Github Top Repositories

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Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.

📈 Аналітичний огляд Telegram-каналу Github Top Repositories

Канал Github Top Repositories (@githubre) у мовному сегменті Англійська є активним учасником. На даний момент спільнота об'єднує 13 267 підписників, посідаючи 15 384 місце в категорії Освіта та 32 523 місце у регіоні Індія.

📊 Показники аудиторії та динаміка

З моменту свого створення невідомо, проект продемонстрував стрімке зростання, зібравши аудиторію у 13 267 підписників.

За останніми даними від 09 червня, 2026, канал демонструє стабільну активність. Хоча за останні 30 днів спостерігається зміна кількості учасників на 373, а за останні 24 години на 13, загальне охоплення залишається високим.

Статус верифікації: Не верифікований
Рівень залученості (ER): Середній показник залученості аудиторії становить 1.17%. Протягом перших 24 годин після публікації контент зазвичай збирає 0.73% реакцій від загальної кількості підписників.
Охоплення публікацій: В середньому кожен допис отримує 155 переглядів. Протягом першої доби публікація в середньому набирає 97 переглядів.
Реакції та взаємодія: Аудиторія активно підтримує контент: середня кількість реакцій на один пост – 1.
Тематичні інтереси: Контент зосереджений навколо ключових тем, таких як repository, fork, programming, statistic, description.

📝 Опис та контентна політика

Автор описує ресурс як майданчик для висловлення суб'єктивної думки:
“Top GitHub repositories in one place 🚀 Explore the best projects in programming, AI, data science, and more.”

Завдяки високій частоті оновлень (останні дані отримано 10 червня, 2026), канал підтримує актуальність та високий рівень охоплення публікацій. Аналітика показує, що аудиторія активно взаємодіє з контентом, що робить його важливою точкою впливу в категорії Освіта.

13 267

Підписники

+1324 години

+737 днів

+37330 день

155

Перегляди допису

~ 9724 години

~ 11048 годин

1.17%

Коефіцієнт залучення

~ 41

Дописів на день

Ads index

beta

Архів дописів

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💡 MemPalace/mempalace just hit the trending charts — here's why it matters. 🔗 https://github.com/MemPalace/mempalace 📝 The best-benchmarked open-source AI memory system. And it's free. ────────────────────────────── MemPalace is a local-first AI memory solution that stores conversation history as verbatim text and retrieves it with semantic search. It features a pluggable backend, with ChromaDB as the default, and supports alternative backends like sqlite_exact, qdrant, and pgvector. To get started, users can install MemPalace using uv tool install mempalace or pipx install mempalace, then initialize it with mempalace init ~/projects/myapp. The mempalace mine command is used to mine content into the palace, while mempalace search retrieves relevant information. MemPalace boasts an impressive 96.6% R@5 raw on the LongMemEval benchmark, with no API calls required. It also includes a temporal entity-relationship graph and supports MCP tools for palace reads/writes, knowledge-graph operations, and more. The target audience for MemPalace includes developers, researchers, and individuals seeking a robust, local-first AI memory solution. Overall, MemPalace offers a powerful and flexible solution for storing and retrieving conversation history, making it an excellent choice for those seeking a reliable and efficient AI memory system. Takeaway: MemPalace revolutionizes local-first AI memory, making it a game-changer for anyone seeking to harness the power of semantic search. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🎯 Andyyyy64/whichllm landed on trending. Worth a proper look. 🔗 https://github.com/Andyyyy64/whichllm 📝 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. ────────────────────────────── whichllm is a handy tool that helps you find the best local LLM (Large Language Model) that can run on your hardware. It auto-detects your GPU, CPU, and RAM, and then ranks the top models from HuggingFace that fit your system. You can use it to simulate a GPU before buying, compare upgrade candidates, and even start a chat with a model. The tool uses evidence-based ranking, not just size heuristics, to choose the top pick. It also considers recency-aware scores, so stale leaderboards are demoted. You can use whichllm to get a copy-paste Python snippet for any model, and it supports various model formats like GGUF, AWQ, and GPTQ. Technical highlights include architecture-aware estimates, live data from the HuggingFace API, and a simple, scriptable command-line interface. whichllm is designed for developers, researchers, and anyone who wants to work with LLMs. To get started, simply run uvx whichllm@latest or install it using brew install andyyyy64/whichllm/whichllm or pip install whichllm. Here's a punchy one-liner takeaway: With whichllm, you can easily find the perfect LLM for your hardware and start building amazing AI projects! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ openai/plugins is making waves. Here's the full picture. 🔗 https://github.com/openai/plugins 📝 OpenAI Plugins ────────────────────────────── The openai/plugins repository is a treasure trove of community-driven innovation, hosting a wide range of Codex plugin examples to streamline your workflow. Each plugin is carefully organized under its own directory, complete with a plugin.json manifest and optional supporting files like skills/, agents/, and assets/. Some highlighted examples include plugins for Figma, Notion, iOS and macOS app development, web apps, Expo, and more. These plugins are designed to make your life easier, whether you're working on design systems, planning and research, or building and deploying apps. The technical details are straightforward: each plugin has a required plugin.json file and may include additional files and directories. For example, a plugin might include a

hooks.json

file for custom hooks or an agents/ directory for custom agent implementations. This repository is perfect for developers, designers, and makers looking to tap into the power of Codex and automate their workflows. In short, the openai/plugins repository is your one-stop shop for unlocking Codex's full potential - join the community and start building today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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💡 phuryn/pm-skills just hit the trending charts — here's why it matters. 🔗 https://github.com/phuryn/pm-skills 📝 PM Skills Marketplace: 100+ agentic skills, commands, and plugins — from discovery to strategy, execution, launch, and growth. ────────────────────────────── The pm-skills GitHub repository is a game-changer for product managers, offering a comprehensive AI-powered operating system for making better product decisions. With 68 PM skills and 42 chained workflows across 9 plugins, this marketplace provides a structured approach to product management, covering discovery, strategy, execution, launch, growth, and shipping AI-built code. The skills are the building blocks, encoding proven PM frameworks and guiding users through specific tasks. Commands chain one or more skills into end-to-end processes, while plugins group related skills and commands into installable packages. To get started, users can install the marketplace using Claude Cowork or Claude Code, or even use the skills with other AI assistants like Codex, Gemini CLI, OpenCode, Cursor, or Kiro. The repository includes a range of plugins, such as pm-product-discovery, pm-product-strategy, and pm-execution, each with its own set of skills and commands. For example, the /discover command chains four skills together: brainstorm-ideas, identify-assumptions, prioritize-assumptions, and brainstorm-experiments. In summary, the pm-skills repository empowers product managers to make better product decisions with its comprehensive AI-powered operating system - Upgrade your product management workflow with pm-skills and start making data-driven decisions today! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🚀 Meet santifer/career-ops: a gem from today's GitHub trending list. 🔗 https://github.com/santifer/career-ops 📝 AI-powered job search system built on Claude Code. 14 skill modes, Go dashboard, PDF generation, batch processing. ────────────────────────────── The Career-Ops system is an open-source, AI-powered job search command center that helps candidates find their dream roles. It evaluates job listings, generates tailored CVs, and scans company portals for new offers. With its 6-block evaluation system and negotiation scripts, Career-Ops provides a comprehensive approach to job searching. The system is agentic, using AI to navigate career pages, evaluate fit, and adapt resumes per listing. It's built with technologies like Claude Code, OpenCode, and Gemini CLI, and supports Node.js and Go. To get started, users can clone and install the repository, configure their profiles, and add their CVs. The system is designed to be customized by Claude Code itself, allowing users to change modes, archetypes, and scoring weights. The key features of Career-Ops include auto-pipeline, interview story bank, and pipeline integrity. It also supports Gemini CLI integration and provides a dashboard TUI for browsing and filtering the pipeline. In summary, Career-Ops is a powerful tool for job seekers, providing a personalized and efficient approach to finding their dream roles: it's like having a personal recruiter in your pocket. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🚀 Meet danielmiessler/Personal_AI_Infrastructure: a gem from today's GitHub trending list. 🔗 https://github.com/danielmiessler/Personal_AI_Infrastructure 📝 Agentic AI Infrastructure for magnifying HUMAN capabilities. ────────────────────────────── Introduction to Personal AI Infrastructure (PAI): PAI is a Life Operating System designed to capture your identity, goals, and work, and help you reach your ideal state using AI. It's built around three layers: PAI (the OS), Pulse (the Life Dashboard), and the DA (your Digital Assistant). Key Features: PAI uses a filesystem as context, avoiding opaque storage, and is built with context scaffolding to feed models the right context. It has a self-improvement loop to capture signals and improve itself, and a custom algorithm to drive the current → ideal state transition. Technical Highlights: PAI uses TypeScript, Bun, and Claude to provide a robust and scalable platform. It has a skill system with deterministic code execution and a library of thinking skills to raise the quality of decisions. Usage and Audience: PAI is designed for individuals, teams, or companies looking to articulate their ideal state and move towards it. It's suitable for anyone who wants to harness the power of AI to improve their life and work. Getting Started: You can install PAI using the one-line install command: curl -sSL https://ourpai.ai/install.sh | bash. The project is in active development, so expect frequent updates and breaking changes. Takeaway: PAI is a powerful tool that can help you magnify your life and work with AI - and the best part is, it's designed to be operated by your AI, making it a true Life Operating System. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ Panniantong/Agent-Reach is making waves. Here's the full picture. 🔗 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. ────────────────────────────── Agent Reach is a tool that empowers your AI Agent with internet capabilities, allowing it to read web pages, search Twitter, watch YouTube videos, and more. It's designed to simplify the process of configuring and using various online tools with your AI Agent. With Agent Reach, you can easily install and update tools like twitter-cli, yt-dlp, and rdt-cli, and access various online platforms without needing to manually configure them. The tool is completely free and open-source, with a focus on security and privacy. It's compatible with all AI Agents that can run shell commands, including Claude Code, OpenClaw, Cursor, and Windsurf. To get started, simply tell your AI Agent to 安装 Agent Reach and follow the prompts. Star this project to support its development and maintenance. One-liner takeaway: Agent Reach simplifies internet access for your AI Agent, making it easy to search, read, and interact with online content. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

13 273

🌟 refactoringhq/tolaria caught my eye on GitHub Trending today. 🔗 https://github.com/refactoringhq/tolaria 📝 Desktop app to manage markdown knowledge bases ────────────────────────────── Tolaria is a desktop app for managing markdown knowledge bases. It's designed for people who want to organize their notes, documents, and knowledge in a flexible and portable way. With Tolaria, you can create a second brain for your personal knowledge, organize company documents, or even store memory and procedures for AI assistants. The app is built around several key principles, including files-first, git-first, and offline-first, which ensure that your data is always portable and under your control. Tolaria also supports keyboard-first navigation and is designed for power users who want to get the most out of their workflow. To get started with Tolaria, you can install it via Homebrew on macOS or download the latest release for macOS, Windows, or Linux. The app is open source and built with Tauri, React, and TypeScript, making it easy to contribute to or run locally. Some of the technical highlights of Tolaria include its use of markdown files with YAML frontmatter, support for git version control, and a keyboard-first design. The app is also highly customizable, with support for AI agents and a command palette for power users. Overall, Tolaria is a powerful tool for anyone who wants to manage their knowledge and notes in a flexible and portable way. Whether you're a power user or just looking for a simple way to organize your thoughts, Tolaria is definitely worth checking out. Takeaway: Tolaria is the ultimate second brain app for anyone who wants to manage their knowledge and notes in a flexible, portable, and powerful way. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🌟 google/skills caught my eye on GitHub Trending today. 🔗 https://github.com/google/skills 📝 Agent Skills for Google products and technologies ────────────────────────────── The google/skills repository on GitHub is a collection of Agent Skills for various Google products and technologies, including Google Cloud. This repository is under active development, and its main purpose is to provide a set of skills that can be used to interact with Google services. The repository offers a wide range of key features, including skills for Gemini API, BigQuery Basics, Cloud Run Basics, and more. To use these skills, you can install them using the command: npx skills add google/skills. From a technical standpoint, the skills are implemented using various programming languages and frameworks. For example:

npx skills add google/skills

This repository is suitable for developers and Google Cloud enthusiasts who want to learn more about Google's products and technologies. In short, the google/skills repository is a valuable resource for anyone looking to enhance their skills and knowledge of Google products, and the best part is - you can get started with just one command! ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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⚡ RyanCodrai/turbovec is making waves. Here's the full picture. 🔗 https://github.com/RyanCodrai/turbovec 📝 A vector index built on TurboQuant, written in Rust with Python bindings ────────────────────────────── TurboVec is a Rust vector index with Python bindings, built on Google Research's TurboQuant algorithm. It provides online ingest, faster search than FAISS, and filtering at search time. The library is designed for building Retrieval-Augmented Generation (RAG) systems where privacy, memory, or latency matters. Key features include: - TurboQuantIndex for vector indexing - IdMapIndex for stable external ids - Hand-written NEON (ARM) and AVX-512BW (x86) kernels for optimized performance - Pure local operation, with no managed service or data leaving the machine The library can be used from Python or Rust, with easy integration into popular frameworks like LangChain, LlamaIndex, Haystack, and Agno. TurboVec achieves high compression ratios and fast search speeds, making it suitable for large-scale applications. The library is designed to be easy to use, with a simple and intuitive API. One-liner takeaway: TurboVec is a game-changer for RAG systems, offering blazing-fast search, low memory usage, and pure local operation, making it the perfect choice for applications where performance and privacy matter. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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🔍 Deep-diving into mvanhorn/last30days-skill — fresh off the trending list. 🔗 https://github.com/mvanhorn/last30days-skill 📝 AI agent skill that researches any topic across Reddit, X, YouTube, HN, Polymarket, and the web - then synthesizes a grounded summary ────────────────────────────── Discover the power of /last30days-skill, a cutting-edge AI agent-led search engine that scores results based on upvotes, likes, and real money - not editors. This innovative tool bridges the gap between multiple platforms, including Reddit, X, YouTube, TikTok, and GitHub, to provide a comprehensive view of what's happening in the last 30 days. Key features include zero config, intelligent search, and the ability to compare tools and understand the world in a way that's not possible with traditional search engines. /last30days can be used before a meeting to get the latest information on a person or company, when something drops to stay on top of the latest news and trends, and to compare tools and make informed decisions. Technical highlights include a Python pre-research brain that resolves topics and searches the right people and communities, a second judge that scores results for humor, wit, and virality, and cross-source cluster merging that combines similar stories from different platforms. This tool is perfect for anyone who wants to stay ahead of the curve, including business professionals, researchers, and curious individuals. So why settle for outdated information when you can have the latest insights and trends at your fingertips? Try /last30days today and experience the power of AI-driven search! With /last30days-skill, you'll never be in the dark again - get the truth in 30 seconds or less. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe

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💡 microsoft/pg_durable just hit the trending charts — here's why it matters. 🔗 https://github.com/microsoft/pg_durable 📝 PostgreSQL in-database durable execution ────────────────────────────── pg_durable is a PostgreSQL extension that enables long-running, fault-tolerant SQL functions. It allows teams to define workflows in SQL, with the extension checkpointing each step, and resume after crashes, restarts, or failed steps. This approach eliminates the need for external services like cron jobs, workers, queues, and status tables. Key features include durable execution, SQL-native workflow definition, and database-aware primitives for scheduling and parallel execution. The extension is designed for backend and data engineers, DBAs, and SREs who want to automate runbooks and build data or AI pipelines with durable execution. SELECT df.start(...) is used to define a workflow, and the extension takes care of executing each step durably. The df namespace provides various functions for managing workflows, including df.start(), df.cancel(), and df.grant_usage(). Technical highlights include zero-infrastructure requirements, as the extension runs as a PostgreSQL extension, and a SQL-native approach, making it easy to define and manage workflows. The target audience includes teams building data or AI pipelines, and those who want to automate runbooks that must survive restarts and be auditable in SQL. To get started, you can install the extension using Debian packages or build it from source, and then create the extension in your PostgreSQL database using CREATE EXTENSION pg_durable;. One-liner takeaway: pg_durable brings durable execution to PostgreSQL, allowing teams to define and run long-running, fault-tolerant SQL workflows without external services. ────────────────────────────── 🧠 Channel: https://t.me/GithubRe