Features
Detailed introduction to all features of AI Instruction Kits.
📚 Instruction Categories
1. System Management
Basic instructions to control AI behavior
- ROOT_INSTRUCTION.md - Operates as instruction manager
- INSTRUCTION_SELECTOR.md - Keyword-based automatic selection
- CHECKPOINT_MANAGER.md - Progress management system
2. General Tasks
General-purpose instructions for daily tasks
- basic_qa.md - Q&A, information provision
- Project management support
- Documentation assistance
3. Coding
Instructions specialized for programming tasks
- basic_code_generation.md - Basics of code generation
- Debugging support
- Refactoring guidance
- Test code creation
4. Writing
For document and content creation
- basic_text_creation.md - Basic text creation
- presentation_creation.md - Presentation structure
- Technical documentation
- Marketing content
5. Analysis
For data analysis and research tasks
- basic_data_analysis.md - Basics of data analysis
- Market research support
- Competitive analysis
- Performance analysis
6. Creative
Support for creative tasks
- basic_creative_work.md - Idea generation
- Design proposals
- Storytelling
- Brainstorming
7. Agent-based
Instructions to behave as specific experts
- python_expert.md - Python development expert
- code_reviewer.md - Code reviewer
- technical_writer.md - Technical writer
🔧 Core Features
Checkpoint Management
Automatically record and track work progress
# Task start
[1/5] Started | Next: Analysis
📌 Record→checkpoint.log: [timestamp][task ID][START] Task name
# Progress update
[3/5] Implementation complete | Next: Testing
📌 Record→checkpoint.log: Records only at start/error/completion
# Task completion
[✓] All complete | Result: Detailed results
Integration Modes
Choose based on project needs
Mode | Benefits | Use Cases |
---|---|---|
Copy | • No Git • Fastest setup • Offline support |
Small projects Non-Git environments |
Clone | • Full control • Custom modifications • History management |
Large customizations Custom instruction development |
Submodule | • Easy updates • Version control • Multi-project support |
Team development Long-term projects |
Custom URL Support
Use instructions from your own repository
# Corporate internal repository
--url https://gitlab.company.com/ai-team/instructions.git
# Personal fork
--url https://github.com/yourname/custom-instructions.git
# Private repository (requires authentication)
--url git@github.com:org/private-instructions.git
🎯 Advanced Usage
1. Creating Custom Instructions
# Custom Instruction Template
## Purpose
Clearly describe the purpose of this instruction
## Prerequisites
- Required knowledge
- Environment requirements
- Dependencies
## Specific Instructions
1. Detailed step 1
2. Detailed step 2
3. ...
## Expected Outcomes
- Deliverable 1
- Deliverable 2
---
## License Information
- **License**: [License name]
- **Author**: [Name]
- **Date**: [Date]
2. PROJECT.md Customization
Describe project-specific settings in detail:
## Project-specific Additional Instructions
### Architecture
- Microservices architecture
- API Gateway: Kong
- Message Queue: RabbitMQ
### Development Standards
- Commit messages: Conventional Commits
- Branch strategy: Git Flow
- Code review: Required (2+ reviewers)
### Security
- Authentication: OAuth 2.0
- Data encryption: AES-256
- Secret management: HashiCorp Vault
3. Pre-customizing Templates
# Edit templates
vi templates/en/PROJECT_TEMPLATE.md
# Add common settings applied to all new projects
- CI/CD configuration
- Standard lint rules
- Common test frameworks
🔒 Security Features
Private Repository Support
Securely retrieve instructions from organization-specific private repositories.
Implementation
# Example of internal repository
bash setup-project.sh --url https://github.com/company/private-ai-instructions.git
- Benefits: Securely manage organization-specific confidential instructions
- Use cases: Internal coding standards, proprietary business logic, security policies
SSH Authentication Support
Supports secure authentication using SSH keys.
Implementation
# Using SSH format URL
bash setup-project.sh --url git@github.com:company/private-instructions.git --submodule
- Benefits: Secure authentication without passwords, easy automation in CI/CD environments
- Prerequisites: SSH key setup required (
ssh-keygen
andssh-add
)
Access Token Support
Supports authentication using personal access tokens from GitHub/GitLab.
Implementation
# Embedding token in URL
bash setup-project.sh --url https://YOUR_TOKEN@github.com/company/repo.git
# Using environment variable (more secure)
export GIT_TOKEN=your_personal_access_token
bash setup-project.sh --url https://${GIT_TOKEN}@github.com/company/repo.git
- Benefits: Fine-grained permission control, expiration settings, minimal access rights
- Use cases: CI/CD environments, automation scripts, temporary access
Internal Network Support
Supports Git servers inside organizations not exposed to the internet.
Implementation
# Example internal GitLab server
bash setup-project.sh --url https://gitlab.company.local/team/ai-instructions.git
# Example internal Gitea server
bash setup-project.sh --url http://git.internal:3000/dev/instructions.git
- Supported servers: GitLab CE/EE, Gitea, Bitbucket Server, other Git-compatible servers
- Benefits: Completely internal operation, no external network required, high security
📦 Version Management
Version Pinning
Pin the version of instructions used in your project to prevent unexpected changes.
Implementation with Submodules
# Pin to specific commit
cd instructions/ai_instruction_kits
git checkout v1.2.3 # or specific commit hash
cd ../..
git add instructions/ai_instruction_kits
git commit -m "Pin instructions to v1.2.3"
- Benefits: Ensure reproducibility, stable operation, consistency across teams
- Use cases: Production environments, critical projects, auditable environments
Update Control
Manage instruction updates systematically and apply after testing.
Update Process
# Check latest version (without actually updating)
cd instructions/ai_instruction_kits
git fetch
git log HEAD..origin/main --oneline
# Apply update after testing
git pull origin main
cd ../..
git add instructions/ai_instruction_kits
git commit -m "Update instructions to latest version"
- Workflow:
- Test new version in development environment
- Review and confirm changes
- Gradually apply to staging → production
Rollback Feature
Instantly revert to previous stable version if issues occur.
Rollback Steps
# Revert to previous version
cd instructions/ai_instruction_kits
git checkout HEAD~1
cd ../..
git add instructions/ai_instruction_kits
git commit -m "Rollback instructions to previous version"
# Revert to specific stable version
cd instructions/ai_instruction_kits
git checkout v1.1.0 # Specific stable version
cd ../..
git add instructions/ai_instruction_kits
git commit -m "Rollback instructions to v1.1.0 (stable)"
- Benefits: Risk management, quick incident response, safe to try updates
- Recommendation: Test before and after rollback, record change history
📊 Usage Statistics and Metrics
Checkpoint Log Analysis
Quantitatively understand work progress and results.
Basic Statistics
# Total completed tasks
grep "COMPLETE" checkpoint.log | wc -l
# Check running tasks (incomplete)
grep "START" checkpoint.log | grep -v "COMPLETE"
# Today's task list
grep "$(date +%Y-%m-%d)" checkpoint.log
# Extract tasks with errors
grep "ERROR" checkpoint.log
Task Analysis Example
# Script example to calculate time per task ID
#!/bin/bash
while read -r line; do
if [[ $line =~ \[TASK-([a-f0-9]+)\] ]]; then
task_id="${BASH_REMATCH[1]}"
# Find START/COMPLETE pairs and calculate time difference
# (Implementation details omitted)
fi
done < checkpoint.log
Project Customization Analysis
Understand project characteristics from PROJECT.md contents:
# Check project settings
cat instructions/PROJECT.md | grep -E "(Build command|Lint command|Test framework)"
# Count customized items
grep -v "^#" instructions/PROJECT.md | grep -v "^$" | grep -v "Example:" | wc -l
Deliverable Quantification
Extract results from checkpoint log:
# Generate deliverable summary
grep "Result:" checkpoint.log | sed 's/.*Result: //' | sort | uniq -c | sort -nr
# Count created files, tests, etc.
grep "Result:" checkpoint.log | grep -E "[0-9]+ (files|tests|endpoints)"
🚀 Future Plans
Planned Features
🤖 AI-powered Instruction Generation
Automatically generate instructions for new categories by learning from existing ones
- Suggest optimal instructions by analyzing project characteristics
- Combine best practices from existing instructions
- Improve based on user feedback
🔍 Instruction Search and Filtering
Quickly find needed instructions even as they grow
- Tag-based classification system
- Keyword search functionality
- Dependency visualization
- Usage frequency-based recommendations
📝 Version Diff Display
Easily understand what changed during updates
- Highlight changed sections
- Impact analysis
- Decision support for rollback
🧪 Instruction Testing Framework
Ensure instruction quality
- Test cases for expected output
- Ambiguity checking
- Cross-AI compatibility testing
Community Contributions
- Adding new instruction categories
- Multi-language support (Chinese, Korean, etc.)
- Industry-specific template collections
- Best practice sharing