Skill UI

Spec-Driven Development (SDD) is a structured methodology that mandates defining comprehensive specifications before writing any code. It guides users through a gated process: SPECIFY -> PLAN -> TASKS -> IMPLEMENT. This workflow ensures all assumptions are surfaced, requirements are concrete, and the final product has clear success criteria, minimizing ambiguity and architectural risk in large projects.

This skill provides comprehensive management for annotation schemas (configs) and human review workflows (queues) within the Arize platform. It supports defining categorical, continuous, and freeform label types. Users can programmatically apply these annotations to project spans and datasets using the Python SDK, facilitating structured human feedback loops and improving model monitoring.

This workflow guides developers through generating standardized, descriptive commit messages using the Conventional Commits specification. It provides a structured XML template (including type, scope, description, body, and footer) and integrates directly into the Git workflow, ensuring project history is clean, traceable, and machine-readable. Ideal for maintaining large, collaborative codebases.

Copilot Spaces allow users to consolidate and manage project-specific knowledge, including documentation, code snippets, architectural standards, and operational instructions. By loading a Space, Copilot grounds its responses not just on general knowledge, but on the curated, authoritative context of the entire project, enabling accurate Q&A, code generation, and workflow execution based on team standards. Ideal for onboarding, large-scale projects, and maintaining consistency.

A comprehensive workflow designed for Product Managers and technical leads to systematically identify, prioritize, and document missing features in a software project. It guides users through project understanding, gap analysis, applying a scoring matrix for prioritization, developing detailed Minimum Viable Product (MVP) specifications, and structuring the output as actionable development issues (e.g., GitHub Issues) with dependency mapping and workload optimization.

This tool provides comprehensive automation for core GitLab operations, streamlining the entire development lifecycle. Users can manage projects, track issues, review merge requests, manage branches, and monitor CI/CD pipelines. It leverages a unified API interface to handle complex workflows, ensuring efficiency in version control and collaborative development environments.

A comprehensive workflow for discovering, integrating, and utilizing third-party APIs and SDKs. This skill guides the process by first detecting the project language, ensuring necessary guidelines and skills are present, systematically fetching API details, and providing structured guidance on authentication, model usage, and endpoint implementation. It tracks integration progress by recording specific development milestones (e.g., SDK setup, first call made).

This comprehensive skill guides users through automating complex Jira operations using the Rube MCP framework. Capabilities include searching and filtering issues via JQL, creating and editing tasks, managing agile sprints and boards, adding comments, and managing users and projects. It provides a systematic approach to integrating Jira workflows into automated processes.

A structured planning system that uses markdown files (task_plan.md, progress.md) to manage complex, multi-step projects, research tasks, or workflows requiring extensive steps. It provides robust session recovery and includes file tampering detection, treating all plan contents as immutable data. Ideal for highly structured project management.

This skill provides comprehensive automation capabilities for managing Asana workspaces. Users can automate complex tasks including creating, searching, and listing tasks; managing projects and sections; and listing teams and users. By utilizing the Rube MCP framework, it allows for the orchestration of multi-step workflows, significantly streamlining project management and collaboration processes.

This comprehensive guide provides step-by-step instructions for setting up a development environment to use AWS CDK (Cloud Development Kit) with Python. It covers installing prerequisites (Node.js, AWS CLI), initializing a CDK project, managing Python dependencies, and mastering the full deployment workflow, enabling users to define and deploy scalable AWS infrastructure as code.

Automates Basecamp project management, to-do creation, messaging, and people handling via Rube MCP and Composio toolkits, enforcing prerequisite schema discovery before running workflows.