frontend▌

Maintain consistent character appearance across AI-generated images using reference sheets and detailed descriptions. \n \n Create turnaround sheets (front, 3/4, side, back views), expression sheets (6+ emotions), outfit variations, and color palettes to document character design \n Use a 50+ word detailed description anchor reused exactly in every prompt as the most practical consistency technique for small projects \n Train character-specific LoRA models for projects requiring many images, wit

Server Components use DIFFERENT navigation methods than Client Components!

Complete guide for scripting, producing, and assembling explainer videos via inference.sh CLI. \n \n Provides three script formulas (Problem-Agitate-Solve, Before-After-Bridge, Feature Spotlight) with timing breakdowns, word counts, and pacing rules for 30–120 second videos \n Covers scene generation via video AI models, voiceover production with TTS, music ducking, and caption integration through a multi-step assembly pipeline \n Includes practical tables for pacing (120–170 wpm by content type

Research a codebase and produce an architectural document describing how features or systems work. The output is a markdown file organized for both human readers and future AI agents.

Related Skills: See query-layer for TanStack Query integration. See styling for CSS and Tailwind conventions.

Problem: Causes all nodes to re-mount on every render.

Use this skill when you need to:

The progressive JavaScript framework for building modern web UI.

This skill provides a structured workflow for translating Figma designs into production-ready code with pixel-perfect accuracy. It ensures consistent integration with the Figma MCP server, proper use of design tokens, and 1:1 visual parity with designs.

Look up Gemini API documentation and SDK patterns when building with Google Gemini. This skill brings Gemini docs TO Claude — it does not call Gemini.