czlonkowski/n8n-skills

Features

• AI Agent Development - Provides a comprehensive framework for creating, testing, and extending custom AI agents and their tools.
• AI Agent Frameworks - Implements a framework for designing autonomous agents with custom tools and memory systems within n8n.
• Agent Architectures - Provides architectural frameworks for designing autonomous agents using LLM chains and memory systems.
• AI Agent Tooling - Enables the creation of custom code functions and structured schemas to extend AI agent capabilities.
• Agentic Workflow Automation - Provides a comprehensive reference for designing and deploying agentic automation workflows and intelligent task sequences.
• Tool Schema Definitions - Defines AI agent capabilities by mapping structured input schemas to specific code functions.
• Binary-JSON Data Separation - Separates binary data from JSON streams to prevent memory bloat when handling large files and images.
• Enterprise Workflow Automations - Designs scalable production sequences and architectural patterns to automate complex business processes.
• Workflow Automations - Offers a system for designing and deploying production-ready automation sequences and tool integrations.
• Workflow Encapsulation Modules - Provides reusable workflow encapsulation modules with typed inputs to reduce logic duplication.
• Scripting References - Provides a technical reference for implementing custom logic using JavaScript and Python within code nodes.
• Array-of-Objects Data Models - Implements a standardized array-of-objects data model for consistent information passing between workflow nodes.
• Custom Scripting Nodes - Provides code nodes for executing arbitrary JavaScript and Python logic for complex data transformations.
• Automation - Implements proven structural approaches for managing webhooks, APIs, and binary data within automation sequences.
• Node Data Mapping - Builds templating patterns and expressions to map data dynamically between different workflow nodes.
• Workflow Automation Patterns - Provides architectural patterns for scalable and reliable automation using webhooks, APIs, and scheduled tasks.
• JavaScript Logic Execution - Supports developing scripts for code nodes using standard data access patterns and array-of-objects return formats.
• Python Logic Execution - Enables implementation of custom logic within code nodes adhering to standard library limitations.
• MCP Server Integrations - Integrates AI assistants with external Model Context Protocol servers using specific parameter and validation profiles.
• MCP Tool Connectors - Supports the execution of automated nodes and operational workflows via the Model Context Protocol.
• Dynamic Data Mapping - Implements templating patterns using variables and timestamps to map data dynamically between processing steps.
• Binary Data Boundary Control - Manages the separation of binary data from JSON and controls data boundaries between storage and agents.
• Container Orchestration & Deployment - Facilitates production deployments using container orchestration with automated HTTPS and high-availability settings.
• Production Deployment Guides - Offers detailed instructions for setting up self-hosted production environments with container orchestration and queue-mode.
• Self-Hosted Deployments - Supports self-hosted production installations on Linux via container orchestration.
• Error Handling Workflows - Implements automated recovery workflows and retry logic to ensure system recoverability.
• Error Routing Logic - Implements node-level error routing to map failures to retry logic or recovery workflows.
• Polyglot Code Execution - Supports custom logic implementation in both JavaScript and Python using a shared data access pattern.
• Composable Sub-workflows - Supports the development of composable workflow modules with typed inputs and parallel execution to reduce duplication.
• Office and Workflow Skills - Automated creation and management of workflow sequences.

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