place the folder at the path above, then restart your agent.
Category
π€AI Agent & AutomationPlatforms
What Ralph Evolver can do for your AI workflow
Recursive self-improvement directly from your Claude conversation
Works across Claude, Cursor, OpenClaw β install once, use everywhere
Trusted by 3,640+ developers worldwide
One-command installation β no complex setup required
Combine with other skills to build powerful multi-step AI workflows
Try these prompts with your AI agent after installing Ralph Evolver
Help me get started with Ralph Evolver
Explains what Ralph Evolver does, walks through the setup, and runs a quick demo based on your current project
Use Ralph Evolver to recursive self-improvement engine
Invokes Ralph Evolver with the right parameters and returns the result directly in the conversation
What can I do with Ralph Evolver in my ai agent & automation workflow?
Lists the top use cases for Ralph Evolver, with example commands for each scenario
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Ralph Evolver extends your AI assistant with the ability to recursive self-improvement engine. Think from first principles, let insights emerge. Rather than leaving your conversation to handle this manually, you can ask your Claude agent directly β and it will take care of the task end-to-end, using Ralph Evolver as its underlying capability.
Ralph Evolver works across Claude, Cursor, OpenClaw through the Model Context Protocol (MCP) β an open standard that lets AI clients share tools and skills without lock-in. Because MCP is platform-agnostic by design, you install Ralph Evolver once and it becomes available across all your AI clients. Whether you're working in Claude for focused sessions or Cursor for integrated workflows, the skill behaves consistently.
Getting started with Ralph Evolver takes about two minutes. Place the skill at `~/.claude/skills/ralph-evolver/` (personal, all projects) or `.claude/skills/ralph-evolver/` (project-specific), then restart your AI client. From that point, typing `/ralph-evolver` in any conversation activates it, or the AI will use it on its own when it detects a relevant request.
Ralph Evolver has been installed 3,640 times, making it one of the more actively used skills in the AI Agent & Automation category. The install rate suggests it solves a real, recurring need rather than a niche edge case. Like all skills on DiscoverAISkills, it is free to install and use. The broader AI skills ecosystem continues to expand as developers contribute new capabilities across categories like developer tools, data analysis, writing, automation, and more.
Place the skill folder at ~/.claude/skills/ralph-evolver/ for personal use (all projects), or .claude/skills/ralph-evolver/ for project-specific use. Restart your AI client, then invoke with /ralph-evolver or let the AI discover it automatically.
Ralph Evolver supports Claude, Cursor, OpenClaw. It integrates seamlessly with these AI platforms to extend their capabilities.
Ralph Evolver is free to install. Check the repository for licensing information.
Recursive self-improvement engine. Think from first principles, let insights emerge.
Automate my ai agent & automation tasks using Ralph Evolver
Identifies repetitive steps in your workflow and sets up Ralph Evolver to handle them automatically
Ralph Evolver is categorized under AI Agent & Automation. These skills help AI agents perform specialized tasks in this domain.
A self-evolution engine for AI agents. Analyzes runtime history to identify improvements and applies protocol-constrained evolution. Communicates with EvoMap...