Autonomous self-learning Agent Plugin for Claude Code Automatic learning, real-time dashboard, 40+ linters, OWASP security, CodeRabbit PR reviews. Production-ready with 100% local processing, privacy-first. Free open source AI automation tool
git clone https://github.com/bejranonda/LLM-Autonomous-Agent-Plugin-for-Claude.gitThis autonomous agent plugin extends Claude Code with a four-tier architecture of 35 specialized agents that continuously improve through task execution. It provides enterprise-grade capabilities including comprehensive KPI intelligence across 11 metrics, automatic vulnerability remediation against OWASP Top 10, and support for 40+ linters across 15+ programming languages. The system operates with 100% local processing for privacy, delivers analysis in seconds instead of minutes, and achieves 80-90% auto-fix success rates on common issues. All processing happens locally without cloud dependencies, making it suitable for production environments requiring data privacy and autonomous operation.
Install the plugin and use category-based commands like `/dev:auto "requirement"` to trigger autonomous execution. Access the real-time dashboard for monitoring agent performance, KPIs, and system health. The system requires no configuration—it automatically learns and optimizes from every task executed.
Automated code quality analysis and auto-remediation across multiple languages
Real-time security vulnerability detection and OWASP compliance checking
Continuous cost optimization with 60-70% token reduction tracking
Production release workflows with automated validation and testing
No install command available. Check the GitHub repository for manual installation instructions.
git clone https://github.com/bejranonda/LLM-Autonomous-Agent-Plugin-for-ClaudeCopy the install command above and run it in your terminal.
Launch Claude Code, Cursor, or your preferred AI coding agent.
Use the prompt template or examples below to test the skill.
Adapt the skill to your specific use case and workflow.
Act as an autonomous agent using the LLM-Autonomous-Agent-Plugin-for-Claude. Analyze [CODEBASE] from [COMPANY] in the [INDUSTRY] sector. Identify key areas for improvement in code quality, security, and documentation. Provide a detailed report with actionable recommendations.
# Code Analysis Report for [COMPANY] ## Overview The codebase for [COMPANY] in the [INDUSTRY] sector has been analyzed using the LLM-Autonomous-Agent-Plugin-for-Claude. The analysis covers code quality, security, and documentation. ## Key Findings ### Code Quality - **Code Duplication**: 15% of the codebase contains duplicated logic. - **Complexity**: High complexity in the `authentication` module. - **Documentation**: 30% of functions lack proper documentation. ### Security - **OWASP Top 10**: Potential SQL injection vulnerabilities in the `database` module. - **Dependencies**: Outdated dependencies in `package.json`. - **Authentication**: Weak password hashing algorithm. ### Recommendations - **Code Quality**: Refactor duplicated code and simplify the `authentication` module. - **Security**: Update dependencies and implement stronger password hashing. - **Documentation**: Add JSDoc comments to undocumented functions. ## Next Steps 1. Schedule a team meeting to discuss the findings. 2. Prioritize the security vulnerabilities. 3. Implement the recommended changes in the next sprint.
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