2d-games
Free2D game development principles. Sprites, tilemaps, physics, camera.
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Architectural decision-making framework. Requirements analysis, trade-off evaluation, ADR documentation. Use when making architecture decisions or analyzing system design.
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"Requirements drive architecture. Trade-offs inform decisions. ADRs capture rationale."
Read ONLY files relevant to the request! Check the content map, find what you need.
| File | Description | When to Read |
|---|---|---|
context-discovery.md | Questions to ask, project classification | Starting architecture design |
trade-off-analysis.md | ADR templates, trade-off framework | Documenting decisions |
pattern-selection.md | Decision trees, anti-patterns | Choosing patterns |
examples.md | MVP, SaaS, Enterprise examples | Reference implementations |
patterns-reference.md | Quick lookup for patterns | Pattern comparison |
| Skill | Use For |
|---|---|
@[skills/database-design] | Database schema design |
@[skills/api-patterns] | API design patterns |
@[skills/deployment-procedures] | Deployment architecture |
"Simplicity is the ultimate sophistication."
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2D game development principles. Sprites, tilemaps, physics, camera.
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3D game development principles. Rendering, shaders, physics, cameras.
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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.
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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.
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Use when monitoring, tracing, or debugging agentic workflows in production. Keywords: observability, tracing, OpenTelemetry, Langfuse, latency, token cost, loop detection, telemetry.
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Use when building self-correcting retrieval systems for AI agents. Keywords: RAG, retrieval, Corrective RAG, Self-RAG, query decomposition, reranking, hallucination, grounding.
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