A thin orchestration dashboard over Claude Code for managing context, automation, and developer headspace. You need tentacles. 🦑
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Updated
Apr 20, 2026 - TypeScript
A thin orchestration dashboard over Claude Code for managing context, automation, and developer headspace. You need tentacles. 🦑
《动手学 Pi》:沿 15 个真实 checkpoint 从零构建 Pi-style Agent
open source agent engineering platform: traces, evals, and metrics to debug and improve your AI agents. Integrates with LangGraph, CrewAI, Claude Agent SDK, and more.
Pixelagent — Multimodal stateful agents
BuildArena, where LLM agents design, build, and test rockets, cars, and bridges in a physics simulator given a goal-directed sentence.
AI Agent 面试知识库:覆盖 LLM、Prompt、RAG、MCP、Tool Use、Agent 架构、Multi-Agent、LangGraph、Claude Code、Codex CLI、工程化评估、安全与源码解析。
Deploys your OS, databases, and SSL on your VPS in just 10 minutes. Orchestrates a team of AI agents for coding, marketing, and sales. The built-in optimizer saves up to 90% on token costs, letting you build and manage your online business directly through chat. Fully open-source.
《智能体工程:从一句话到一个闭环》(Prompt · Context · Harness · Loop),本书将大语言模型驱动的智能体系统拆解为四种递进的工程范式,四种范式从 Token 到 System,从一次调用到完整的自主闭环,构成了智能体系统的完整工程视图。
SuperOptiX: Full Stack Agentic AI Framework
Agentic Testing Harness
The AI engineer roadmap for agent builders: a staged path with runnable labs to build a coding agent from scratch - by AI Builder Club
Claude Code 完整教學講義:從入門到 Harness Engineering,以五層進化模型為骨架的 23 章系統化課程
Multi-agent orchestration for VS Code Copilot, Claude Code, OpenAI Codex and Cursor
Bilingual hands-on roadmap for production-aware AI agents: MCP, memory, RAG, workflows, evaluation, safety, and agent colonies.
Application for Agent re-engineering for better and reliable Gen AI workflows.
Research and learning toward a future-facing agent system for governing wishes across the Agent Engineering Stack.
Interactive AI concepts lab — hands-on demos from LLM fundamentals to agent engineering, built on a director-style demo framework. 互動式 AI 教學實驗室,每個概念都能親手玩。
The meta layer behind AI skills. Persistent behavioral overlays that make expected agent conduct explicit across changing tasks and capabilities.
面向 Coding Agent 开发者的中文工程知识库与变更情报站
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