Skill UI

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.

A comprehensive guide for developers on utilizing the Kling AI Text-to-Video REST API. This skill provides minimal working examples in Python and Node.js, demonstrating the complete workflow: submitting a text prompt, polling the task status, and retrieving the final generated video URL. Ideal for integrating advanced AI video generation capabilities into development projects.

This skill provides a comprehensive guide to the credit-based pricing model of Kling AI. It details costs for video generation (Standard/Professional modes), image creation (Kolors), and API resource packs. Users can utilize this guide to accurately budget, estimate total project costs, and implement cost-saving strategies, ensuring the efficient and economical execution of their AI content generation workflow.

This guide provides minimal working examples demonstrating the LangChain Expression Language (LCEL). It shows how to chain together diverse components—such as prompts, LLMs, and output parsers—using simple pipe syntax (e.g., .pipe() or |). Ideal for developers starting a new LangChain project, understanding core AI workflow patterns, or mastering structured data output.

A comprehensive guide to configuring a structured, local development environment for LangChain applications. It covers setting up project architecture, managing dev dependencies, and implementing a two-tiered testing strategy: isolated unit tests using mocked LLMs (for fast, API-free testing) and robust integration tests using real API providers. Ideal for establishing a reliable, rapid iteration workflow.

Automates LaunchDarkly feature flag workflows by listing projects and environments, crafting webhook-driven trigger workflows, deleting flows, and tracking code references through Composio MCP.

Automate Linear project, issue, cycle, label, and comment workflows via the Composio Linear toolkit exposed through Rube MCP, including prerequisite connection checks and optional custom GraphQL queries for advanced cases.

A comprehensive solution to integrate Linear project management with GitHub Actions CI/CD pipelines. This skill enables automating development workflows by running integration tests, automatically linking Pull Requests (PRs) to issues, transitioning issue states based on PR events, and creating new Linear issues directly from build failures. Ideal for ensuring development quality and maintaining up-to-date project tracking.

This skill provides a comprehensive command-line interface (CLI) for managing issues, projects, and teams within the Linear platform. Users can create, update, and track the status of issues, set project phases (e.g., backlog, in-progress), and manage complex workflows directly from the terminal, ensuring better traceability and project organization.

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.

This guide details how to use the official @linear/sdk to interact with the Linear project management API. It covers performing core CRUD operations, such as creating new issues, listing teams, querying issue states, and performing raw GraphQL requests. Ideal for developers needing to integrate Linear into a custom workflow, test API connectivity, or learn foundational automation patterns.