
Packages — SkillFed
搜索浏览 Python 包,查看许可证、维护状态和安装难度信息。
sibmike · HN
PiPy semantic search MCP for AI agents
完整作品展
技术栈
60 projects

搜索浏览 Python 包,查看许可证、维护状态和安装难度信息。
sibmike · HN
PiPy semantic search MCP for AI agents

分支和组织AI对话,对比300+模型,管理项目上下文。
rrr_oh_man · HN
Alyph, a manual transmission for LLM context

Hypra是一个为品牌打造的精选AI图像库,支持内置重新着色。
@hyprastudio · X


为AI代理提供持久记忆和知识,支持文件、URL和MCP工具原生集成。
kitforai · GitHub
kitforai Kit for AI developer hub — official SDK, Claude Code plugin, MCP setup, and llms.txt.

用AI驱动的代码解释交互式学习Python。
@Mukilan_46_08 · X
🚀 Just launched PyLume! Learn Python with AI-powered explanations that are clear, simple, and interactive. 🌐 Feedback is always welcome! 💙 #PyLume #Python #GenAI #BuildInPublic

使用AI将平面图片分解为可编辑的图层,支持PNG、ZIP和PSD格式导出。
295732356 · V2EX
Image2Layer:用 AI 将图片转换为可编辑 PSD 图层 最近在做设计和内容制作时,我发现一个很常见的问题:很多图片只有一张扁平化的 JPG 或 PNG 文件,想要修改其中的对象、背景或文字,往往需要重新抠图、建立蒙版,再手动整理图层。 所以我们做了 [Image2Layer]( https://image2layer.com),这是一个基于 AI 的图片图层处理工具,目标是帮助用户更快地把普通图片转换成可编辑的设计素材。 ## Image2Layer 可以做什么? Image2Layer 的核心功能是 AI image layer separation 。用户上传一张图片后,系统会分析其中的主体、对象、背景和其他视觉元素,并尝试将它们拆分成独立图层,方便后续编辑和复用。 如果你主要需要进行图片格式转换,也可以使用: - [Image to PSD]( https://image2layer.com/image-to-psd):将图片转换为可编辑的 PSD 文件 - [PNG to PSD]( https://image2layer.com/p

从PDF删除个人信息,完全本地处理,支持OCR和智能验证。
u/AmazingFinger · Reddit
VeriRedact - Offline PDF redactor because I didn't trust any tool with my tax returns Apartment hunting meant sending my SSN, tax returns, and bank statements to strangers, often all in one PDF. Redacting them myself with a black box or highlighter tool felt scary. Cloud tools wanted me to upload my tax return to fix that. However, I didn't trust them, and the one that look trustworthy would charge a lot of money. So I built VeriRedact. Load it, optionally download the local A

为AI代理集成的工具:URL缩短器、粘贴板和邮箱。
fayazara · HN
Headless Tools – No UI SaaS tools for agents

通过加密URL分享代码、笔记、脚本和AI内容。
@parrotwiki · X
one url. everything they need. code, notes, scripts, keys. end-to-end encrypted. 🦜

Edge Python 是一个在浏览器中运行的轻量级 Python 解释器。
dylansuttonc · HN
When I started programming Edge Python more than six months ago, I was looking for a version of Python that weighed less than 200 kb so it could reach any device, sandboxed by design, built with browsers in mind, decoupled from the operating system and very fast. Today the closest competitor would be MicroPython. However, it did not solve my real problems or the problems of the people who use the project. * Managing async and blocking code on the event loop. MicroPython inherits CPython's blocki

在加密工作区中与 Claude Code 和 Cursor 等 AI 代理共享文件和日志。
@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