A repository of reusable prompts and best practices for building applications (ai optional LOL).
Context engineering optimizes AI outputs through structured prompt frameworks, RAG strategies, and system-level instructions. Rather than complex compute-heavy approaches, this library uses simple referencing (@ref syntax in most IDEs) to compose prompts dynamically.
- Reference framework files in your prompts using
{design},<design>, or similar delimiters - Combine pre-prompts with referenced content:
Use {design} when creating {concept}. <design>@design_prompt_1</design> - Pull repo into
/docsand start referencing
Design: Template-driven prompts for initial creation or element enhancement
Build: Technical scaffolding and project kickstarters aligned to designs
Judge: Critical evaluation prompts that challenge and iterate on existing work
Prompt/Context Engineering: Instruction clarity, context frameworks, output formatting, chain-of-thought, few-shot templates
Agent Rules: Command completion, response modifiers, tone/style, error handling, memory usage
RAG Optimization: Embedding patterns, retrieval strategies, context window utilization, chunking standards, relevance weighting
System Instructions: Agent behavior, tool protocols, safety guardrails, multi-agent coordination, response moderation
Language Rigidity: Semantic frameworks, domain terminology, context-sensitive patterns, precision/generalization balance
UX/UI Integration: Command center design, mobile/desktop optimization, visual cue integration, error standardization
Design Paradigms & Frameworks: Command interfaces, button mechanics, conversational UI, direct manipulation, form patterns, modal schemas
- Embed in system prompts
- Integrate with RAG systems
- Implement in frontend interfaces
- Fine-tune with rule-aware training
- Enforce via middleware
Submit PRs with:
- Established format adherence
- Compliance/violation examples
- Expected outcomes
- Related rule cross-references
2026 Q1: Design Frameworks, Framework Compatibility, Context/Agent Rules optimization
2026 Q2: UI/UX Integration
2026 Q3: Language Rigidity, RAG Optimization
2026 Q4: System Prompts
Main changes: Removed informal language, restructured for clarity, tightened descriptions, moved roadmap context into structured timeline, eliminated redundancy between sections.