Everything Claude Code
Everything Claude Code is an agent harness performance optimization system built for Claude Code, Codex, Cursor, and other AI development tools. This system provides skills, memory persistence, security scanning, and continuous learning capabilities evolved from 10+ months of production use.
Key Features
- Agent performance optimization — Token optimization, memory persistence, and continuous learning loops
- Security scanning — AgentShield component with vulnerability detection and sanitization
- Cross-platform support — Works with Claude Code, Cursor, Codex CLI/app, and OpenCode
- Skills library — 50+ specialized skills for TypeScript, Python, Go, Java, Kotlin, and 7 other languages
- Memory system — Hooks that automatically save/load context across sessions
- Verification loops — Checkpoint and continuous evaluation with grader metrics
- Subagent orchestration — Git worktree parallelization and cascade methods
Installation
Install the universal package:
npm install -g ecc-universal
For security features:
npm install -g ecc-agentshield
Clone and run selective install:
git clone https://github.com/affaan-m/everything-claude-code
cd everything-claude-code
node install-plan.js
node install-apply.js
Use ECC_HOOK_PROFILE=minimal|standard|strict and ECC_DISABLED_HOOKS=... to control runtime behavior without editing hook files.
Basic Usage
Initialize in your Claude Code workspace:
# Setup for Claude Code
ecc init --harness claude-code
# For Codex CLI
ecc codex-setup
# Enable specific skills
ecc skill enable typescript-reviewer
ecc skill enable memory-persistence
Basic harness commands:
// In your AI chat
/harness-audit // Performance scoring
/loop-start // Begin continuous eval
/quality-gate // Checkpoint validation
/model-route // Switch model strategies
Start with the Shorthand Guide on the project's social media for setup fundamentals, then reference the Longform Guide for advanced token optimization.
Notable Details
License: MIT
Language: JavaScript with TypeScript, Python, Go, Java support
Community: 135K+ stars, 6K+ forks, 30+ contributors
Languages supported: 7 (English, Portuguese, Chinese, Japanese, Korean, Turkish)
Origin: Anthropic Hackathon Winner
The project includes 997 internal tests and maintains compatibility across major AI development harnesses through a manifest-driven install system.