π―Skills18
Comprehensive code review skill that analyzes diffs for security vulnerabilities, anti-patterns, and quality issues with automatic frontend/backend domain detection
Provides Electron 28 patterns for the LlamaFarm Desktop application, covering main/renderer processes, IPC communication, security, and packaging.
Provides shared TypeScript best practices for LlamaFarm's Designer (React) and Electron subsystems, covering idiomatic patterns for TanStack Query, TailwindCSS, and Radix UI.
Shared Python best practices for the LlamaFarm monorepo, covering patterns, async programming, typing, testing, error handling, and security.
Provides React 18 patterns for LlamaFarm Designer, covering components, hooks, TanStack Query v5, React Router v7, and testing.
Shared Go best practices for the LlamaFarm CLI project, covering idiomatic Go patterns, error handling with context wrapping, concurrency with mutexes and channels, table-driven testing, and security guidelines for Go 1.24+ with Cobra and Bubbletea.
RAG-specific best practices skill for LlamaFarm covering LlamaIndex, ChromaDB, and Celery workers, including ingestion, retrieval, embeddings, and performance patterns.
Provides CLI development best practices for LlamaFarm using Cobra, Bubbletea, and Lipgloss frameworks in Go.
Common utilities best practices skill for LlamaFarm covering HuggingFace Hub integration, GGUF model management, and shared Python utilities used across all LlamaFarm services.
Designer skills for LlamaFarm covering React 18, TanStack Query, TailwindCSS, and Radix UI patterns for the designer subsystem.
Provides server-specific best practices for FastAPI, Celery, and Pydantic development within the LlamaFarm project, extending Python skills with framework-specific patterns.
Universal runtime best practices for PyTorch inference, Transformers models, and FastAPI serving, covering device management, model loading, and memory optimization.
Configuration module patterns skill for LlamaFarm covering Pydantic v2 models, JSONSchema generation, YAML processing, and validation.
Guidelines for creating temporary files in the system temp directory, helping agents create reports, logs, or progress files without cluttering the repository.
Generates specialized skills for each subsystem in a monorepo, creating shared language skills and subsystem-specific checklists for high-quality AI-assisted code generation.
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