从零构建 AI Agent——每一步都有源码，每一章都能运行，渐进式理解智能体。Build an AI Agent from Scratch — Learn AI Agents step by step with runnable source code.
CXS is a deterministic continuity standard for long-range, multi-session, and long-chat LLM reasoning. It enables GPT, Claude, Grok, Gemini, and local models to share state through a human-readable Continuity Passport with strict-mode rules, drift detection/repair, and full chain-of-custody. Validated across 250+ continuity tests.
Local-first LLM operating-system hub for BACH, Rinnsal, gardener, SQLite agent memory, MCP servers, skills, and multi-agent orchestration
Local-first Python toolkit for parallel Claude and LLM agent orchestration: consensus voting, stigmergy, boss-worker swarms, and benchmarks
This repository showcases a variety of AI agent implementations, ranging from chat applications and RAG (Retrieval-Augmented Generation) pipelines to specialized MCP (Model Context Protocol) servers.
Top-tier contribution fork for smolagents: secure coded-agent patterns, MCP interoperability, and maintainer-friendly contributor guidance.
an example project demonstrating how to build, define, and integrate custom skills with the Google ADK (Agent Development Kit) 2.0 framework. The repository features a step-by-step implementation of a Python-based agent (skills_app/agent.py) that programmatically invokes external skill scripts (such as a lucky color lookup) to handle user prompts.
From zero-shot prompts to multi-agent loops — the complete progression of AI engineering in 2026. 7 levels, runnable Python code, real patterns used in production systems.
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