Learning resourceResearch and knowledge

skill.color-expert

Give coding agents deeper color-science, accessibility, palette, and pigment-mixing expertise.

Learning resourceResearch and knowledge

skill.color-expert

Give coding agents deeper color-science, accessibility, palette, and pigment-mixing expertise.

Learning resourceResearch and knowledgeOpenAPI

kernel-memory

@microsoftC#

Study how to build document indexing, retrieval, and cited memory for AI applications.

Project overview

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.

Stars: 2,169
Forks: 400
License: MIT

Learning resourceResearch and knowledge

claude-code-reverse-engineering

@PrajwalsrinvasJavaScript

Extract and analyze Claude Code internals from its shipped native binary.

Project overview

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.

Stars: 3
Forks: 1
License: MIT

PluginResearch and knowledge

gophernotes

@gopherdataGo

Run and share interactive Go notebooks in Jupyter or nteract.

Stars: 3,965
Forks: 265
License: MIT

Benchmark or evalResearch and knowledge

AgentBench

@THUDMPython

Evaluate LLM agents across diverse interactive environments and tasks.

Project overview

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.

Stars: 3,557
Forks: 270
License: Apache-2.0

skill.color-expert

skill.color-expert

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