2d-games
무료2D game development principles. Sprites, tilemaps, physics, camera.
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Use when designing human approval gates for high-stakes agent actions. Keywords: human-in-the-loop, HITL, approval gate, checkpoint, confirmation, risk-tiered, action review.
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설치 방법 보기설치하기 전에 에이전트에게 전달되는 지시 내용을 확인할 수 있습니다.
The "Human-in-the-Loop" (HITL) skill provides a standardized framework for integrating human oversight into agentic workflows. By tiering actions based on risk, we ensure autonomy is utilized safely for low-impact tasks while maintaining rigorous human control over high-impact operations. This skill aligns with the C4 Runtime Protocol to prevent "black box" agent behavior.
rm -rf, bulk overwrites).To manage friction, apply the appropriate gate based on the action category:
| Tier | Category | Mechanism | User UX |
|---|---|---|---|
| 0 | Informational | Auto-Approve | Logged in background/console. |
| 1 | Standard Edit | Warn/Confirm | Inline diff preview + "Proceed". |
| 2 | Destructive/Critical | Hard Gate | Explicit approval required; blocked until sign-off. |
| 3 | Financial/Deployment | Multi-Factor/Formal Audit | Requires explicit sign-off via UI/Artifact link. |
diff or specific "what is changing" summary before writing.ask_question tool or an artifact.HITL checkpoints are first-class citizens in C4:
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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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