Skill UI

Master the configuration of Langfuse webhooks to capture crucial prompt lifecycle events (Created, Updated, Deleted). This skill guides you through building a secure endpoint to intercept these events, enabling powerful, automated integrations. Use cases include triggering CI/CD pipelines upon production prompt changes, syncing data to external systems, or notifying teams via Slack.

A comprehensive guide for managing Lindy AI agents through platform upgrades, reconfigurations, or workspace migrations. It covers the entire lifecycle, including inventory documentation, configuration exporting, phased deployment planning, and critical post-migration steps for webhooks, email, and phone numbers, ensuring business continuity.

This skill provides comprehensive management of the entire issue lifecycle within the Linear project management tool. Users can create new issues, update key metadata (priority, labels, due dates), and automate state transitions through defined workflows. It also supports building parent/sub-issue hierarchies, managing issue relations (blocks, duplicates), and adding comments, making it ideal for automating project tracking and workflow enforcement.

Automate core Agile workflows within Linear. This skill allows users to manage the entire project lifecycle, including creating and updating projects, setting milestones, assigning issues, and managing time-boxed cycles (sprints). It also includes advanced functionalities like calculating cycle metrics and rolling over unfinished tasks, significantly streamlining product development and planning processes.

Provides a deep dive into migrating issue tracking data from major platforms like Jira, Asana, and GitHub to Linear. This guide covers the entire lifecycle, including initial workflow assessment, status and priority mapping, data export utilizing API examples, and detailed transformation logic required to ensure data integrity and smooth adoption within Linear.

This skill guides users through the entire lifecycle of developing intelligent AI assistants, chatbots, and conversational interfaces. It specializes in establishing robust natural language understanding, managing multi-turn context, and defining best practices for creating seamless, production-ready AI applications with real-world value.

A comprehensive guide to integrating Lokalise into Continuous Integration/Continuous Deployment (CI/CD) workflows using GitHub Actions. This setup automates the entire translation lifecycle: uploading source strings on code pushes, downloading the latest translations during builds, and running PR checks to ensure translation coverage across all required locales. It eliminates manual file management, keeping code, translations, and CI pipelines perfectly synchronized.

This skill provides comprehensive handling for Lokalise translation data, covering the entire localization lifecycle. It facilitates creating keys with rich metadata, managing versions using immutable snapshots, isolating work with feature branches, and generating various export formats (JSON, XLIFF). It is essential for handling sensitive translation data, ensuring PII compliance, and managing scalable internationalization within development pipelines.

Provides a comprehensive, production-ready reference architecture for integrating Lokalise Translation Management System (TMS) into web applications. This guide covers the entire end-to-end translation lifecycle, including best-practice project layouts, file organization for i18n, CI/CD workflows (build-time vs. OTA paths), and necessary API client implementations. Use this when establishing new multi-language support or standardizing localization practices across a team.

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.

This skill guides the design and implementation of a complete, production-grade Machine Learning pipeline. It employs a multi-agent orchestration workflow, systematically covering all stages of the ML lifecycle: data ingestion and quality assurance, feature engineering, model training, optimization, and robust deployment (MLOps). It ensures built-in reproducibility, monitoring, and scalability.

This comprehensive skill provides full programmatic control over the entire work order lifecycle within the MaintainX platform. Users can create new work orders with detailed metadata, programmatically transition their status (Open, In Progress, On Hold, Completed), query existing tasks, and attach documentation or comments. It is ideal for automating complex maintenance operations and ensuring end-to-end operational visibility.