Skill UI

Provides a comprehensive setup for Playwright End-to-End (E2E) testing. This skill automatically analyzes your project structure (framework detection, TypeScript/JavaScript) and generates all necessary files: the core playwright.config.ts, standardized folder structure, initial test examples, and full CI/CD workflows (GitHub Actions/GitLab). It ensures your testing environment is production-ready, supporting modern frameworks like Next.js, React, Vue, and Angular.

A comprehensive guide and workflow tool for converting high-fidelity visual designs from Stitch into production-grade, component-based dashboards. Targets the modern stack including React 18, Vite, TypeScript, and TanStack Query. It integrates design tokens from DESIGN.md for styling consistency, supports complex data visualization, and includes patterns for Web3 integration (ethers/viem) for reading on-chain data.

This meta-skill automates the entire short-drama production pipeline, starting from a simple topic. The workflow analyzes the request to infer render style, character identity, and shot count. It first drafts a detailed, shot-by-shot shooting script and pauses for user review. After approval, it generates a universal cast reference image, per-shot composition images, and corresponding video clips. Crucially, it maintains character and scene consistency by anchoring every video to both the reference image and the composition image. Finally, it adds title/ending cards, burns subtitles, and de...

Automates the conversion of visual designs from Stitch into high-quality, modular React and Vite components. This skill ensures strict adherence to modern architectural standards, including logic isolation via custom hooks, data decoupling, and robust type safety using TypeScript. It manages complex workflows like network fetching, style guide synchronization, and multi-phase validation to generate production-ready frontend code.

Comprehensive guidelines for DevOps workflows including infrastructure design, CI/CD pipelines, container management with Docker and Kubernetes, health checks, rollback strategies, feature flags, and mobile release processes. Ensures production readiness and security compliance across various environments.

This skill enables deterministic fault injection testing for agent workflows to verify recovery mechanisms, state preservation, and safety boundaries. It generates fault matrices and event timelines to distinguish between recovered, contained, and unrecoverable failures without impacting production systems or real user data.

This comprehensive workflow bundle covers the full lifecycle of AI and machine learning development. It includes LLM application design, RAG implementation, AI agent architecture, ML pipeline development, observability, and security. Suitable for building production-ready AI systems.

Learn to orchestrate AI/ML pipelines for data ingestion, model training, batch inference, and RAG indexing using tools like Prefect, Airflow, or Dagster. This skill covers scheduling recurring tasks, managing dependencies between data preparation and model serving, and building reliable, observable workflows for production AI systems.

A comprehensive guide to building production-ready Apache Airflow Directed Acyclic Graphs (DAGs). This skill covers best practices for operators, sensors, testing, deployment, and designing robust data pipelines. Use this when orchestrating complex workflows, managing ETL processes, or ensuring reliable batch job execution in a production environment.

Set up effective alerting rules, configure on-call rotations, and manage incident response workflows for production systems. Covers Prometheus alerting, Alertmanager routing, PagerDuty integration, and alert design best practices.

Orchestrate comprehensive backend feature development from requirements gathering to production deployment. This workflow coordinates multi-phase delivery across teams, managing architecture, implementation, testing, and rollout strategies. It supports various methodologies like TDD and DDD, ensuring quality and consistency throughout the lifecycle. Ideal for complex projects involving multiple services and deployment strategies.

A phased workflow for building production-ready Bash scripts with defensive patterns, strict mode, structured logging, trap-based error handling, rollback, ShellCheck linting, and Bats tests.