Skill UI

This skill provides comprehensive guidance for the creation, organization, and management of Helm charts. It is essential for packaging, distributing, and deploying Kubernetes applications across various environments. Use it when implementing complex, templated, and reusable manifests for robust cloud-native deployments.

Automates iam policy creation for AWS Skills, activating when you mention the trigger, guiding best practices, generating production-ready configs, and validating outputs for compute, storage, networking, and serverless scenarios.

This skill provides comprehensive tools for managing lead data within the Instantly platform. It handles lead list creation, robust lead imports with validation (e.g., block list checks, email format checks), and essential updates (move, status change). Crucially, it ensures compliance with international regulations like GDPR and CAN-SPAM by managing unsubscription flows and deletion rights.

Automate Jira tasks through Composio’s Rube MCP connector, covering issue search, creation, edits, agile boards, comments, projects, and user roles while always querying latest tool schemas.

A comprehensive guide and expert skill for mastering Atlassian Jira. Covers project setup, advanced JQL querying, workflow design, issue tracking, automation rules, reporting, and dashboard creation. Essential for technical configuration and operational optimization of Jira instances.

Automates JMeter test plan creation and validation for load, stress, and benchmarking scenarios; triggers whenever you request the jmeter test plan creator and delivers production-ready configs aligned with best practices.

Auto-activating DevOps skill that guides Kubernetes deployment creation with best practices, production-ready IaC configurations, and validation across Terraform, Helm, and monitoring workflows.

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.

This comprehensive guide details how to safely upgrade LangChain versions (e.g., from 0.1.x to 0.3.x+). It covers critical breaking changes across both TypeScript and Python implementations, including updating import paths, converting legacy LLMChain to the modern LCEL pipe syntax, updating agent creation, and migrating memory management. Essential for maintaining and modernizing existing LLM applications.

A comprehensive guide covering production-grade patterns for using the Langfuse SDK. Learn how to implement robust LLM observability, including singleton client setup, using the `observe` wrapper for automatic span creation, and utilizing `startActiveObservation` for fine-grained trace control. Essential for maintaining high standards of observability in AI-powered applications.

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.

This skill guides developers through setting up and processing Lokalise webhooks for real-time content synchronization. It covers the API integration steps to register webhook endpoints, handling various translation lifecycle events (key creation, translation updates, file imports), and implementing secure payload verification using webhook secrets. It demonstrates building robust, asynchronous event handlers in Node.js/Express, perfect for automating workflows based on content changes in a SaaS environment.