7.5 KiB
7.5 KiB
🤖 README-PROPOSAL-AGENTS.md
Beautiful documentation for AI Agent Guidelines Proposal
📋 Table of Contents
🧠 Overview
Welcome to the beautifully designed documentation for the PROPOSAL-AGENTS.md file. This document outlines a comprehensive baseline for AI agent operations that can be mounted across all your projects via your AI home directory.
| Attribute | Details |
|---|---|
| Purpose | Baseline AI agent guidelines for all projects |
| Target User | Solo entrepreneur (Founder/CTO/Operations) |
| AI Usage | Optimized for 14+ hours daily interaction |
| Structure | Mountable across multiple project environments |
🏗️ Proposal Structure
┌─────────────────────────────────────────────────────────────┐
│ PROJECT ENVIRONMENT │
├─────────────────────────────────────────────────────────────┤
│ ┌─────────────────┐ ┌─────────────────────────────────┐ │
│ │ │ │ │ │
│ │ PROJECT-SPECIFIC│ │ 🏠 AI HOME DIRECTORY │ │
│ │ CONTEXT │ │ (Mounted Volume) │ │
│ │ │ │ │ │
│ │ - Project docs │ │ - AGENTS.md (base rules) │ │
│ │ - Codebase │ │ - PROPOSAL-AGENTS.md │ │
│ │ - Requirements │ │ - Documentation Standards │ │
│ └─────────────────┘ │ - Operational Guidelines │ │
│ │ - LLM Optimization Practices │ │
│ └─────────────────────────────────┘ │
└─────────────────────────────────────────────────────────────┘
📁 File Location
AI-Home-Directory/
├── collab/ # Collaboration directory
│ └── proposals/ # Proposals subdirectory
│ ├── PROPOSAL-AGENTS.md # Baseline agent guidelines
│ └── README-PROPOSAL-AGENTS.md # This beautiful file
✨ Key Features
🎯 Core Principles for AI Agents
| Principle | Description |
|---|---|
| Context Awareness | Understand the mounted AI home directory across projects |
| Communication Protocol | Use collab/ directory as primary channel |
| Project Integration | Respect project-specific rules and workflows |
⚙️ Operational Guidelines
- Repository Management: Clean structure with conventional commits
- Documentation Standards: Date/time headers, revision tracking
- Workflow Adherence: Follow question -> proposal -> implementation
🧩 LLM Optimization Practices
- Prompt Engineering: Clear, structured requests
- Code Generation: Consistent with project patterns
- Error Handling: Defensive programming approach
📊 Implementation Guide
Step 1: Understanding the Framework
- Read Project Context → Always review project-specific documentation first
- Respect Existing Rules → Check collab/rules directory for project-specific guidelines
- Integrate with Workflow → Follow established patterns rather than creating new ones
Step 2: Following Documentation Standards
- Include date/time header with timezone
- Maintain change tracking/revision table
- Create changelog in source files
- Apply "make it beautiful" rule to all documentation
Step 3: Operational Excellence
- Use atomic commits with conventional commit messages
- Commit frequently to local repository
- Avoid git push operations (as per guidelines)
- Maintain clean top-level directory structure
🏆 Best Practices
🛡️ Security Practices
- 🔐 Verify file permissions and access controls
- 🛡️ Sanitize inputs and outputs appropriately
- 🔐 Protect sensitive information and credentials
- 🔒 Follow secure coding principles
📈 Quality Assurance
- ✅ Implement appropriate testing strategies
- ✅ Ensure code quality and maintainability
- ✅ Perform regular documentation updates
- ✅ Validate outputs against expected outcomes
⚡ Performance Considerations
- ⚡ Optimize for efficient processing
- 💾 Minimize resource usage where possible
- 📊 Consider impact on system performance
- 🔄 Implement caching strategies when appropriate
🚀 Solo Entrepreneur Optimization
For someone using AI 14+ hours daily with multiple projects:
| Need | Solution |
|---|---|
| Time Efficiency | Atomic operations, quick wins |
| Context Switching | Consistent interfaces across projects |
| Decision Documentation | Clear reasoning trails for complex decisions |
| Multi-Project Impact | Considerations for interconnected projects |
🤝 Communication Workflow
┌─────────────┐ ┌──────────────┐ ┌─────────────────┐
│ Question │ -> │ Proposal │ -> │ Implementation │
│ │ │ │ │ │
│ What to do? │ │ How to do it?│ │ Execute & Test │
└─────────────┘ └──────────────┘ └─────────────────┘
Primary Channels
- Collaboration: Use collab/ directory for all communication
- Documentation: Maintain comprehensive records
- Change Management: Use version control with proper tracking
💼 Founder/CTO Specific Considerations
Decision Making Framework
- 📊 Document reasoning for complex decisions
- 🔗 Consider impact across multiple projects
- 📜 Maintain traceability for future reference
- 🔄 Suggest alternatives when appropriate
Scalability Planning
- 🏗️ Design solutions that work across multiple project contexts
- 🧱 Use modular, reusable components
- 📈 Plan for increasing complexity as projects grow
- 🔗 Maintain consistent interfaces across projects
📈 Active Development Status
🔄 Note: This proposal is part of a living knowledge base that supports your 14+ hours daily AI usage.
Current Focus Areas
- Documentation standards
- Operational guidelines
- LLM optimization
- Integration patterns (planned)
- Performance metrics (planned)
📞 Getting Help
For questions about implementing these guidelines:
- Create a new issue in the collab/ directory
- Reference this proposal document
- Provide specific context about your use case
- Follow the established question -> proposal -> implementation workflow
Last updated: October 24, 2025
Part of the AIOS (AI Operating System) ecosystem
Optimized for solo entrepreneur workflows