This project provides a curated collection of bash scripts and slash commands to enhance the Claude Code environment, targeting power users. It offers lightning-fast commands and automated workflows, aiming to reduce token usage by 50-80% and improve operational efficiency by implementing Anthropic's recommended patterns for batched operations and standardized workflows, all while maintaining minimal context overhead.

How It Works

The project implements Anthropic's Claude Code Best Practices by focusing on optimizing the Claude execution environment. Its core approach involves: token-conscious bash scripts and CLI tools designed to minimize token usage; NLP-powered code analysis leveraging only Python's standard library for static analysis, code quality, and documentation insights without external dependencies; thoughtful batching to keep complex logic out of Claude's context; and comprehensive Software Development Life Cycle (SDLC) workflows for development, debugging, testing, documentation, Git operations, and deployment accessible via simple slash commands. It also integrates with Playwright and Context7 MCP servers for visual testing and up-to-date documentation. This strategy adds approximately 300 tokens to Claude's context, enabling professional-grade capabilities while significantly reducing token overhead.

Quick Start & Requirements

• Primary install: curl -sSL https://raw.githubusercontent.com/cassler/awesome-claude-code-setup/main/setup.sh | bash && source ~/.zshrc
• Alternative: git clone https://github.com/cassler/awesome-claude-code-setup.git && cd awesome-claude-code-setup && ./setup.sh && source ~/.zshrc
• Prerequisites: ripgrep and jq are required. Optional enhancements include fzf, bat, gum, delta, and httpie. The setup script automatically offers to install missing tools.
• Estimated setup time: Approximately 30 seconds for the one-line install.
• Links: Repository

Highlighted Details

• Features 19 Slash Commands for complete workflows, such as /start-feature, /debug-issue, /understand-codebase, and /visual-test.
• Provides 17 Shell Tools accessible via the ch command, categorized for project overview, search, Git, Docker, TypeScript, Python, Go, and NLP analysis.
• Offers NLP-Powered Code Analysis capabilities including complexity scoring, security vulnerability detection, code smell identification, duplicate code detection, and documentation coverage analysis, all using Python's standard library.
• Achieves significant token savings (50-80%) through efficient commands, batch operations, and token-aware analysis tools like ch nlp tokens.

Maintenance & Community

Contributions are welcomed via forking the repository, adding scripts or commands, and submitting pull requests. No specific community channels (e.g., Discord, Slack) or active maintainer information are detailed in the README.

Licensing & Compatibility

The project is released under the MIT License, which is permissive for commercial use and integration into closed-source projects.

Limitations & Caveats

The effectiveness of this toolset is primarily tied to the Claude Code environment. While the setup script attempts to install dependencies, users might need to manually install optional enhancements. The NLP analysis capabilities are constrained by what can be achieved using only Python's standard library.