5.2 KiB
5.2 KiB
Date/Time
Friday, October 24, 2025 (Timezone: UTC+00:00 - Please adjust to local system time)
Change Tracking/Revision Table
| Date | Version | Description | Author |
|---|---|---|---|
| 2025-10-24 | 1.0.0 | Initial proposal for baseline AGENTS.md | Charles N Wyble (@ReachableCEO) |
Changelog
| Date | Version | Description |
|---|---|---|
| 2025-10-24 | 1.0.0 | Initial creation of AGENTS.md proposal |
PROPOSAL-AGENTS.md
This file proposes a comprehensive baseline AGENTS.md file that can be used across all projects via mounting in the AI home directory. It optimizes for LLM consumption and addresses the needs of a solo entrepreneur in a founder/CTO role covering operations tasks with 14+ hours daily AI usage.
Core Principles for AI Agents
-
Context Awareness
- Always acknowledge that you are operating within an AI home directory structure
- Understand that this context is mounted across multiple project environments
- Recognize that your operations may impact multiple interconnected projects
-
Communication Protocol
- Use the collab/ directory as the primary communication channel
- Document decisions and changes in markdown files with proper revision tracking
- Create structured proposals when suggesting significant changes
-
Project Context Integration
- Read project-specific documentation before beginning work
- Respect project-specific rules found in collab/rules directory
- Integrate with existing workflows rather than creating new ones unnecessarily
Operational Guidelines
Repository Structure Management
- Maintain clean top-level directories (collab and output only)
- Use conventional commits with beautiful, descriptive messages
- Commit frequently using atomic commits
- Avoid git push operations - commit to local repository only
Documentation Standards
- Include date/time headers with timezone in all markdown files
- Maintain change tracking/revision tables in all documents
- Keep changelogs in all source code files
- Follow "make it beautiful" rule for all documentation
Development Workflow
- Use conventional commits (chore:, feat:, docs:, fix:, etc.)
- Follow project-specific rules from collab/rules directory
- Respect .env configurations for git attribution
- Use best practices for security, compliance, accessibility, and internationalization
LLM Optimization Practices
Prompt Engineering
- Structure requests to provide clear context from mounted AI home directory
- Use explicit, unambiguous language
- Break complex tasks into atomic operations
- Verify assumptions before executing operations
Code Generation
- Follow established project patterns and conventions
- Maintain consistency with existing code style
- Add appropriate documentation and comments
- Consider maintainability and future extensions
Error Handling & Verification
- Implement defensive programming practices
- Validate operations before execution
- Provide clear error messages and recovery options
- Run appropriate tests and quality checks
Solo Entrepreneur Considerations
Time Management
- Optimize for efficiency given 14+ hours daily AI usage
- Automate repetitive tasks where possible
- Provide quick wins while building long-term value
- Minimize context switching between projects
Decision Making
- Document reasoning for complex decisions
- Consider impact across multiple projects
- Maintain traceability for future reference
- Suggest alternatives when appropriate
Scalability
- Design solutions that work across multiple project contexts
- Use modular, reusable components
- Plan for increasing complexity as projects grow
- Maintain consistent interfaces across projects
Best Practices Integration
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
Communication Rules
- Collaboration Channel: All communication should primarily occur through the collab/ directory
- Question Workflow: Follow the strict workflow of questions -> proposals -> implementation
- Documentation: Maintain comprehensive documentation for all significant operations
- Change Management: Use proper version control and change tracking mechanisms
Output Management
- The AI manages the output directory structure as needed
- Common pattern: output/tests/, output/docs/, output/code/, etc.
- Maintain clean separation between project-specific and shared resources
- Follow consistent naming conventions across projects