by decebals · Claude Skill · ★ 345
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claude-code-java Reusable AI development infrastructure for Java projects, optimized for Claude Code This project is not affiliated with Anthropic. What is this? A collection of reusable components for Claude Code - Anthropic's agentic coding tool. The core of this project is a set of skills (structured markdown files that provide Claude with domain knowledge and workflows), but it also includes project templates, MCP server configurations, and setup scripts. Who is this for? Java developers using Claude Code who want consistent, high-quality AI assistance for common tasks like code reviews, testing, commits, and architecture decisions. Purpose AI-powered development workflows with focus on: Token efficiency - Designed for fewer iterations and lower token usage Reproducible patterns - Reusable workflows across projects Java ecosystem - Tailored for Java/Maven development Incremental adoption - Start small, expand as needed Quick Start Clone this workspace Setup your Java project This creates with symlinked skills, generate
| Stars | 345 |
| Forks | 59 |
| Language | Shell |
| Category | Claude Skill |
| License | MIT |
| Quality Score | 45.25/100 |
| Last Updated | 2026-02-08 |
| Created | 2026-01-30 |
| Platforms | claude-code, cli |
| Est. Tokens | ~7k |
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claude-code-java is Reusable AI development infrastructure for Java projects, optimized for Claude Code. It is categorized as a Claude Skill with 345 GitHub stars.
claude-code-java is primarily written in Shell. It covers topics such as ai-assisted-development, claude-code, claude-code-skills.
You can find installation instructions and usage details in the claude-code-java GitHub repository at github.com/decebals/claude-code-java. The project has 345 stars and 59 forks, indicating an active community.
claude-code-java is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to claude-code-java on Agent Skills Hub include Skills-Manager, ai-maestro, claude-code-skills. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.