skill.color-expert

Kernel Memory is a reference implementation for turning documents into an AI memory layer through extraction, chunking, indexing, retrieval-augmented generation, and source citations. It can run as an asynchronous service or as an embedded component in .NET applications. The repository is archived and explicitly presented as unsupported research code, so it should be used for learning and architectural reference rather than production deployment.

This repository documents how Claude Code features work and packages the reverse-engineering process as a reusable skill. It extracts the embedded cli.js from the installed Bun binary, reformats the minified source, locates features through surviving string literals, annotates relevant code, and produces evidence-backed reports on commands, skills, agents, caching, and remote control; the workflow requires a local Claude Code installation and substantial source processing.

gophernotes adds a Go kernel to Jupyter Notebook and nteract, allowing live Go code to sit alongside equations, visualizations, and explanatory text in shareable documents. It evaluates code through the gomacro interpreter. On Windows, gomacro cannot use the required plugin support for third-party packages, so those notebooks should be run through the documented Docker setup.

AgentBench measures how well LLMs act autonomously across eight interactive environments, including database and operating-system tasks. The current repository carries a function-calling version integrated with AgentRL, while the older benchmark remains available as v0.1. Running the suite requires Docker, and Python 3.9 is recommended because several scientific dependencies are pinned to older versions.