Skill UI

Automates GitLab project operations through Composio's Rube MCP, covering issue tracking, merge request workflows, CI/CD pipelines, branch handling, and user management for faster DevOps work.

This utility provides programmatic access to Granola meeting data, enabling developers to build automated post-meeting workflows. Users can read meeting notes from the local cache, integrate with MCP servers for AI context, automatically extract action items and assignees, and sync outcomes directly into coding tasks, project documentation, or issue trackers like GitHub. Ideal for automating the development lifecycle from meeting insights.

A comprehensive guide to setting up a fast, reproducible local development workflow for Groq applications. This setup includes structured project scaffolding, implementing singleton clients, defining model constants, and providing isolated unit tests with mocking, alongside live integration tests. Ideal for developers building low-latency LLM applications and ensuring rapid iteration cycles.

This comprehensive guide details how to set up robust CI/CD pipelines for projects integrating with Ideogram. It covers automated unit testing, optional integration tests using GitHub Secrets, and crucial prompt validation logic directly within GitHub Actions workflows, ensuring high code quality and reliable API interaction.

Automate Jira operations through Atlassian MCP by searching, creating, updating, transitioning, and commenting on issues while auto-detecting project configuration and enforcing consistent templates for sprint and workflow requests.

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 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.

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 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.