CyberCode is an AI agent designed to overcome the limitations of stateless conversational AI, offering persistent memory, self-evolutionary capabilities, and efficient context management for coding tasks. It targets developers and power users seeking a more adaptive and context-aware AI assistant that learns user habits and project specifics across sessions, ultimately reducing development friction and improving efficiency.

How It Works

CyberCode integrates a Claude Code-style workflow with Hermes Agent's self-evolutionary principles. Its core innovation lies in moving beyond simple chat history by extracting stable user preferences and successful workflows into reusable "Skills," which remain visible and editable by the user. To combat context window limitations, it employs a multi-layered native token optimization stack: Code Graph understands code structure and relationships, RTK compresses diverse tool outputs (Git, Docker, etc.), and smart pruning removes redundant information. Additional optimizations like Lite, Caveman, and Lazy Programmer further reduce prompt noise and filler, aiming for efficient context utilization.

Quick Start & Requirements

• Installation: Download pre-built desktop applications for macOS, Windows, and Linux from the "Latest Release" page.
• User Guide: Detailed instructions are available at https://wk42worldworld.github.io/cybercode/.
• Prerequisites: Supports various model providers including Anthropic, OpenAI, Google, DeepSeek, Kimi, MiniMax, GLM, and OpenRouter (or compatible local endpoints) without requiring a separate LiteLLM proxy. Requires a compatible operating system (macOS, Windows, Linux).

Highlighted Details

• Unified Interface: The same local agent core and provider settings can be accessed via a Desktop GUI, terminal TUI, Telegram, or Feishu.
• Flexible Model Providers: A built-in protocol bridge simplifies configuration for numerous LLM providers and local endpoints.
• Advanced Token Optimization: Features Code Graph, RTK, smart pruning, Lite cleanup, and reuse-first coding strategies to minimize context window consumption.
• Open Source Core: The client, server, desktop app, adapters, memory system, and optimization stack are all open source, allowing for inspection and customization.

Maintenance & Community

The project provides a CONTRIBUTING.md file for potential contributors and links to an "Issues" tracker. Specific details regarding active maintainers, community channels (like Discord/Slack), or sponsorships are not detailed in the provided README excerpt.

Licensing & Compatibility

• License: MIT.
• Compatibility: The MIT license permits broad use, including commercial applications and linking within closed-source projects.

Limitations & Caveats

The README does not explicitly state limitations, alpha status, or known bugs. It emphasizes that the core behavior is inspectable and customizable, suggesting a focus on user control rather than inherent functional restrictions.