开发者工具1 week ago · 1 次试用
Kit for AI — The Memory Layer for AI Agents
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。
Open source
kitforai · GitHub
kitforai Kit for AI developer hub — official SDK, Claude Code plugin, MCP setup, and llms.txt.
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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.
Solvo：将你的文档转化为AI客服聊天小组件，自动回答客户问题并引用来源。
@dhruvkumar1805 · X
基于您的知识库的AI办公助手，自动化编码、研究和演示任务。
zhiheng_huang · HN
Sharper – an AI office agent grounded in your knowledge, with citations
发现和分享 AI 代理技能，支持 Claude、Cursor 等多个平台
Skills.lc — AI 技能、Prompt、工作流和 Agent 分享平台，帮助发现和沉淀 AI 使用经验
TODO for AI - 自动化邮件、文档检索和发票等日常公司任务的AI代理。
@cviklihamar · X
here 🙌 let's connect! - an ai agent that clears your team's todos (ships code, runs your tools). let's connect!
按职业场景语义搜索 AI Skills，保存收藏集，一键装入 Claude Code。
SkillForge — Claude Skill 发现与分发平台，按职业场景组织 5700+ skill 覆盖 30 个垂直领域，一行命令装到 Claude Code / Cursor，登录后可留存自己的工具集
AI Todo 用智能方式将目标分解为可行步骤，优化任务优先级。
AI Todo — 像很多程序员一样，我日常要兼顾工作任务、生活琐事、项目计划，时常感到事情多但漏掉的也不少。想用智能方式管理这些待办，但市面上的工具要么设计臃肿，要么 AI 能力很弱。于是我花了几周开发了 AI Todo，目标是:
向 QWQ AI 提问，获得详细推理答案，无需登录。
QWQ AI Assistant — 免费提供经过深思熟虑且富有详细推理的答案的 AI 助手，不需要登录
Unrot：每日编程挑战助你保持开发技能敏锐，享受AI辅助和连续打卡。
u/Administrative_Egg78 · Reddit
I built this because AI was making me a dumb&lazy engineer I noticed something sad about how I use AI. I was shipping faster, but practicing less. I could get answers quickly, but I was losing the habit of working through the fundamentals myself. So I built Unrot: short daily challenges for developers across languages, system design, architecture, data engineering, and other tracks. Game/xp and rewards system, a tiny bit competitive. No signup required to try it: https://unrot.dev
与多个 AI 模型聊天，进行深度研究和编码任务。
@Shekar77hima · X
run deepresearch, coding agents for free.
使用在微虚拟机中运行代码的AI代码审查来捕获更多漏洞。
u/dumbfoundded · Reddit
Ito, AI Code Review that Runs Code I've been using AI code review tools but none of them actually run code so I built one: https://www.ito.ai/ The way it works is that it uses microVMs to spin up your environment with all of the services running. Then a bunch of AI agents go and test the application to collect runtime evidence. The result is you get test cases along with evidence about whether or not the test cases pass or fail. The runtime evidence can be videos, request/response curls, db
