Github Top Repositories
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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 14 268 subscribers, ranking 13 983 in the Education category and 28 170 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 14 268 subscribers.
According to the latest data from 05 September, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 255 over the last 30 days and by 8 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 0.92%. Within the first 24 hours after publication, content typically collects 0.61% reactions from the total number of subscribers.
- Post reach: On average, each post receives 131 views. Within the first day, a publication typically gains 87 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 06 September, 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.
14 268
Subscribers
+824 hours
+1197 days
+25530 days
Posts Archive
14 268
π‘ santifer/career-ops just hit the trending charts β here's why it matters.
π https://github.com/santifer/career-ops
π AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing.
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Career-Ops is an open-source, AI-powered job search command center that turns any AI coding CLI into a full-fledged career management system. It helps candidates choose companies by evaluating job listings, generating tailored CVs, scanning portals, and tracking applications.
The system features a
6-Block Evaluation process, Interview Story Bank, Negotiation Scripts, and ATS PDF Generation. It also includes a Portal Scanner for 45+ pre-configured companies and custom queries, as well as Batch Processing for parallel evaluation.
To get started, users can run npx @santifer/career-ops init or clone the repository and install dependencies. The system is designed to be customized by Claude itself and supports Gemini CLI integration.
Career-Ops is perfect for candidates who want to take control of their job search and make informed decisions. With its AI-powered evaluation and recommendation features, it helps users find the best job opportunities and increase their chances of landing their dream role.
The system is built with technologies like Claude Code, OpenCode, Gemini CLI, Codex, and Node.js. It's available in multiple languages and has a MIT license.
In short, Career-Ops is a game-changer for job seekers, and its AI-powered approach helps them find the few offers worth their time out of hundreds - your time is valuable, and so is the recruiter's.
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π§ Channel: https://t.me/GithubRe
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π Meet phuryn/pm-skills: a gem from today's GitHub trending list.
π https://github.com/phuryn/pm-skills
π PM Skills Marketplace: 100+ agentic skills, commands, and plugins β from discovery to strategy, execution, launch, and growth.
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The PM Skills Marketplace is an AI operating system designed to help product managers make better decisions. It offers 68 PM skills and 42 chained workflows across 9 plugins, covering the entire product development process from discovery to strategy, execution, launch, growth, and shipping AI-built code.
The marketplace is compatible with
Claude Code and Cowork, and its skills can also be used with other AI assistants. To get started, you can use commands like /discover, /strategy, or /write-prd to invoke specific workflows.
One of the key features of the PM Skills Marketplace is its ability to provide structure and proven PM frameworks, such as those from Teresa Torres, Marty Cagan, and Alberto Savoia. This helps product managers to make better decisions and create more effective product strategies.
From a technical perspective, the marketplace is built using a modular architecture, with each plugin grouping related skills and commands into installable packages. The skills are loaded automatically when relevant to the conversation, and can be invoked using specific commands or by describing the steps in plain language.
The PM Skills Marketplace is designed for product managers, entrepreneurs, and anyone involved in product development. Whether you're looking to improve your product strategy, streamline your execution, or simply make better decisions, the PM Skills Marketplace has something to offer.
In short, the PM Skills Marketplace is a powerful tool that can help you supercharge your product decisions with AI-driven workflows.
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π§ Channel: https://t.me/GithubRe
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π yikart/AiToEarn caught my eye on GitHub Trending today.
π https://github.com/yikart/AiToEarn
π Let's use AI to Earn!
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AiToEarn is an innovative platform that empowers individuals and businesses to monetize, publish, engage, and create content across multiple platforms. With its AI Agent automation, it simplifies the process of building, distributing, and earning from content on various social media channels, including TikTok, YouTube, Facebook, and more.
The platform offers
five usage methods: web, OpenClaw, Claude/Cursor, Docker, and source code development. To get started, users can obtain an API Key by registering and logging in to the website.
Key features include content creation, publishing, and engagement agents, as well as support for multiple platforms and languages. The platform is suitable for one-person companies, creators, and businesses looking to streamline their content marketing efforts.
From a technical standpoint, AiToEarn is built using Node.js 20.18.x and offers a range of tools and integrations for customization and extension.
In summary, AiToEarn is a powerful tool for anyone looking to simplify their content marketing workflow and turn their creativity into cash: create, publish, engage, and earn with AiToEarn - the ultimate content monetization platform!
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π§ Channel: https://t.me/GithubRe
14 268
π Meet x1xhlol/system-prompts-and-models-of-ai-tools: a gem from today's GitHub trending list.
π https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools
π FULL Augment Code, Claude Code, Cluely, CodeBuddy, Comet, Cursor, Devin AI, Junie, Kiro, Leap.new, Lovable, Manus, NotionAI, Orchids.app, Perplexity, Poke, Qoder, Replit, Same.dev, Trae, Traycer AI, VSCode Agent, Warp.dev, Windsurf, Xcode, Z.ai Code, Dia & v0. (And other Open Sourced) System Prompts, Internal Tools & AI Models
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The system-prompts-and-models-of-ai-tools GitHub repository is a valuable resource for the AI community, providing a comprehensive collection of system prompts and models for various AI tools. The purpose of this repository is to facilitate the development and improvement of AI systems by offering a centralized hub for
prompts and models.
To get started, users can explore the repository's contents, which include a wide range of prompts and models for different AI applications. The repository is open-source, allowing developers to contribute and share their own prompts and models.
From a technical perspective, the repository highlights the importance of secure data practices, particularly for AI startups, by providing resources and guidance on prompt injection and system prompt extraction risks.
This repository is ideal for AI developers, researchers, and startups looking to improve their AI systems and stay up-to-date with the latest developments in the field.
In short, the system-prompts-and-models-of-ai-tools repository is a go-to resource for anyone involved in AI development - star it and join the community to accelerate your AI journey!
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π§ Channel: https://t.me/GithubRe14 268
π‘ TapXWorld/ChinaTextbook just hit the trending charts β here's why it matters.
π https://github.com/TapXWorld/ChinaTextbook
π ζζε°ει«γ倧ε¦PDFζζγ
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ChinaTextbook is a GitHub repository that provides free access to Chinese textbooks, aiming to promote compulsory education and eliminate regional education disparities. The repository contains a wide range of textbooks, including mathematics for elementary, middle, and high school, as well as university-level mathematics, such as linear algebra and probability theory.
To use the repository, simply browse through the folders and download the desired textbooks. Note that some files may be split into smaller parts due to GitHub's upload limits, but a
mergePDFs-windows-amd64.exe program is provided to merge them.
The repository is maintained by TapXWorld and is open to contributions and donations. Join the Telegram community to get the latest updates and share your thoughts: https://t.me/+1V6WjEq8WEM4MDM1.
One-liner takeaway: Empowering education with free access to Chinese textbooks.
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π§ Channel: https://t.me/GithubRe14 268
β‘ Andyyyy64/whichllm is making waves. Here's the full picture.
π https://github.com/Andyyyy64/whichllm
π Find the local LLM that actually runs and performs best on your hardware. Ranked by real, recency-aware benchmarks, not parameter count. One command, run it instantly.
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Find the perfect LLM for your hardware with Andyyyy64/whichllm, a Python tool that auto-detects your GPU/CPU/RAM and ranks top models from HuggingFace that fit your system. Key features include evidence-based ranking, recency-aware scoring, and architecture-aware estimates.
whichllm is easy to use: just run uvx whichllm@latest or install it with pip install whichllm. You can simulate different GPUs, compare upgrade candidates, and even get copy-paste Python snippets for your chosen model. The tool is designed for developers and researchers who want to get the most out of their hardware. whichllm --gpu "RTX 4090"
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π‘ aaif-goose/goose just hit the trending charts β here's why it matters.
π https://github.com/aaif-goose/goose
π an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
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Meet goose, a general-purpose AI agent designed to run on your machine, making it easy to tackle tasks such as research, writing, automation, and data analysis. With a native desktop app for macOS, Linux, and Windows, a full CLI for terminal workflows, and an API for embedding, goose is built in
Rust for optimal performance and portability.
It supports over 15 providers, including Anthropic, OpenAI, and Google, and connects to 70+ extensions via the Model Context Protocol open standard. To get started, you can download the desktop app or install the CLI using a simple script:
curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash14 268
π refactoringhq/tolaria caught my eye on GitHub Trending today.
π https://github.com/refactoringhq/tolaria
π Desktop app to manage markdown knowledge bases
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Tolaria is a desktop app for managing markdown knowledge bases. It's used for personal knowledge, company docs, and storing AI memory and procedures. The app is files-first, git-first, and offline-first, ensuring your data belongs to you, not the app.
Key features include:
-
Keyboard-first design for power-users
- Support for AI agents like Claude Code, Codex CLI, and Gemini CLI
- Standards-based notes in markdown with YAML frontmatter
To get started, you can install Tolaria via Homebrew or download the latest release. The app is open source and built with Tauri, React, and TypeScript.
One-liner takeaway: Tolaria is the ultimate tool for managing your knowledge base, giving you complete control over your data and versatility in using AI agents.
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π§ Channel: https://t.me/GithubRe
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π Deep-diving into opencv/opencv β fresh off the trending list.
π https://github.com/opencv/opencv
π Open Source Computer Vision Library
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The OpenCV library is a game-changer for computer vision enthusiasts, providing a vast array of functions and tools for image and video processing, feature detection, object recognition, and more. With its
extensive documentation and active community, OpenCV is the perfect platform for developers, researchers, and students to explore and innovate in the field of computer vision.
To get started, users can access the official homepage for courses, documentation, and forums, or contribute to the library by submitting pull requests and following the guidelines. The library's technical highlights include its ability to support various programming languages, such as C++, Python, and Java, making it a versatile tool for diverse applications.
Whether you're a seasoned developer or just starting out, OpenCV is an invaluable resource for anyone looking to push the boundaries of computer vision. So why not join the community today and start building something amazing with OpenCV? Empower your vision with the world's leading computer vision library!
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π§ Channel: https://t.me/GithubRe14 268
π Spotted on GitHub Trending: roboflow/supervision β let's break it down.
π https://github.com/roboflow/supervision
π We write your reusable computer vision tools. π
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Supervision is a Python library that simplifies the development of computer vision applications. Its primary purpose is to provide reusable tools for common tasks such as loading datasets, drawing detections, and counting objects in a specific zone. The library is model-agnostic, allowing users to plug in any classification, detection, or segmentation model.
To get started, you can
pip install supervision in a Python environment with version 3.9 or higher. The library offers a range of key features, including connectors for popular libraries like Ultralytics, Transformers, and MMDetection, as well as highly customizable annotators for visualizing detections.
For usage, you can use the library to load datasets from various formats, split and merge datasets, and save them in different formats. The library also provides a range of technical highlights, including support for object detection, tracking, and speed estimation.
The library is designed for developers and researchers working on computer vision projects, particularly those who want to build applications faster and more reliably. With its user-friendly documentation and active community, Supervision is an excellent choice for anyone looking to simplify their computer vision workflow.
One-liner takeaway: Supervision simplifies computer vision development by providing reusable tools and a model-agnostic approach, making it an excellent choice for developers and researchers looking to build applications faster and more reliably.
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π§ Channel: https://t.me/GithubRe
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π₯ RyanCodrai/turbovec is trending β and it deserves your attention.
π https://github.com/RyanCodrai/turbovec
π A vector index built on TurboQuant, written in Rust with Python bindings
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Turbovec is a Rust vector index with Python bindings, built on Google Research's TurboQuant algorithm. It allows for
online ingest, adding vectors without a train step, and is faster than FAISS with hand-written NEON and AVX-512BW kernels. Key features include filter-at-search-time capabilities, pure local deployment, and support for stable external ids.
Technical highlights include a 10-16x compression ratio, Lloyd-Max scalar quantization, and bit-packing. The length-renormalized scoring ensures unbiased inner-product estimation.
Audience: Developers building RAG (Retrieval-Augmented Generation) stacks where privacy, memory, or latency matters.
To get started, install via pip install turbovec or cargo add turbovec, and explore the Python or Rust APIs.
Turbovec is ideal for applications requiring efficient and private vector search. Try it out and experience the power of TurboQuant! You'll be searching faster and more efficiently in no time: Turbovec - search at the speed of thought.
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π§ Channel: https://t.me/GithubRe
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π mvanhorn/last30days-skill caught my eye on GitHub Trending today.
π https://github.com/mvanhorn/last30days-skill
π AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary
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The last30days-skill is an AI agent-led search engine that scores results by upvotes, likes, and real money, rather than editors. It searches across multiple platforms, including Reddit, X, YouTube, and GitHub, to provide a more comprehensive view of a topic. The skill is easy to use, with a
/last30days command that can be run in various platforms, including Claude Code, Codex, and Gemini CLI.
Key features include shareable HTML briefs, intelligent search, and cross-source cluster merging. It's useful for research, sales calls, and staying up-to-date with the latest information on a topic. The skill is designed for anyone looking for a more accurate and comprehensive search engine, including researchers, sales professionals, and anyone looking to stay informed.
One-liner takeaway: With last30days-skill, you can search what actually matters, not just what editors think is relevant.
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π§ Channel: https://t.me/GithubRe14 268
π aaif-goose/goose caught my eye on GitHub Trending today.
π https://github.com/aaif-goose/goose
π an open source, extensible AI agent that goes beyond code suggestions - install, execute, edit, and test with any LLM
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Meet goose, your native open source AI agent that runs on your machine, helping you with code, research, writing, automation, and more. It's available as a desktop app for macOS, Linux, and Windows, a full CLI for terminal workflows, and an API to embed it anywhere.
goose is built in Rust for performance and portability, and it works with 15+ providers, including Anthropic, OpenAI, and Google. You can connect to 70+ extensions via the Model Context Protocol open standard. To get started, you can download the desktop app or install the CLI using a simple script:
curl -fsSL https://github.com/aaif-goose/goose/releases/download/stable/download_cli.sh | bash