🚀 Meet obra/superpowers: a gem from today's GitHub trending list.

🔗 https://github.com/obra/superpowers
📝 An agentic skills framework & software development methodology that works.
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Superpowers is a software development methodology for coding agents, providing a set of composable skills and instructions to enhance their capabilities. The system starts by asking users about their goals, then breaks down the project into manageable chunks, and creates an implementation plan emphasizing test-driven development, simplicity, and code quality.

Key features include test-driven-development, systematic-debugging, and collaboration tools, such as brainstorming, writing-plans, and executing-plans.

To use Superpowers, simply install the plugin for your preferred coding agent, such as Claude Code, Codex CLI, or GitHub Copilot CLI.

From a technical standpoint, Superpowers is built around a skills library that includes testing, debugging, and collaboration tools, all designed to work seamlessly across different coding agents.

This project is suitable for developers and teams looking to streamline their development process and improve code quality.

In short, Superpowers is an innovative approach to software development that can supercharge your coding agents and take your projects to the next level - automating the process, not just the code.

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🧠 Channel: https://t.me/GithubRe

🚀 Meet HKUDS/CLI-Anything: a gem from today's GitHub trending list.

🔗 https://github.com/HKUDS/CLI-Anything
📝 "CLI-Anything: Making ALL Software Agent-Native" -- CLI-Hub:https://clianything.cc/
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CLI-Anything is a revolutionary project that bridges the gap between AI agents and the world's software by making any software agent-ready with just one command line. The project's purpose is to empower agents to interact with various software, enabling them to perform tasks autonomously.

Key features of CLI-Anything include the CLI-Hub, a central registry where you can browse, search, and install any CLI with a single pip install cli-anything-hub command, followed by cli-hub install <name>. The project also provides demos that showcase AI agents using generated CLIs to produce real artifacts.

To get started, users can visit the CLI-Hub to explore and install CLIs. The project is built using python, click, and pytest, with a focus on JSON and human-readable output.

CLI-Anything is designed for developers, AI researchers, and power users who want to automate tasks and integrate various software with AI agents. With its extensive test coverage and security features, the project ensures reliable and secure interactions between agents and software.

In summary, CLI-Anything is a game-changer for AI-agent interaction, and its potential is vast: one command line to rule them all.

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🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: rmyndharis/OpenWA — let's break it down.

🔗 https://github.com/rmyndharis/OpenWA
📝 Free, Open Source, Self-Hosted WhatsApp API Gateway
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Introducing OpenWA, a free, open-source WhatsApp API Gateway designed for developers who need full control over their messaging infrastructure. With a pluggable architecture, OpenWA allows you to swap database engines, storage backends, and cache layers without changing a single line of application code.

The key features of OpenWA include a REST API, multi-session support, webhooks, a web dashboard, and API key authentication. It also supports text messages, media messages, message reactions, bulk messaging, and message status tracking.

To get started with OpenWA, you can use the docker compose command to start the application in development mode or production mode. The project uses a Node.js runtime, NestJS framework, and TypeScript language.

OpenWA is suitable for developers who want to build custom messaging applications without vendor lock-in or hidden paywalls. With its flexible architecture and comprehensive documentation, OpenWA is an ideal choice for businesses and individuals looking for a reliable and scalable WhatsApp API Gateway.

Take control of your messaging infrastructure with OpenWA - the open-source WhatsApp API Gateway that puts you in the driver's seat!

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🧠 Channel: https://t.me/GithubRe

🔥 ChromeDevTools/chrome-devtools-mcp is trending — and it deserves your attention.

🔗 https://github.com/ChromeDevTools/chrome-devtools-mcp
📝 Chrome DevTools for coding agents
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Introducing ChromeDevTools/chrome-devtools-mcp, a game-changing tool that lets your coding agent control and inspect a live Chrome browser. This Model-Context-Protocol (MCP) server gives your AI coding assistant access to the full power of Chrome DevTools, enabling reliable automation, in-depth debugging, and performance analysis.

The key features of chrome-devtools-mcp include:
- Getting performance insights by recording traces and extracting actionable performance insights
- Advanced browser debugging capabilities, such as analyzing network requests, taking screenshots, and checking browser console messages
- Reliable automation using puppeteer to automate actions in Chrome and automatically wait for action results

To use chrome-devtools-mcp, you'll need Node.js, Chrome, and npm. The tool supports a range of coding agents, including Antigravity, Claude, Cursor, and Copilot, and provides a CLI for use without MCP.

From a technical standpoint, chrome-devtools-mcp is built using Node.js and leverages the power of Chrome DevTools and puppeteer. The tool is designed to be flexible and customizable, with options for slim mode and performance analysis.

chrome-devtools-mcp is perfect for developers who want to supercharge their coding workflow with the power of Chrome DevTools. Whether you're looking to automate tasks, debug issues, or analyze performance, this tool has got you covered.

In short, chrome-devtools-mcp is a must-have tool for any developer looking to take their coding skills to the next level - it's like having a superpower in your coding toolbox!

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🧠 Channel: https://t.me/GithubRe

📌 Spotted on GitHub Trending: rohitg00/ai-engineering-from-scratch — let's break it down.

🔗 https://github.com/rohitg00/ai-engineering-from-scratch
📝 Learn it. Build it. Ship it for others.
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The AI Engineering from Scratch curriculum is designed to bridge the gap between using AI tools and understanding how they work. With 435 lessons and 20 phases, this free, open-source resource covers everything from math foundations to deep learning and autonomous systems. Each lesson follows a consistent structure, where you build an algorithm from scratch, then use it through a production library, resulting in a reusable artifact that you can apply to real-world problems. The curriculum is suitable for anyone who wants to understand how AI works, not just call APIs. By the end, you'll have a portfolio of 435 artifacts that you actually understand because you built them. Build it, use it, ship it - that's the motto, and with this curriculum, you'll be well on your way to becoming an AI engineer from scratch.

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🧠 Channel: https://t.me/GithubRe

🚀 Meet teng-lin/notebooklm-py: a gem from today's GitHub trending list.

🔗 https://github.com/teng-lin/notebooklm-py
📝 Unofficial Python API and agentic skill for Google NotebookLM. Full programmatic access to NotebookLM's features—including capabilities the web UI doesn't expose—via Python, CLI, and AI agents like Claude Code, Codex, and OpenClaw.
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The notebooklm-py GitHub repository provides a comprehensive and unofficial Python API for NotebookLM, a powerful tool for research automation and content generation. With this library, developers can access NotebookLM's features programmatically, including capabilities not exposed in the web UI. The API supports Python 3.10+ and can be installed via pip install notebooklm-py.

Key features include:

* Complete NotebookLM coverage: create, list, rename, and delete notebooks, as well as manage sources, chat, research, and sharing.
* Content generation: audio overviews, videos, slide decks, quizzes, flashcards, infographics, data tables, and mind maps.
* Beyond the web UI: batch downloads, quiz/flashcard export, mind map data extraction, and more.

The library can be used in three ways:

1. Python API: for application integration, async workflows, and custom pipelines.
2. CLI: for shell scripts, quick tasks, and CI/CD automation.
3. Agent integration: for integrating with AI agents like Claude Code, Codex, and OpenClaw.

The repository includes a quick start guide, CLI reference, and Python API documentation to help users get started.

notebooklm-py is ideal for prototypes, research, and personal projects, and is not affiliated with Google. However, please note that it uses undocumented Google APIs, which can change without notice, and may be subject to rate limits.

To get started, users can install the library via pip and follow the quick start guide. For more information, refer to the repository's documentation, including the troubleshooting guide and release notes.

In summary, notebooklm-py is a powerful tool for unlocking the full potential of NotebookLM, and with its comprehensive API and ease of use, it's a must-try for anyone looking to automate research and content generation tasks - Automate your research and content creation with notebooklm-py, and take your productivity to the next level!

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🧠 Channel: https://t.me/GithubRe

🔥 can1357/oh-my-pi is trending — and it deserves your attention.

🔗 https://github.com/can1357/oh-my-pi
📝 ⌥ AI Coding agent for the terminal — hash-anchored edits, optimized tool harness, LSP, Python, browser, subagents, and more
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Oh My Pi is a powerful coding agent that ships with a comprehensive set of tools, designed to streamline your development workflow. With 40+ providers, 32 built-in tools, and 13 LSP operations, this agent is capable of handling a wide range of tasks, from code execution and debugging to project management and conflict resolution.

To get started, you can install Oh My Pi using curl -fsSL https://omp.sh/install | sh on macOS or Linux, or bun install -g @oh-my-pi/pi-coding-agent using Bun. On Windows, you can use irm https://omp.sh/install.ps1 | iex in PowerShell.

Oh My Pi boasts an impressive array of features, including time-traveling stream rules, first-class subagents, and unapologetically native support for macOS, Linux, and Windows. The agent also supports code review with priorities and a verdict, hashline: edit by content hash, and hindsight: memory the agent curates.

One of the key highlights of Oh My Pi is its ability to integrate seamlessly with your existing tools and workflows. For example, you can use read pr://1428 to read a PR, or search to walk a diff like a directory. The agent also supports preview, then accept for proposed edits.

Whether you're a seasoned developer or just starting out, Oh My Pi has something to offer. With its extensive range of features and tools, this coding agent is designed to help you work more efficiently and effectively.

Takeaway: Oh My Pi is the ultimate coding sidekick, helping you code smarter, not harder.

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🧠 Channel: https://t.me/GithubRe

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

🔗 https://github.com/antoinezambelli/forge
📝 A Python framework for self-hosted LLM tool-calling and multi-step agentic workflows
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Forge is a reliability layer for self-hosted LLM tool-calling, designed to lift local models to the top of their class on multi-step agentic workflows. It achieves this through guardrails (rescue parsing, retry nudges, step enforcement) and context management (VRAM-aware budgets, tiered compaction).

Key features include a WorkflowRunner for defining tools and running structured agent loops, Guardrails middleware for validating responses and enforcing required steps, and a Proxy server for transparently applying guardrails to local model servers.

Forge supports various backends, including Ollama, llama-server, Llamafile, and Anthropic. It's built with Python 3.12+ and is licensed under MIT.

The target audience is developers and researchers working with self-hosted LLMs, particularly those building multi-step workflows, multi-turn conversations, and long-running sessions.

In a nutshell, Forge helps you build more reliable and efficient self-hosted LLM tool-calling workflows, so you can focus on what matters – creating value for your users.

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🧠 Channel: https://t.me/GithubRe