2d-games
無料2D game development principles. Sprites, tilemaps, physics, camera.
日本語の概要は準備中です。原文の説明を表示しています。
Use the Figma MCP server to fetch design context, screenshots, variables, and assets from Figma, and to translate Figma nodes into production code. Trigger when a task involves Figma URLs, node IDs, design-to-code implementation, or Figma MCP setup and troubleshooting.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Use the Figma MCP server for Figma-driven implementation. For setup and debugging details (env vars, config, verification), see references/figma-mcp-config.md.
These rules define how to translate Figma inputs into code for this project and must be followed for every Figma-driven change.
references/figma-mcp-config.md — setup, verification, troubleshooting, and link-based usage reminders.references/figma-tools-and-prompts.md — tool catalog and prompt patterns for selecting frameworks/components and fetching metadata.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
2D game development principles. Sprites, tilemaps, physics, camera.
日本語の概要は準備中です。原文の説明を表示しています。
3D game development principles. Rendering, shaders, physics, cameras.
日本語の概要は準備中です。原文の説明を表示しています。
Create aesthetically beautiful interfaces following proven design principles. Use when building UI/UX, analyzing designs from inspiration sites, generating design images with ai-multimodal, implementing visual hierarchy and color theory, adding micro-interactions, or creating design documentation. Includes workflows for capturing and analyzing inspiration screenshots with chrome-devtools and ai-multimodal, iterative design image generation until aesthetic standards are met, and comprehensive design system guidance covering BEAUTIFUL (aesthetic principles), RIGHT (functionality/accessibility), SATISFYING (micro-interactions), and PEAK (storytelling) stages. Integrates with chrome-devtools, ai-multimodal, media-processing, ui-styling, and web-frameworks skills.
日本語の概要は準備中です。原文の説明を表示しています。
Use when implementing or managing persistent, hierarchical memory systems for AI agents. Covers cross-session state, fact supersession, and self-managed memory tools to enable long-term recall and adaptive agent behavior.
日本語の概要は準備中です。原文の説明を表示しています。
Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.
日本語の概要は準備中です。原文の説明を表示しています。
Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.
日本語の概要は準備中です。原文の説明を表示しています。