super-claude-kit

🥈Silver

Transform Claude Code from stateless to stateful with persistent context memory. Cross-session persistence, token-efficient storage, and zero dependencies. Ideal for developers building AI assistants and workflows that require long-term context.

65100Updated 1w ago

Intermediate30min to implementautomation

Saves ~240 min per use

Quick InstallView Source

git clone https://github.com/arpitnath/super-claude-kit.git

Works with:

Claude

Overview

About This Skill

The super-claude-kit is an innovative Claude Code skill designed to transition your AI from a stateless to a stateful architecture. By implementing a persistent context memory system, this skill allows for cross-session persistence and token-efficient storage, ensuring that your AI agent can remember previous interactions and maintain context over time. This enhancement is crucial for applications that require continuity in user interactions, making it a powerful tool for developers and product managers focused on creating more intuitive AI experiences. One of the key benefits of the super-claude-kit is its ability to save time and enhance productivity in AI automation workflows. While specific time savings are currently unknown, the implementation of this skill can significantly reduce the need for repetitive context-setting in user interactions, allowing AI agents to respond more accurately and efficiently. This not only streamlines the development process but also improves user satisfaction by providing a more seamless experience. This skill is particularly suited for developers, product managers, and AI practitioners who are looking to enhance their AI agents with advanced memory capabilities. Whether you're working on customer support bots, personal assistants, or any application that benefits from stateful interactions, the super-claude-kit can elevate your project. For instance, in a customer support scenario, an AI agent equipped with this skill can remember past issues and resolutions, leading to quicker and more relevant responses. The implementation of the super-claude-kit is classified as intermediate in difficulty, requiring about 30 minutes to integrate into existing workflows. It has no dependencies, making it easy to adopt within various AI-first environments. As businesses increasingly rely on AI automation to improve efficiency, incorporating this skill into your AI agent's capabilities can significantly enhance its effectiveness, ensuring that it remains relevant and responsive to user needs.

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/arpitnath/super-claude-kit

Requirements

Claude Code or compatible AI agent
Works with: Claude

Quick Start Guide

Install the Skill

Copy the install command above and run it in your terminal.

Open Your AI Agent

Launch Claude Code, Cursor, or your preferred AI coding agent.

Try It Out

Use the prompt template or examples below to test the skill.

Customize

Adapt the skill to your specific use case and workflow.

Usage Examples

Prompt Template

I'm building an AI assistant that needs to maintain context across multiple sessions. Here's the initial context: [INITIAL_CONTEXT]. The assistant will interact with users over time, and I need to store the conversation history and any important details. The assistant will handle [SPECIFIC_TASKS]. Can you help me implement a stateful version of this using super-claude-kit?

Example Output

To implement a stateful AI assistant using super-claude-kit, you'll need to follow these steps:

1. **Initialize the Stateful Assistant**:
```python
from super_claude_kit import StatefulAssistant

# Initialize with your initial context
assistant = StatefulAssistant(initial_context="[INITIAL_CONTEXT])")
```

2. **Define Your Tasks**:
```python
@assistant.task
def handle_user_request(user_input):
    # Your logic here
    return response
```

3. **Store and Retrieve Context**:
```python
# Store context
assistant.store_context("key", "value")

# Retrieve context
context_value = assistant.retrieve_context("key")
```

4. **Handle Conversations**:
```python
# Start a new conversation
conversation_id = assistant.start_conversation()

# Add messages to the conversation
assistant.add_message(conversation_id, "user", "Hello, how can you help me?")
assistant.add_message(conversation_id, "assistant", "I can help with [SPECIFIC_TASKS]. What do you need?")

# Retrieve conversation history
history = assistant.get_conversation_history(conversation_id)
```

5. **Persist and Load State**:
```python
# Persist the state
assistant.persist_state("path/to/state.json")

# Load the state
assistant.load_state("path/to/state.json")
```

This example demonstrates how to create a stateful AI assistant that can maintain context across multiple sessions, handle specific tasks, and persist its state for future use.