2d-games
Free2D game development principles. Sprites, tilemaps, physics, camera.
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Automatic quality control, linting, and static analysis procedures. Use after every code modification to ensure syntax correctness and project standards. Triggers onKeywords: lint, format, check, validate, types, static analysis.
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See how to installReview the instructions the agent will receive before you install.
MANDATORY: Run appropriate validation tools after EVERY code change. Do not finish a task until the code is error-free.
npm run lint or npx eslint "path" --fixnpx tsc --noEmitnpm audit --audit-level=highruff check "path" --fix (Fast & Modern)bandit -r "path" -llmypy "path"npm run lint && npx tsc --noEmitlint fails: Fix the style or syntax issues immediately.tsc fails: Correct type mismatches before proceeding..eslintrc, tsconfig.json, pyproject.toml and suggest creating one.Strict Rule: No code should be committed or reported as "done" without passing these checks.
| Script | Purpose | Command |
|---|---|---|
scripts/lint_runner.py | Unified lint check | python scripts/lint_runner.py <project_path> |
scripts/type_coverage.py | Type coverage analysis | python scripts/type_coverage.py <project_path> |
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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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