agent-rules-kit

--- globs: <root>/**/* alwaysApply: false --- # Pampa - Semantic Code Search Tool ## Overview Pampa is a powerful semantic search tool designed specifically for AI agents to efficiently navigate and understand codebases. It provides intelligent code indexing and search capabilities that go beyond simple text matching. ## Core Concepts ### What is Pampa? Pampa is an AI-powered code search engine that: - **Indexes code semantically**: Understands code meaning, not just syntax - **Provides contextual search**: Finds relevant code based on intent - **Supports multiple languages**: Works with Python, TypeScript, Java, Go, and more - **Integrates with AI agents**: Designed specifically for AI-assisted development ### Key Features #### Semantic Understanding - Analyzes code structure, relationships, and patterns - Understands function purposes, class relationships, and design patterns - Provides context-aware search results #### Multi-Language Support - Python, TypeScript, JavaScript, Java, Kotlin, C#, Swift, Go, PHP, Ruby, C/C++ - Language-specific parsing and understanding - Cross-language reference tracking #### AI Agent Integration - Optimized for AI agent workflows - Provides structured responses for automated processing - Supports batch operations and complex queries ## How Pampa Works ### 1. Code Indexing Pampa scans your codebase and creates a semantic index: - Parses source files for structure and meaning - Extracts functions, classes, imports, and dependencies - Builds relationships between code components - Creates embeddings for semantic similarity ### 2. Intelligent Search When you search for code: - Understands natural language queries - Finds functionally similar code even with different naming - Returns relevant context and usage examples - Provides explanations of how code works ### 3. Context Provision Pampa helps AI agents by: - Providing relevant code context for tasks - Finding examples of patterns and implementations - Identifying dependencies and relationships - Suggesting related code sections ## Benefits for Development ### For AI Agents - **Faster code understanding**: Quickly grasp large codebases - **Better context awareness**: Find relevant code for any task - **Improved suggestions**: Make informed recommendations based on existing patterns - **Efficient navigation**: Jump to relevant code sections instantly ### For Developers - **Code discovery**: Find existing implementations before writing new code - **Pattern learning**: Understand how patterns are implemented in your codebase - **Documentation**: Get instant explanations of code functionality - **Refactoring assistance**: Identify related code that might need updates ## Integration with Development Workflow Pampa integrates seamlessly into your development process: 1. **Installation**: Simple setup with minimal configuration 2. **Indexing**: Automatic scanning and indexing of your codebase 3. **Search**: Natural language queries to find relevant code 4. **Results**: Structured responses with code snippets and explanations ## Best Practices ### Query Formulation - Use descriptive, intent-based queries - Include context about what you're trying to accomplish - Ask about patterns, implementations, or specific functionality ### Code Organization - Keep consistent coding styles for better analysis - Use meaningful names for functions and variables - Include docstrings and comments for better semantic understanding ### Maintenance - Regular re-indexing for updated codebases - Keep dependencies up to date - Monitor search performance and optimize queries This foundation enables efficient, intelligent code search that enhances both AI agent capabilities and developer productivity.