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🚀 Meet Panniantong/Agent-Reach: a gem from today's GitHub trending list.

🔗 https://github.com/Panniantong/Agent-Reach
📝 Give your AI agent eyes to see the entire internet. Read & search Twitter, Reddit, YouTube, GitHub, Bilibili, XiaoHongShu — one CLI, zero API fees.
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Agent Reach 是一个让 AI Agent 拥有互联网能力的工具。它通过一键安装，让你的 AI Agent 可以读网页、搜索 Twitter、看 YouTube、刷小红书 等。

它的关键特点包括：
- 完全免费：所有工具开源，所有 API 免费
- 隐私安全：Cookie 只存在你本地，不上传不外传
- 持续换代：每个平台都是「首选 + 备选」多后端路由

使用方法非常简单：
- 安装：帮我安装 Agent Reach：https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/install.md
- 更新：帮我更新 Agent Reach：https://raw.githubusercontent.com/Panniantong/agent-reach/main/docs/update.md

支持的平台包括：
- 网页
- YouTube
- RSS
- 全网搜索
- GitHub
- Twitter
- B站
- Reddit
- 小红书
- LinkedIn

技术亮点是：
- 每个平台 = 首选 + 备选的有序后端列表
- agent-reach doctor 告诉你每个渠道的状态

适合的受众是：
- AI 爱好者
- 研发人员
- 互联网企业

一句话总结：Agent Reach 让你的 AI Agent 拥有互联网能力，简单、免费、安全。

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⚡ meshery/meshery is making waves. Here's the full picture.

🔗 https://github.com/meshery/meshery
📝 Meshery, the cloud native manager
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Meshery is a cloud native manager that enables the design and management of Kubernetes-based infrastructure and applications. It offers visual and collaborative GitOps, freeing you from YAML while managing multi-cluster deployments. Key features include infrastructure lifecycle management, multiple Kubernetes clusters and clouds, and visually managing infrastructure. Meshery provides a single pane of glass to manage multiple clusters and supports 380+ integrations. It's perfect for teams looking to collaborate on cloud native projects with features like Workspaces and Environments. With Meshery, you can manage your connections and credentials with ease and preview changes to your infrastructure before merging. Meshery is a self-service engineering platform that simplifies cloud native management - try it now and transform your cloud native experience!

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🧠 Channel: https://xn--r1a.website/GithubRe

🌟 obra/superpowers caught my eye on GitHub Trending today.

🔗 https://github.com/obra/superpowers
📝 An agentic skills framework & software development methodology that works.
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Superpowers is a software development methodology that transforms your coding agents into powerhouses. Its purpose is to make your agent use composable skills and initial instructions to ensure effective coding. The key features include brainstorming, test-driven development, systematic debugging, and collaboration tools.

To use Superpowers, you can install it via various platforms like Claude Code, Antigravity, Codex App, and more. The installation process differs depending on the harness you use.

From a technical standpoint, Superpowers uses a skills library that includes testing, debugging, collaboration, and meta skills. It also emphasizes test-driven development, systematic over ad-hoc approaches, complexity reduction, and evidence over claims.

The target audience for Superpowers includes coding agents, developers, and anyone looking to streamline their coding process.

In a nutshell, Superpowers is a game-changer for coding agents - with Superpowers, your agent doesn't just write code, it crafts solutions.

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💡 google-research/timesfm just hit the trending charts — here's why it matters.

🔗 https://github.com/google-research/timesfm
📝 TimesFM (Time Series Foundation Model) is a pretrained time-series foundation model developed by Google Research for time-series forecasting.
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Introducing TimesFM: a pretrained time-series foundation model developed by Google Research for time-series forecasting.

The model is pretrained and available for use, with a paper detailing its development and capabilities. TimesFM has been integrated into various Google products, including BigQuery ML and Google Sheets, for easy access and scalability.

To get started with TimesFM, you can install it via PyPI using pip install timesfm[torch] or pip install timesfm[flax]. The model also supports XReg for covariate support.

Some of the key features of TimesFM include:
- ForecastConfig for customizing forecasting settings
- Support for continuous quantile forecast
- Flax version for faster inference

Here's an example of how to use TimesFM:

import torch
import numpy as np
import timesfm

model = timesfm.TimesFM_2p5_200M_torch.from_pretrained("google/timesfm-2.5-200m-pytorch")
model.compile(timesfm.ForecastConfig(...))
point_forecast, quantile_forecast = model.forecast(...)

TimesFM is suitable for data scientists, researchers, and developers working with time-series data.

One-liner takeaway: TimesFM makes time-series forecasting more accessible and scalable, and is a game-changer for anyone working with time-series data.

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🧠 Channel: https://xn--r1a.website/GithubRe

🔥 RocketChat/Rocket.Chat is trending — and it deserves your attention.

🔗 https://github.com/RocketChat/Rocket.Chat
📝 The Secure CommsOS™ for mission-critical operations
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Rocket.Chat is an open-source, secure communications platform for teams, developed in TypeScript. It offers real-time conversations, file sharing, and audio/video conferencing. With end-to-end encryption and role-based access control, it ensures data protection.

Key features include deployment flexibility, customizable workspaces, and integration with external systems. Rocket.Chat supports various deployment methods, including Docker, Podman, and Kubernetes.

The platform is used by millions of users worldwide, including organizations like Deutsche Bahn and Credit Suisse. It has desktop and mobile apps for seamless communication.

Rocket.Chat is designed for teams, organizations, and developers looking for a secure and customizable communication solution.

With a strong focus on community involvement and open-source development, Rocket.Chat is a platform that's constantly evolving.

Rocket.Chat is the ultimate secure communication solution for teams - join the community and experience it for yourself!

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🧠 Channel: https://xn--r1a.website/GithubRe

🎯 continuedev/continue landed on trending. Worth a proper look.

🔗 https://github.com/continuedev/continue
📝 open-source coding agent
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The Continue project is an open-source coding agent that's available as a CLI, VS Code extension, and JetBrains plugin. Although the repository is no longer actively maintained, it's still a valuable resource for developers.

To get started, you can check out the Continue Docs for configuration, customization, and usage information.

The final 2.0.0 release includes a polished version of the VS Code extension, CLI, and JetBrains plugin, with features like removed anonymous telemetry and bug fixes.

The project is licensed under Apache 2.0 and has a community-driven codebase.

One-liner takeaway: Continue may be discontinued, but its open-source codebase remains a pioneering foundation for AI-powered coding tools.

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🧠 Channel: https://xn--r1a.website/GithubRe

💡 penpot/penpot just hit the trending charts — here's why it matters.

🔗 https://github.com/penpot/penpot
📝 Penpot: The open-source design tool for design and code collaboration
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Penpot is an open-source design platform for teams that build digital products at scale, giving them full ownership of their design infrastructure. It's built on open source, supports self-hosting, and works with open standards like SVG, CSS, HTML, and JSON.

Key features include real-time collaboration, design tokens for consistency, and a powerful open API for automation and integrations. The platform is designed for developers, with features like inspect mode and support for webhooks.

Penpot offers a full-stack design platform for building scalable design systems and integrated product development processes. It's perfect for teams that need security, flexibility, and ownership without vendor lock-in.

To get started, you can use Penpot in the cloud or deploy it on your own servers. The community is active, with many resources available, including tutorials, documentation, and a contributing guide.

Penpot is licensed under the Mozilla Public License, v. 2.0.

Takeaway: Penpot is the ultimate open-source design platform that puts teams in control of their design infrastructure, and that's a game-changer!

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🚀 Meet krahets/hello-algo: a gem from today's GitHub trending list.

🔗 https://github.com/krahets/hello-algo
📝 《Hello 算法》：动画图解、一键运行的数据结构与算法教程。支持简中、繁中、English、日本語，提供 Python, Java, C++, C, C#, JS, Go, Swift, Rust, Ruby, Kotlin, TS, Dart 等代码实现
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Hello Algo is an open-source, free, and beginner-friendly data structure and algorithm tutorial. Its purpose is to provide an easy-to-understand and smooth learning curve for newcomers. The key feature of this project is its use of animated illustrations and one-click runnable code to help readers learn by practicing and exploring the underlying implementation of data structures and algorithms.

To get started, you can read it online or download the PDF or EPUB version. The project supports multiple programming languages, including Python, Java, C++, JavaScript, and many more.

From a technical standpoint, Hello Algo uses a variety of tools and technologies to create an engaging learning experience. The project is ideal for beginners, students, and anyone looking to improve their understanding of data structures and algorithms.

In terms of contributing to the project, there are several ways to get involved, including content correction, code translation, and translation review. The project is licensed under CC BY-NC-SA 4.0, which allows for non-commercial use, sharing, and adaptation.

Overall, Hello Algo is a valuable resource for anyone looking to learn data structures and algorithms in a fun and interactive way. So, what are you waiting for? Dive into the world of algorithms and start coding with Hello Algo today - and remember, learning to code is just a click away!

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