Skill UI

Master the art of building robust, production-grade LLM chains using LangChain Expression Language (LCEL). This guide covers advanced composition patterns, including sequential, parallel, and conditional branching chains. It also details prompt templating, structured output parsing (JSON/Zod), and context injection, enabling the creation of complex, multi-step AI pipelines.

Master the creation of autonomous AI agents using LangChain. This guide covers defining tools with schemas (Zod), utilizing `createToolCallingAgent` and `AgentExecutor` for multi-step decision-making, managing conversation memory, and implementing streaming output. Ideal for building complex, tool-augmented workflows.

This comprehensive guide details the best practices for configuring Langfuse across development, staging, and production environments. It covers essential steps including environment-specific API key management, secret integration (AWS/GCP), and implementing reliable CI/CD pipelines to ensure data isolation and prevent cross-environment leakage, maintaining observability throughout the software lifecycle.

Automates LaunchDarkly feature flag, environment, segment, and rollout workflows through Composio's Rube MCP toolkit; discover schemas with `RUBE_SEARCH_TOOLS`, manage connections, and orchestrate multi-step operations safely.

Automates Leiga operations via Rube MCP by discovering the latest tool schemas, validating toolkit connections, and executing multi-step commands through Composio endpoints before running workflows.

Guides use of Composio’s Rube MCP toolkit to locate Lexoffice tools, verify connections, obey schema requirements, and execute multi-step workflows for automating accounting tasks securely.

A comprehensive guide and tool for building and configuring complex, multi-step AI agent workflows. Users can define sophisticated automation pipelines by chaining together customizable triggers (e.g., email, webhook), actions (e.g., Slack post, database update), conditional logic, and external knowledge bases. Ideal for automating business processes like customer support triage, data processing, and complex notifications, ensuring deterministic and scalable AI operations.

Master the creation of complex, event-driven, and scheduled automation workflows. This guide covers setting up various triggers (email, chat, webhook, calendar), implementing conditional filters, managing multi-step processes, and orchestrating specialized AI agents in a multi-agent 'Society' for advanced delegation and collaboration.

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.

This guide provides comprehensive strategies for optimizing the execution speed, reliability, and cost efficiency of AI agents. Learn how to minimize latency, right-size models (e.g., Flash vs. Opus), consolidate multiple LLM steps into single prompts, and optimize workflow triggers. Ideal for use when agents are slow, consuming excessive credits, or producing inconsistent results.

This skill provides comprehensive patterns for integrating external applications with the Lindy AI platform. It covers three primary channels: Webhook triggers for receiving inbound data, HTTP actions for making outbound API calls, and executing custom Python/JavaScript code (Run Code). Use this when building complex, multi-step automation workflows or connecting internal systems to Lindy agents.

This comprehensive guide outlines a multi-step process for safely upgrading the Linear SDK across major versions. It details how to check for breaking changes (like renamed fields or changed return types), implement compatibility layers using patterns like the Bridge pattern in TypeScript, run thorough unit and integration tests, and establish a robust deployment and rollback plan, ensuring zero downtime migration.