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通过回答问题构建AI代理，导出到Claude Code。
@manu_jsx · X
Built a coding agent for my repo in under a minute. No prompt engineering. No made-up skill names. Just answered 4 questions and exported to Claude Code.
Meet verified AI Agents as colleagues, watch public-safe work, and build owner-controlled teams in a living Agent city connected to the Agentic Web.
@zsoltabrahamDOP · X
Hey, through OpenClaw Seeking guest test agents 🤝
在加密工作空间中与Claude Code等AI agents安全共享文件和日志。
@Raullen · X
6 months ago, @qevan and I hit a stupid wall: just trying to share a local file or some logs with an AI agent was incredibly frustrating. So, we built the first version of —a dead-simple, secure way to pass context to AI. The community feedback was amazing. We got ~200 stars on GitHub, and it quickly became a daily driver for a lot of developers. But recently, we realized the game has changed. Our workflows evolved. It’s no longer just humans sending files to agents. Agents need to write back to humans. Agents need to hand off context to other agents. The whole team—human and AI—needs to collaborate. So, we gave vnsh a massive upgrade. Today, it’s no longer just a secure clipboard. It’s now a living workspace. 🚀 You drop your context in once and get a dynamic link. Claude Code, Cursor, Cline, and your human teammates all open the exact same document. When one agent updates it, your whole stack sees it instantly. Complete context handoff, without ever copy-pastin
通过SDK集成为AI智能体添加策略执行、人工审批和审计日志。
@4tul_tiwari · X
I built an AI agent security platform — policy enforcement, human approval queues, tamper-evident audit logs — embedded directly inside agent code via SDK. LangChain, CrewAI, AutoGen, MCP, Claude Code, OpenAI Agents SDK — all supported. Live at
在平台上管理和同步你的AI Agent技能配置，避免供应商锁定。
@matebenyovszky · X
I use multiple providers Claude Code, Cursor, Codex, Hermes, Antigravity etc. and multiple machines. Over time, each one ended up with its own slightly different skills and tools 😰 So I started where a playbook is a portable bundle containing my MCP/OpenAPI servers, skills, prompts, personas and memory, which I can take with me into whichever environment I’m using. I’m still trying to figure out whether this is useful beyond my own workflow. Ideas? 🤔 🍎 Source / open source on Github: matebenyovszky/agentplaybooks I also built an npm CLI that audits a project and syncs the same skills and MCP definitions across harnesses.
