agent-context-kit
🥈SilverAgent Context Kit provides a framework for AI coding agents to build Python backend services using Domain Driven Design and Hexagonal Architecture. It ensures consistent coding standards and patterns for agents like Cursor, Claude Code, and Windsurf. Benefits operations teams by accelerating development while maintaining high-quality, maintainable code.
4130Updated 2mo ago
Intermediate30min to implementautomation
Saves ~110 min per use
Quick InstallView Source
git clone https://github.com/bardiakhosravi/agent-context-kit.gitWorks with:
Claude
Overview
About This Skill
Tenets provides opinionated, battle-tested architectural rules that AI coding agents follow when building backend services using Domain-Driven Design and Hexagonal Architecture. It installs with a single CLI command and integrates with Claude Code, Cursor, GitHub Copilot, and custom agents to enforce consistent design patterns across generated code. By embedding DDD and Hexagonal Architecture context upfront, Tenets ensures AI-generated features respect domain boundaries, separate business logic from infrastructure, and maintain architectural compliance without manual enforcement. It extends Spec-Kit templates with DDD planning sections and includes a repository-local code review agent that inspects diffs against the Tenets rulebook. Development teams benefit from faster AI-assisted coding while maintaining predictable, reviewable, production-ready architecture.
How to Use
Install with `npx tenets init --claude` (or `--cursor`, `--copilot`, `--agents`) to add architecture rules to your project. Optionally add `--speckit` to extend your Spec-Kit templates with DDD sections. Run `npx tenets update` to refresh rules and integrations. For Claude Code with built-in code review, use `npx tenets init --claude --code-review-agent` which installs a PostToolUse hook.
Use Cases
Enforce consistent Hexagonal Architecture patterns across Claude Code, Cursor, and Copilot-generated code
Extend Spec-Kit planning templates with DDD bounded context and domain model sections
Run automated code review agents that verify AI-generated diffs against architecture rules
Prevent architectural drift by embedding design guardrails into agent instructions
Tags
Setup & Installation
Quick Install
No install command available. Check the GitHub repository for manual installation instructions.
Alternative Install (Git Clone)
git clone https://github.com/bardiakhosravi/agent-context-kitRequirements
- Claude Code or compatible AI agent
- Works with: Claude
Quick Start Guide
1
Install the Skill
Copy the install command above and run it in your terminal.
2
Open Your AI Agent
Launch Claude Code, Cursor, or your preferred AI coding agent.
3
Try It Out
Use the prompt template or examples below to test the skill.
4
Customize
Adapt the skill to your specific use case and workflow.
Usage Examples
Prompt Template
Create a Python backend service for [COMPANY] in the [INDUSTRY] sector using the Agent Context Kit. The service should handle [DATA] processing with the following requirements: [REQUIREMENTS]. Follow Domain Driven Design and Hexagonal Architecture principles. Provide the complete codebase with clear documentation.
Example Output
```python
# Domain Layer
class OrderService:
def __init__(self, order_repository):
self.order_repository = order_repository
def create_order(self, order_data):
# Business logic for order creation
order = Order(**order_data)
self.order_repository.save(order)
return order
# Application Layer
class OrderApplicationService:
def __init__(self, order_service):
self.order_service = order_service
def process_order(self, order_data):
# Application logic for order processing
order = self.order_service.create_order(order_data)
# Additional processing logic
return order
# Infrastructure Layer
class OrderRepository:
def save(self, order):
# Database operations for saving order
pass
# Main Application
if __name__ == '__main__':
order_repository = OrderRepository()
order_service = OrderService(order_repository)
order_application_service = OrderApplicationService(order_service)
order_data = {
'customer_id': '123',
'items': [
{'product_id': '456', 'quantity': 2}
]
}
order = order_application_service.process_order(order_data)
print(f'Order created: {order}')
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