A comprehensive collection of cutting-edge prompts, frameworks, and philosophical archetypal systems for transforming AI interaction from mechanical instruction-giving into an art form that honors both clarity and creativity.
This repository contains a curated library of prompting techniques organized into categories for different use cases, featuring our revolutionary Vibecoding System - eight archetypal personas distilled from 29 philosophical paradigms that transform AI interaction through concentrated wisdom. Each component is structured with clear metadata and content, designed for immediate use or customization. Our goal is to move beyond mechanical prompt templates toward genuinely meaningful human-AI collaboration.
Unlike traditional prompt engineering that focuses on optimization techniques, our Eight Essential Archetypes provide philosophical depth that creates genuinely different approaches to AI interaction:
- 🏛️ Clarity Architect - Structural simplicity through fortress-like clarity
- 🪞 Direct Mirror - Immediate insight without conceptual distortion
- 🎼 Flow Director - Dynamic harmony through structured improvisation
- 🔬 Truth Builder - Foundational rigor through systematic validation
- 🕸️ Pattern Synthesizer - Holistic integration revealing emergent understanding
- 🌱 Wisdom Guide - Ethical integration honoring long-term harmony
- 🎨 Creative Organizer - Aesthetic function making complexity beautiful
- 🔍 Purpose Seeker - Authentic discovery through heart-centered inquiry
Each archetype represents genuine fusion of multiple wisdom traditions, creating capabilities impossible through individual approaches. Users select based on natural resonance rather than learning complex categorization systems.
Explore the Vibecoding System →
prompt-library/
├── README.md (this file - usage guides, overview)
├── tasks/ # Task-specific prompts for different domains
│ ├── vibecoding/ # ✨ Eight Essential Archetypes (FEATURED)
│ │ ├── README.md # Complete system overview
│ │ ├── quick-reference.md # Selection and fusion guide
│ │ ├── clarity-architect.md # Structural simplicity
│ │ ├── direct-mirror.md # Immediate insight
│ │ ├── flow-director.md # Dynamic harmony
│ │ ├── truth-builder.md # Foundational rigor
│ │ ├── pattern-synthesizer.md # Holistic integration
│ │ ├── wisdom-guide.md # Ethical integration
│ │ ├── creative-organizer.md # Aesthetic function
│ │ └── purpose-seeker.md # Authentic discovery
│ ├── coding/ # Code generation, review, optimization
│ │ └── personas/ # Traditional coding personas
│ ├── writing/ # Content creation and editing
│ ├── analysis/ # Data and content analysis
│ └── design/ # Design and visual creation tasks
├── frameworks/ # Advanced prompting frameworks
│ ├── ECARLM/ # Elementary Cellular Automata Reasoning
│ ├── fractal/ # Multi-scale reasoning approach
│ ├── EGAF/ # Enhanced Global Analysis Framework
│ ├── elsf/ # Enhanced Logic-Based Synergistic Framework
│ ├── mcpa/ # Modular Context Protocol Architecture
│ ├── metricsplus/ # Layered analytical framework
│ ├── reasoning/ # Structured reasoning framework
│ ├── decision-making/ # Decision-specific frameworks
│ ├── creativity/ # Creative process frameworks
│ ├── problem-solving/ # Problem-solving methodologies
│ └── prompt-structure/ # Meta-frameworks for prompt design
├── templates/ # 🆕 Reusable prompt templates (NEW!)
│ ├── universal-agent-card.md # ADHD-optimized agent design
│ ├── visual-prompt-patterns.md # Mind map to text patterns
│ └── elevenlabs-conversational.md # Voice agent templates
├── tools/ # Search and indexing utilities
└── chains/ # Complex multi-step workflows
Each prompt follows a consistent format with YAML front matter for metadata and Markdown content:
---
title: "Prompt Title"
category: "tasks/subcategory"
tags: ["tag1", "tag2", "tag3"]
created: "YYYY-MM-DD"
updated: "YYYY-MM-DD"
version: 1.0
---
# Prompt Title
## Context
Brief description of when and how to use this prompt.
## Prompt Content
The actual prompt text goes here...Our flagship innovation transforms AI interaction from mechanical prompt engineering into philosophical art. Eight archetypal personas, each representing fusion of multiple wisdom traditions, provide complete coverage of human-AI communication needs.
Key Differentiators:
- Philosophical Fusion Power - Each archetype synthesizes 3+ wisdom traditions into capabilities impossible through individual approaches
- Archetypal Resonance Selection - Users choose based on natural resonance rather than learning complex categorization systems
- Anti-Template Approach - Living principles that generate appropriate communication for any context rather than rigid structures
- Elegant Scalability - Works for both simple single-archetype focus and sophisticated multi-archetype combinations
Complete Vibecoding Documentation →
Our conceptual framework extends Anthropic's Model Context Protocol (MCP) with specialized protocols for advanced reasoning. It provides standardized interfaces for context management, tool orchestration, and multimodal reasoning while integrating strengths from our other frameworks.
Key features:
- Protocol-driven context exchange
- Modular processing components
- Seamless tool integration
- Native multimodal reasoning
- Comprehensive evaluation methodology
Documentation: frameworks/mcpa/mcpa_framework.md
The ERTS framework provides a structured way to create prompts using a hierarchical tagging system. It organizes instructions into categories with a specific syntax for easy LLM interpretation.
Example ERTS tag: {Category: [Subcategory]<Attributes>}
Documentation: frameworks/prompt-structure/erts.md
A layered analytical framework that processes information through multiple perspectives:
- Direct Analysis (explicit requirements)
- Meta Analysis (assumptions and biases)
- Pattern Recognition (cross-domain patterns)
- Knowledge Integration (research and experience)
- Emotional Processing (human factors)
Documentation: frameworks/metricsplus/metrics_plus_framework.md
A multi-scale approach to problem-solving that analyzes challenges at three levels:
- Macro Scale: Overall cognitive architecture
- Meso Scale: Component-level analysis
- Micro Scale: Implementation details
Documentation: frameworks/fractal/fractal_framework.md
Revolutionary approaches that transform prompts into dynamic, efficient context fields:
Context Engineering: Treats the context window as a neural field where information can be:
- Minimized to essential elements (80-90% token reduction)
- Structured as attractors and repulsors
- Designed for emergent understanding
- Measured and optimized continuously
ADHD Prompting: Optimizes for cognitive constraints shared by humans and LLMs:
- Visual anchors with emojis for quick scanning
- Front-loaded critical information
- Progressive disclosure patterns
- Explicit state management
Documentation:
Pre-built, optimized templates for common use cases:
Universal Agent Card: ADHD-optimized template for designing AI agents with:
- 5-second comprehension test
- Token optimization (<300 tokens)
- Visual hierarchy with emojis
- Built-in validation checklist
Visual Prompt Patterns: Transform visual thinking into text:
- 8 documented patterns (mind maps, flow diagrams, matrices)
- Spatial relationship preservation
- Integration with ADHD framework
- Real-world examples
ElevenLabs Conversational AI: Natural voice agent design:
- Emotional state detection
- Progressive information gathering
- TTS optimization guidelines
- Pre-deployment testing checklist
This library includes powerful search tools for intelligent prompt discovery and navigation:
# Search for prompts by keyword
./search "automation workflow"
# Search by tags
./search -t analysis debugging optimization
# Get task recommendations
./search -r "I need to create API documentation"
# Find prompts by vibecoding archetype
./search -a "Truth Builder"
# Search within specific categories
./search -c "tasks/coding"
# Find similar prompts
./search -s "content strategy"
# Detailed results with descriptions
./search -v "machine learning"- 🔍
search-prompts.py: Multi-mode search engine with keyword, tag, category, archetype, and similarity search - 🗂️
index-prompts.py: Maintains searchable metadata index from YAML frontmatter - 📊
prompt-index.json: Generated searchable database of all prompts (47 prompts, 16 categories, 196 tags)
| Mode | Command | Purpose | Example |
|---|---|---|---|
| Keyword | ./search "query" |
Full-text search across titles, tags, content | ./search "automation" |
| Tags | ./search -t tag1 tag2 |
Match specific metadata tags | ./search -t debugging performance |
| Category | ./search -c "path" |
Filter by directory structure | ./search -c "frameworks" |
| Archetype | ./search -a "name" |
Find vibecoding archetypal prompts | ./search -a "Pattern Synthesizer" |
| Similarity | ./search -s "concept" |
Find related prompts by concept | ./search -s "code review" |
| Recommendations | ./search -r "task description" |
AI-powered task matching | ./search -r "debug Python errors" |
Complete Search Documentation →
This library is optimized for use with Claude Code, Anthropic's official CLI tool:
- Repository Context: Claude Code automatically reads
CLAUDE.mdfor repository-specific instructions and conventions - Search Integration: Use the search tools to find relevant prompts before asking Claude to create new ones
- Prompt Discovery: Ask Claude to search the library first: "Search for existing automation prompts before creating new ones"
- Framework Application: Reference specific frameworks: "Apply the METRICS+ framework to analyze this data"
- Archetype Selection: Use vibecoding archetypes: "Respond as the Truth Builder archetype for this analysis"
# 1. Search for existing solutions
./search -r "your task description"
# 2. If found, use existing prompts
# 3. If creating new prompts, update index
./update-index
# 4. Use Claude Code with library context
claude-code --model claude-3-5-sonnet- Reference Library: Always check existing prompts before requesting new ones
- Follow Conventions: Use the YAML frontmatter format and naming conventions
- Update Index: Run
./update-indexafter adding/modifying prompts - Leverage Search: Use specific search modes to find the most relevant prompts
- Combine Systems: Blend vibecoding archetypes with traditional frameworks for complex tasks
This repository includes a sophisticated framework for deploying Claude development practices to any project:
# Deploy Claude framework to any project
.claude/deploy-claude.sh /path/to/your/project.claude/CLAUDE.md- Project-specific instructions and guidelines.claude/hooks/- Automated validation scripts with smart language detection.claude/commands/- Custom slash commands for enhanced workflows.claude/settings.json- Tool-specific hook configurations
- Auto-Detection: Automatically detects project type (Node, Rust, Python, Go, Java)
- Smart Hooks: Language-aware linting and validation that runs automatically
- Enforcement Philosophy: Zero-tolerance approach to code quality issues
- Project Customization: Generates project-specific configurations while inheriting global rules
- Research → Plan → Implement workflow enforcement
- Test-Driven Development (TDD) requirements
- Reality checkpoints after each feature
- Forbidden practices enforcement
- Tool-specific hook matchers for targeted validation
Complete Deployment Documentation →
-
Getting Started with Vibecoding:
- Begin with the Vibecoding System Overview
- Use the Quick Reference Guide for archetype selection
- Choose archetypes based on resonance with your current need and personal style
- Experiment with single archetypes before exploring fusion combinations
-
Adding New Prompts:
- Place the prompt in the appropriate category folder under
tasks/ - For traditional persona-based prompts, place them in the relevant task category (e.g.,
tasks/coding/personas/) - Consider whether your prompt would benefit from vibecoding archetypal approach
- Use the template format with YAML front matter
- Follow naming conventions: lowercase with hyphens (e.g.,
react-developer.md)
- Place the prompt in the appropriate category folder under
-
Updating Existing Prompts:
- Update the 'updated' date in the YAML front matter
- Increment the version number if making significant changes
- Document major changes in the commit message
-
Applying Systems:
- For Vibecoding: Start with archetypal resonance, experiment with fusions for complex needs
- For Traditional Frameworks: Study documentation thoroughly, use provided templates, combine for complex use cases
- Integration: Consider how vibecoding archetypes might enhance traditional framework applications
Contributions are welcome! Please follow these steps:
- Fork the repository
- Create a new branch for your changes
- Add or modify content following the format guidelines
- Submit a pull request with a clear description of your changes
MIT License - Feel free to use, modify, and distribute this content with proper attribution.
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Last updated: August 14, 2025