Skill UI

A comprehensive guide for deploying the application layer that interacts with Lindy AI agents. This includes setting up webhook receivers, managing callback handlers, and ensuring production readiness across multiple platforms like Docker, Vercel, and AWS. It covers prerequisites, multi-step deployment instructions, post-deployment verification scripts, and rollback plans for robust MLOps practices.

A comprehensive runbook detailing procedures for responding to failures and outages across Lindy AI agents. Covers critical scenarios including platform downtime (SEV1), individual agent failures, integration authentication issues, credit exhaustion, and webhook endpoint failures. Provides structured diagnostics and fallback strategies to ensure business continuity during incidents.

A comprehensive guide detailing advanced strategies for migrating complex, rule-based automations from platforms like Zapier, Make, n8n, or custom codebases to Lindy AI. It teaches users how to redesign workflows, leveraging AI agents to replace rigid conditional logic with adaptable reasoning, ensuring a smooth and intelligent transition across multiple phases.

llama.cpp is a pure C/C++ library designed for efficient LLM inference, optimized to run on resource-constrained environments. It excels in scenarios where high-end NVIDIA GPUs (CUDA) are unavailable, making it ideal for Apple Silicon Macs, AMD/Intel GPUs, or edge deployment devices like Raspberry Pi. It supports GGUF quantization formats, enabling significant memory reduction and speed improvements for local, cross-platform AI applications.

This comprehensive guide details the deployment process for Mistral AI-powered applications across various cloud and container platforms, including Vercel, Docker, Google Cloud Run, and self-hosted vLLM setups. It covers secure API key management, platform-specific secret configuration, and the full steps required to establish robust, scalable production pipelines for your AI model.

Track experiments, catalog models, compare versions, and deploy trained artifacts with MLflow’s framework-agnostic lifecycle tools across PyTorch, TensorFlow, and other stacks.

Mastery of modern mobile development across multiple platforms, including React Native, Flutter, and native iOS/Android. Expertise covers the entire lifecycle, specializing in architectural patterns (Clean, MVVM), performance optimization, offline-first data synchronization (GraphQL, SQLite), advanced DevOps practices (CI/CD, Fastlane), and App Store Optimization (ASO). Ideal for building robust, scalable, and highly performant cross-platform applications.

This comprehensive workflow guides the process of building and deploying new features that must maintain consistent functionality and design across multiple operating systems (web, mobile, and desktop). It strictly follows an API-first architecture, starting with defining shared API contracts (OpenAPI/GraphQL) and a unified design system. The process then guides parallel implementation across specialized stacks like React/Next.js, SwiftUI, and Jetpack Compose, ensuring high code consistency and faster time-to-market.

This comprehensive checklist guides developers through the pre-release verification process for Obsidian community plugins. It covers critical technical areas such as validating manifest structure, ensuring clean production builds (e.g., removing sourcemaps), identifying potential memory leaks, and verifying cross-platform readiness, ensuring a high-quality user experience upon submission.

Guides marketers through planning, executing, and scaling paid campaigns across Google Ads, Meta, LinkedIn, and other platforms with strategy, audience targeting, budgeting, and creative/optimization best practices.

This guide provides comprehensive principles for modern game development, covering engine selection (Unity, Unreal, Godot), platform integration (Steam features, console compliance), input abstraction, and performance optimization techniques. It helps developers make informed decisions when building cross-platform games for PC and console environments.

This skill provides expert guidance on writing highly portable shell scripts that adhere strictly to POSIX standards. It teaches users how to avoid shell-specific extensions (like advanced arrays, specific conditionals, or GNU features) to ensure maximum compatibility and robustness across diverse Unix-like systems (Linux, BSD, Solaris, etc.). Ideal for critical infrastructure scripting and environments requiring extreme cross-platform reliability.