headroom: Headroom is a context compression layer designed for AI agents and LLMs, significantly reducing token usage (60-95% fewer tokens) by compressing tool outputs, logs, RAG chunks, files, and conversation history. It operates locally and reversibly, ensuring data privacy and the ability to retrieve original content on demand.; antigravity-workspace-template: This project provides a production-grade workspace template for building autonomous AI agents on Google Antigravity, aiming to simplify enterprise-grade architecture to 'Clone → Rename → Prompt'. It pre-embeds a complete cognitive architecture, enabling the IDE to act as an industry-savvy architect with features like infinite memory, auto-discovery of tools, and multi-agent orchestration.
Optimizing AI Coding Agent Workflows: Significantly reduce token costs and improve efficiency when using agents like Claude Code, Cursor, or Aider for daily coding tasks.
Rapid prototyping and development of autonomous AI agents.