Github Top Repositories
Top GitHub repositories in one place π Explore the best projects in programming, AI, data science, and more.
Show moreπ Analytical overview of Telegram channel Github Top Repositories
Channel Github Top Repositories (@githubre) in the English language segment is an active participant. Currently, the community unites 13 241 subscribers, ranking 15 402 in the Education category and 32 619 in the India region.
π Audience metrics and dynamics
Since its creation on Π½Π΅Π²ΡΠ΄ΠΎΠΌΠΎ, the project has demonstrated rapid growth, gathering an audience of 13 241 subscribers.
According to the latest data from 08 June, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 357 over the last 30 days and by 10 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.16%. Within the first 24 hours after publication, content typically collects 0.75% reactions from the total number of subscribers.
- Post reach: On average, each post receives 153 views. Within the first day, a publication typically gains 99 views.
- Reactions and interaction: The audience actively supports content: the average number of reactions per post is 1.
- Thematic interests: Content is focused on key topics such as repository, fork, programming, statistic, description.
π Description and content policy
The author describes the resource as a platform for expressing subjective opinions:
βTop GitHub repositories in one place π
Explore the best projects in programming, AI, data science, and more.β
Thanks to the high frequency of updates (latest data received on 09 June, 2026), the channel maintains relevance and a high level of publication reach. Analytics show that the audience actively interacts with content, making it an important point of influence in the Education category.
codegraph is 100% local, with no data leaving your machine and no external services required.
To get started, simply run the installer with npx @colbymchenry/codegraph or curl -fsSL https://raw.githubusercontent.com/colbymchenry/codegraph/main/install.sh | sh (on macOS/Linux) or irm https://raw.githubusercontent.com/colbymchenry/codegraph/main/install.ps1 | iex (on Windows). Then, initialize your project with codegraph init -i to build the knowledge graph index.
Technical highlights include support for 19+ languages and 14 frameworks, with a self-contained SQLite database. Benchmark results show an average of 35% cheaper, 59% fewer tokens, 49% faster, and 70% fewer tool calls compared to not using CodeGraph.
The target audience is developers who want to improve their code intelligence and workflow efficiency. With CodeGraph, you can work smarter, not harder - give it a try and see the difference for yourself: CodeGraph is the secret sauce to turbocharge your coding productivity!
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π§ Channel: https://t.me/GithubReplugins for internal plugins developed by Anthropic, and external_plugins for third-party plugins from partners and the community.
To get started with a plugin, you can install it directly from the marketplace via Claude Code's plugin system by running /plugin install {plugin-name}@claude-plugins-official or browsing through the /plugin > Discover section.
For developers, the repository provides a plugin-name/ structure template, including a .claude-plugin/ directory with a required plugin.json file, as well as optional directories for commands/, agents/, and skills/.
This repository is for anyone looking to expand Claude Code's capabilities - and with great power comes great coding responsibility: trust no plugin before installing.
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π§ Channel: https://t.me/GithubRemulti-agent pipeline that analyzes the project, builds a knowledge graph, and provides an interactive dashboard. It includes features like guided tours, fuzzy and semantic search, diff impact analysis, and persona-adaptive UI.
To get started, simply install the plugin, analyze the codebase, and explore the dashboard. The tool supports multiple languages and can be easily integrated into various development environments.
Understand Anything is perfect for developers, teams, and organizations looking to improve their understanding of complex codebases and knowledge bases.
Check it out and start understanding anything - your codebase will thank you!
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π§ Channel: https://t.me/GithubReadvanced traffic routing interface, client and traffic monitoring, and subscription link management. The panel also supports dark and light themes and has an API interface for custom integrations.
To get started, you can install S-UI using the provided installation scripts for Linux/macOS or by downloading the latest Windows release. The project also supports Docker installation for containerized environments.
The S-UI project is designed for users who want a powerful and customizable web panel for their servers. With its extensive feature set and user-friendly interface, it's an ideal solution for those looking to manage their server configurations efficiently.
One-liner takeaway: S-UI is a feature-rich web panel that simplifies server management with its advanced traffic routing, client monitoring, and subscription link management capabilities.
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π§ Channel: https://t.me/GithubResupercharge your workflow!
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π§ Channel: https://t.me/GithubRestream content from various sources, download videos for offline viewing, and even manage subtitles. The app also features a customizable interface, a library to track your watched content, and a trending section to discover new titles.
To get started, you'll need to install Node.js, obtain a free TMDB API key, and install ffmpeg for downloading content. The app is available for Linux, Windows, and can be built from source using npm.
Streambert is designed for personal and educational use only, and users are responsible for ensuring they have the legal rights to access any content. The app does not host or distribute copyrighted content, and instead, sources content from third-party providers.
In short, Streambert is your one-stop-shop for streaming and downloading your favorite content, with a focus on privacy and customization - watch what you want, without the hassle of ads and trackers.
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π§ Channel: https://t.me/GithubReinspiring lists, cheatsheets, blogs, and podcasts related to various topics, including networking, security, and development. Whether you're a seasoned professional or just starting out, this repository has something for everyone. Check it out and stay up-to-date with the latest tools and knowledge in the field! You'll find it's a treasure trove of information - Dig in and uncover the secrets!
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π§ Channel: https://t.me/GithubRemodes for different research tasks, including Socratic guidance for research planning and a systematic review mode for thorough literature analysis.
Technical highlights of this repository include its integration with the Claude Code platform, allowing for seamless interaction with AI tools. It also supports various file formats, including Markdown and LaTeX, making it versatile for different types of research outputs.
The intended audience for this repository includes academic researchers across various disciplines who are looking to leverage AI tools to improve the efficiency and quality of their research. By utilizing this repository, researchers can focus on high-level thinking and interpretation, while delegating more mundane tasks to AI assistants.
In terms of usage, getting started with the repository involves installing the academic-research-skills plugin through the Claude Code marketplace and then accessing its various features through a set of predefined commands. For instance, users can initiate a research project by asking for guidance on a specific topic or by requesting a literature review on a particular subject.
Overall, the academic-research-skills repository represents a powerful tool for academics looking to harness the potential of AI in their research. By automating routine tasks and providing intelligent assistance, it enables researchers to concentrate on the creative and intellectual aspects of their work, leading to higher quality research outcomes.
One-liner takeaway: The academic-research-skills repository is a game-changer for researchers, offering a suite of AI-powered tools that streamline the research process, from planning to publication, and free up time for the high-level thinking that drives real innovation.
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π§ Channel: https://t.me/GithubReagents as teammates, squads for stable routing, autonomous execution, reusable skills, and unified runtimes.
To get started, you can install Multica using Homebrew, an install script, or PowerShell. Then, set up and start the daemon, verify your runtime, create an agent, and assign your first task. The platform has a simple CLI for connecting your local machine to Multica, managing workspaces, and running the agent daemon.
Multica is designed for human + AI teams and works with various coding agents, including Claude Code, Codex, and GitHub Copilot CLI. The platform is built using Next.js, Go, and PostgreSQL, and has a modular architecture.
Whether you're a developer, a contributor, or just someone interested in AI-powered teamwork, Multica is worth exploring. With its cutting-edge technology and user-friendly interface, Multica is poised to revolutionize the way we work with AI agents. Your next 10 hires won't be human - they'll be Multica agents.
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π§ Channel: https://t.me/GithubReWorkflowRunner 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 β creating value for your users.
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π§ Channel: https://t.me/GithubRecurl -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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π§ Channel: https://t.me/GithubRePython 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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π§ Channel: https://t.me/GithubRe
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