2d-games
Free2D game development principles. Sprites, tilemaps, physics, camera.
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Flip core assumptions to reveal hidden constraints and alternative approaches - "what if the opposite were true?"
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See how to installReview the instructions the agent will receive before you install.
Flip every assumption and see what still works. Sometimes the opposite reveals the truth.
Core principle: Inversion exposes hidden assumptions and alternative approaches.
| Normal Assumption | Inverted | What It Reveals |
|---|---|---|
| Cache to reduce latency | Add latency to enable caching | Debouncing patterns |
| Pull data when needed | Push data before needed | Prefetching, eager loading |
| Handle errors when occur | Make errors impossible | Type systems, contracts |
| Build features users want | Remove features users don't need | Simplicity >> addition |
| Optimize for common case | Optimize for worst case | Resilience patterns |
Problem: Users complain app is slow
Normal approach: Make everything faster (caching, optimization, CDN)
Inverted: Make things intentionally slower in some places
Insight: Strategic slowness can improve UX
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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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