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.
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.
Top-tier contribution fork for smolagents: secure coded-agent patterns, MCP interoperability, and maintainer-friendly contributor guidance.
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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