agentware
NewFramework that makes your LLM self-aware, loops with self-learning and persistent memory that's private. Open-source & free.
Summary
Agentware is an open-source framework that equips LLMs with self-awareness, persistent memory, and self-learning capabilities, enabling them to autonomously improve over time.
- It provides a private, local memory system that allows agents to retain context across sessions, making it ideal for building long-running, adaptive AI assistants without relying on external cloud services.
Install & Usage
mkdir -p .claude/agentsAdd the configuration to .claude/agents/agentware.md
@agentwareUse Cases
Usage Examples
/agentware init --memory persistent --name my-assistant
/agentware learn from my previous conversations and improve your responses
Using agentware, create a self-learning agent that remembers my coding preferences and suggests improvements.
Security Audits
Frequently Asked Questions
What is agentware?
Agentware is an open-source framework that equips LLMs with self-awareness, persistent memory, and self-learning capabilities, enabling them to autonomously improve over time. It provides a private, local memory system that allows agents to retain context across sessions, making it ideal for building long-running, adaptive AI assistants without relying on external cloud services.
How to install agentware?
To install agentware: create the agents directory (mkdir -p .claude/agents), then add the config to .claude/agents/agentware.md. Finally, @agentware in Claude Code.
What is agentware best for?
agentware is a agent categorized under General. It is designed for: agent. Created by r5rana.
What can I use agentware for?
agentware is useful for: Build a personal AI assistant that remembers your preferences and past conversations across sessions.; Create a self-improving coding agent that learns from its own mistakes and adapts its behavior over time.; Develop a research assistant that accumulates knowledge from multiple queries and refines its answers based on previous interactions.; Implement a customer support bot that retains user history and continuously improves its responses without manual retraining.; Design a learning companion that tracks a student's progress and adjusts its teaching style based on past performance.; Construct a private, offline-capable agent for sensitive data processing where no external memory services are allowed..