Skill UI

A comprehensive guide for improving application speed across the entire stack, including frontend rendering, backend logic, and database queries. It outlines the crucial workflow—Measure, Identify, Fix, Verify—and addresses common bottlenecks like N+1 queries, Core Web Vitals improvements (LCP, INP, CLS), and large data handling.

Guides HR coordinators through onboarding, announcements, and employee communications by orchestrating Gmail, Calendar, Drive, and Chat workflows—creating orientation events, uploading documents, announcing hires, and turning emails into tracked tasks.

This guide details how to systematically decompose large specifications or features into small, manageable, and verifiable tasks. It outlines best practices for vertical slicing, mapping component dependencies, and defining clear acceptance criteria. Use this process to ensure complex development work is broken down into reliably executable steps, suitable for agents or teams.

This comprehensive guide teaches the correct usage of the Flutter `provider` package for state management. It covers setting up various provider types (immutable, mutable, future, stream) and emphasizes best practices for consuming state safely using `context.watch`, `context.read`, and `Selector`. Learn how to use `ProxyProvider` for dependency injection and maintain robust, scalable Flutter applications.

Master advanced state management using Riverpod in Flutter and Dart. This guide covers setting up providers, defining different provider types (Future, Stream), utilizing reactive reading (ref.watch) and one-time access (ref.read), handling lifecycles, combining providers, and implementing proper testing strategies. Learn best practices for building scalable and maintainable Flutter applications.

A comprehensive guide to safely deploying new features to production. This methodology emphasizes moving beyond simple deployment by incorporating a detailed pre-launch checklist (covering security, performance, and accessibility), utilizing feature flags, and executing staged rollouts (Canary releases). It details best practices for observability, monitoring key metrics, and planning effective rollbacks.

A comprehensive workflow for the full lifecycle management of AI skills. This tool guides users through creating skills from scratch, modifying existing ones, and rigorously benchmarking performance. It supports iterative refinement, quantitative evaluation, and optimizing skill descriptions for maximum triggering accuracy.

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.

Guides zero-to-live Star Office visualization for Aion/OpenClaw by installing, starting, connecting, and troubleshooting the local UI service, checking ports/auth, and offering alternative open-source monitors when needed.

This skill generates highly structured DESIGN.md files, acting as a semantic design system for Google Stitch. It translates complex, anti-generic frontend principles—including typography, color calibration, component behavior, and motion physics—into actionable, natural-language rules. Use it as the single source of truth to guide AI in generating premium, non-clichéd, professional user interfaces.

This meta-skill set provides a structured framework covering the entire software development lifecycle (SDLC). It guides developers through every phase, from initial concept refinement and requirement specification to incremental implementation, testing, code review, and deployment. It enforces critical professional behaviors like surfacing assumptions, managing ambiguity, and maintaining scope discipline to ensure high-quality, robust engineering outcomes.

This skill enables the generation of high-quality, cinematic videos using a highly structured prompt format (JSON). Users define detailed cinematic elements—including background, characters, camera movements, dialogue, and audio—and can optionally provide a reference image to guide the visual style or content of the final output. It automates the complex AIGC video generation workflow.