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 14 150 subscribers, ranking 14 019 in the Education category and 28 451 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 14 150 subscribers.
According to the latest data from 28 August, 2026, the channel demonstrates stable activity. Although there has been a change in the number of participants by 273 over the last 30 days and by 9 over the last 24 hours, overall reach remains high.
- Verification status: Not verified
- Engagement rate (ER): The average audience engagement rate is 1.05%. Within the first 24 hours after publication, content typically collects 0.70% reactions from the total number of subscribers.
- Post reach: On average, each post receives 149 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 29 August, 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.
14 150
Subscribers
+924 hours
+417 days
+27330 days
Posts Archive
14 146
π₯ addyosmani/agent-skills is trending β and it deserves your attention.
π https://github.com/addyosmani/agent-skills
π Production-grade engineering skills for AI coding agents.
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The addyosmani/agent-skills GitHub repository provides production-grade engineering skills for AI coding agents. These skills encode workflows, quality gates, and best practices used by senior engineers when building software, ensuring AI agents follow them consistently across every development phase.
The repository includes
8 slash commands that map to the development lifecycle, activating the right skills automatically. It also features a Quick Start guide for easy installation and a Meta skill for discovering which skill applies to a given task.
Technical highlights include test-driven development, incremental implementation, and context engineering. The skills are designed to work with various agents, including Claude Code, Cursor, Codex, and GitHub Copilot.
The target audience is developers and teams looking to improve their coding efficiency and quality. With addyosmani/agent-skills, you can streamline your development process and ensure your code meets high standards.
In short, addyosmani/agent-skills helps you code like a pro by providing a set of production-ready skills for AI agents - install, and let the skills do the heavy lifting.
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π§ Channel: https://t.me/GithubRe14 146
π₯ PrimeIntellect-ai/prime-agent is trending β and it deserves your attention.
π https://github.com/PrimeIntellect-ai/prime-agent
π A self-improving RLM agent for coding workflows and long-running autonomous tasks.
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Prime Agent is an open-source coding and research agent designed for general and long-running work. It's built around two core abstractions: the Recursive Language Model (RLM) and the Continual Harness. The RLM treats context as variables and tools like recursive subagents as function calls, while the Continual Harness stores supplemental prompts, memories, and reusable subagent specifications as durable state.
The agent combines a persistent Python control environment with durable harness state, allowing useful working context and reusable operating patterns to outlive a single chat window.
prime-agent can be installed using a simple curl command and can be started from any directory. It offers various features such as programmatic subagents, skill creation, and direct agent-to-agent communication.
Technical highlights include a persistent IPython environment, daemon-backed continuity, and heartbeats and schedules for long-running work. The agent is designed for long-running evaluations in research and offers a range of commands for managing sessions, including prime-agent agents, prime-agent attach, and prime-agent shutdown.
The Prime Agent is suitable for researchers, developers, and anyone looking for a powerful tool for long-running work. With its extensive documentation and open-source license, it's an attractive choice for those seeking a flexible and customizable solution.
In short, Prime Agent is a game-changer for long-running work - it's like having a super-smart, always-on, and highly customizable assistant at your fingertips!
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π§ Channel: https://t.me/GithubRe14 146
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π‘ firecrawl/pdf-inspector just hit the trending charts β here's why it matters.
π https://github.com/firecrawl/pdf-inspector
π Fast Rust library for PDF inspection, classification, and text extraction. Intelligently detects scanned vs text-based PDFs to enable smart routing decisions.
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Purpose: The
pdf-inspector GitHub repository offers a fast Rust library for PDF classification and text extraction. It detects whether a PDF is text-based or scanned, extracts text with position awareness, and converts it to clean Markdown without using OCR.
Key Features: This library includes smart classification, text extraction with font information and coordinates, Markdown conversion with headings, lists, and tables, and support for CID fonts and multi-column layouts.
Usage: It provides bindings for Python, Node.js, and browser WebAssembly, allowing for easy integration into various projects. The library can be used for tasks such as PDF routing, where it can quickly classify PDFs and extract text from text-based documents, saving time and cost by avoiding unnecessary OCR processing.
Technical Highlights: The library achieves fast performance, with classification taking around 10-50ms and text extraction taking around 150ms. It also supports various scan strategies, including early exit, full scan, and sampling, making it suitable for large-scale PDF processing pipelines.
Audience: This library is designed for developers working with PDFs, particularly those who need to process large volumes of documents and require a fast and efficient solution for text extraction and classification.
In summary, pdf-inspector is a powerful tool for PDF processing, offering a unique combination of speed, accuracy, and functionality, making it an ideal choice for developers looking to streamline their PDF workflows: process your PDFs faster and smarter with pdf-inspector.
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π§ Channel: https://t.me/GithubRe14 146
π― obra/superpowers landed on trending. Worth a proper look.
π https://github.com/obra/superpowers
π An agentic skills framework & software development methodology that works.
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Superpowers is a software development methodology that gives your coding agents a set of composable skills to work more efficiently. It starts by asking you what you're trying to achieve, then breaks down the work into manageable tasks with clear implementation plans. The agent works autonomously, following a subagent-driven-development process, and emphasizes
test-driven-development and systematic debugging.
Key features include a skills library with testing, debugging, and collaboration tools, as well as a brainstorming feature that refines rough ideas through questions and presents designs for validation. The methodology is designed to be systematic and simple, with a focus on complexity reduction and evidence-based decision making.
To get started, you can install Superpowers as a plugin for various coding agents, including Claude Code, Antigravity, and Codex App. The installation process varies depending on the agent, but most involve installing a plugin or package from the Superpowers repository.
The target audience for Superpowers is developers who want to work more efficiently and effectively with their coding agents. The methodology is designed to be flexible and adaptable, with a focus on community support and continuous improvement.
One-liner takeaway: Superpowers is a game-changer for coding agents, empowering them to work more efficiently and effectively, and helping developers achieve their goals with ease.
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π§ Channel: https://t.me/GithubRe14 146
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14 146
π‘ esengine/DeepSeek-Reasonix just hit the trending charts β here's why it matters.
π https://github.com/esengine/DeepSeek-Reasonix
π DeepSeek-native AI coding agent for your terminal. Engineered around prefix-cache stability β leave it running.
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Reasonix is a DeepSeek-native AI coding agent designed for your terminal. It's engineered around
prefix-cache stability, keeping token costs low across long sessions. The legacy TypeScript line (Reasonix 0.x) is in maintenance mode, with active development moved to the Go rewrite in the main-v2 branch.
To install Reasonix, run npm install -g reasonix or use npx reasonix code for a one-time execution. It works on macOS, Linux, and Windows. The dsnix alias is also available for a shorter command.
Key features include:
* Coding agent: Launches a coding session with filesystem and shell tools.
* Chat mode: A lighter mode for plain chat without disk access.
* Skills and memory: Author custom skills and manage user-private knowledge.
* Configuration: Customizable via a JSON file and per-project overrides.
The target audience includes developers and power users who want to leverage AI assistance in their coding workflow.
Technical highlights include:
* prefix-cache stability for low token costs.
* DeepSeek API integration for seamless AI functionality.
* Customizable configuration for tailored workflows.
In summary, Reasonix is a powerful AI coding agent that streamlines your development workflow with its unique prefix-cache stability and customizable features. Try it out and experience the future of coding assistance!
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π§ Channel: https://t.me/GithubRe
14 146
π tirth8205/code-review-graph caught my eye on GitHub Trending today.
π https://github.com/tirth8205/code-review-graph
π Local-first code intelligence graph for MCP and CLI. Builds a persistent map of your codebase so AI coding tools read only what matters, with benchmarked context reductions on reviews and large-repo workflows.
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The code-review-graph tool is designed to optimize your code review process by building a structural map of your codebase and tracking changes incrementally. This allows your AI assistant to focus on the most relevant parts of your code, reducing the number of tokens it needs to read and making the review process more efficient.
The key features of code-review-graph include its ability to parse your codebase into an abstract syntax tree (AST) using
Tree-sitter, store the AST as a graph of nodes and edges, and query the graph to determine the minimal set of files that need to be reviewed.
To use code-review-graph, you can install it via pip install code-review-graph and then run code-review-graph install to set up the tool for your project. The tool supports a wide range of programming languages, including Python, JavaScript, and Java, and allows you to add support for custom languages by creating a languages.toml file.
code-review-graph is designed for developers who want to optimize their code review process and reduce the time and resources required for code reviews. With its advanced features and support for custom languages, it's an ideal tool for any development team looking to streamline their workflow.
In short, code-review-graph helps you review smarter, not harder, by giving your AI assistant the context it needs to focus on the most important parts of your code.
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π§ Channel: https://t.me/GithubRe
14 146
π₯ Significant-Gravitas/AutoGPT is trending β and it deserves your attention.
π https://github.com/Significant-Gravitas/AutoGPT
π AutoGPT is the vision of accessible AI for everyone, to use and to build on. Our mission is to provide the tools, so that you can focus on what matters.
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The AutoGPT GitHub repository is an open-source platform that enables users to build, deploy, and run AI agents that can automate various tasks and workflows. With AutoGPT, users can describe an outcome in plain English or use a visual builder to shape every step of the process, and then run the agent on demand, on a schedule, or from a trigger. The platform offers four main surfaces: AutoPilot, Agents, Marketplace, and Build, which provide a range of features and functionalities for creating and managing AI agents.
The
AutoGPT platform is available in both hosted and self-hosted options, with the hosted version providing a managed infrastructure and model access, while the self-hosted version requires users to provide their own infrastructure and model API keys. The platform supports a wide range of integrations with popular apps and services, including Gmail, Google Calendar, GitHub, and Slack.
AutoGPT is designed for a wide range of users, from individuals to businesses, and offers a range of features and functionalities that can help automate various tasks and workflows. Whether you're looking to automate executive operations, sales, marketing, engineering, customer support, or research tasks, AutoGPT provides a powerful and flexible platform for creating and managing AI agents.
One-liner takeaway: AutoGPT is a game-changing platform that empowers users to automate tasks and workflows with ease, giving them back 10 hours every week to focus on what matters most.
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π§ Channel: https://t.me/GithubRe
14 146
π Spotted on GitHub Trending: TapXWorld/ChinaTextbook β let's break it down.
π https://github.com/TapXWorld/ChinaTextbook
π ζζε°ει«γ倧ε¦PDFζζγ
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ChinaTextbook is an open-source repository providing free access to Chinese textbooks, aiming to promote compulsory education and bridge the educational gap between regions.
The repository contains a wide range of mathematics textbooks for primary, junior high, and senior high school, as well as university-level mathematics materials, including linear algebra, discrete mathematics, and probability theory.
To use the repository, simply browse through the directories and download the desired textbooks. Note that some files may be split into multiple parts due to GitHub's file size limits.
To
merge these split files, you can use the provided mergePDFs-windows-amd64.exe program.
The target audience for this repository includes students, teachers, and anyone interested in Chinese education.
The takeaway: empowering education, one free textbook at a time.
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π§ Channel: https://t.me/GithubRe14 146
π₯ google/guava is trending β and it deserves your attention.
π https://github.com/google/guava
π Google core libraries for Java
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The google/guava repository is a collection of core Java libraries developed by Google. These libraries provide new collection types, such as multimap and multiset, immutable collections, a graph library, and utilities for concurrency, I/O, hashing, primitives, strings, and more.
To use Guava, you can add it to your build using Maven or Gradle, with two different "flavors" available: one for use on a Java 8+ JRE and one for use on Android.
Some key features of Guava include
Serializable support, Java 8+ compatibility, and a wide range of Java libraries.
Guava is suitable for Java developers of all levels, from beginners to experienced professionals, who want to simplify their coding process.
Overall, the google/guava repository is a valuable resource for any Java developer looking to streamline their workflow.
Guava simplifies Java development with its robust set of libraries - use it to upgrade your coding game!
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π§ Channel: https://t.me/GithubRe14 146
β‘ huangruiteng/loopx is making waves. Here's the full picture.
π https://github.com/huangruiteng/loopx
π Lightweight loop engineering state kernel for long-running AI agent teams. Agent-loop agnostic across Codex, Claude Code, and other coding agents, with durable goals, quota-aware auto-wake, executable todos, evidence logs, and verifiable handoffs.
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LoopX is a local control plane for long-running AI agent work, keeping objectives, gates, todos, evidence, and quota stable across turns. It's designed for loop engineering, allowing humans to manage and improve AI workflows.
Key features include:
* A
compact state kernel for tracking goals, todos, and evidence
* Agent-agnostic design, supporting various AI agents like Codex, Claude Code, and Cursor
* Human judgment integration, ensuring humans are involved in critical decision-making
To use LoopX, simply install it via curl and bash, then connect it to your project. You can start from your agent, such as Codex App or Claude Code, and use the loopx command to manage your workflow.
LoopX is useful for multi-day engineering, research, and experiment objectives, as well as issue and PR loops that require preserving scope, evidence, and review state. It's not an autonomous production controller, but rather a tool to help humans manage and improve AI-driven workflows.
The takeaway: Keep the loop moving, keep the judgment human.
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π§ Channel: https://t.me/GithubRe
14 146
β‘ goauthentik/authentik is making waves. Here's the full picture.
π https://github.com/goauthentik/authentik
π The authentication glue you need.
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Authentik is an open-source Identity Provider (IdP) for modern Single Sign-On (SSO). It supports various protocols like
SAML, OAuth2/OIDC, LDAP, and RADIUS, making it suitable for self-hosting in small labs to large production clusters.
You can install authentik using Docker Compose, Kubernetes (Helm Chart), AWS CloudFormation, or DigitalOcean Marketplace.
The project has a strong focus on development and contributions, with extensive developer documentation and a contribution process in place.
Security is also a top priority, with guidelines outlined in the SECURITY.md file.
Authentik is licensed under MIT License, CC BY-SA 4.0, and an Enterprise License for commercial use.
Takeaway: Authentik is your one-stop-shop for a robust, open-source identity management system that's free, flexible, and feature-rich.
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π§ Channel: https://t.me/GithubRe14 146
π mattpocock/skills caught my eye on GitHub Trending today.
π https://github.com/mattpocock/skills
π Skills for Real Engineers. Straight from my .agents directory.
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The mattpocock/skills GitHub repository offers a collection of skills designed to enhance your experience with coding agents like Claude Code and Codex. The purpose of these skills is to help you work more efficiently and effectively with AI-powered tools, addressing common issues such as misalignment, verbosity, and code quality.
Key features include grilling sessions to ensure you and the agent are aligned, a shared language to reduce verbosity, and feedback loops to improve code quality. The skills are small, easy to adapt, and composable, allowing you to customize them to fit your needs.
To get started, you can install the skills using the
claude plugins install mattpocock-skills command or by running npx skills@latest add mattpocock/skills. Once installed, you can use skills like /grill-me and /grill-with-docs to improve your workflow.
These skills are designed for real engineers who want to take control of their coding process and work more effectively with AI-powered tools. With these skills, you can ship better apps and improve your overall coding experience.
In short, mattpocock/skills helps you work smarter, not harder, with coding agents - try them out and see the difference for yourself!
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π§ Channel: https://t.me/GithubRe14 146
π Spotted on GitHub Trending: cloudflare/computer β let's break it down.
π https://github.com/cloudflare/computer
π Give your agent a computer πΎ
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The Cloudflare Computer is a virtual filesystem that lives inside a Durable Object, providing a unique way to manage and execute code in a cloud environment. It has three main backends: Container, Isolate shell, and Isolate JavaScript, each offering a different way to execute code and interact with the filesystem.
The
workspace.runtime.exec function is the main entry point for executing code, and it allows you to choose the backend and execute code in a flexible way. The Cloudflare Computer also provides a node:fs/promises interface, making it easy to work with the filesystem in a Node.js environment.
To get started, you can install the @cloudflare/computer package and follow the instructions in the README. There are also several examples in the examples/ directory that demonstrate how to use the Cloudflare Computer in different scenarios.
The Cloudflare Computer is suitable for experiments, exploration, and prototypes, but it's not yet ready for production use. The project is still in the preview phase, and the APIs are subject to change.
One-liner takeaway: Cloudflare Computer is a powerful virtual filesystem that enables flexible and scalable code execution in the cloud, and it's waiting for your feedback to shape its future.
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π§ Channel: https://t.me/GithubRe14 146
π Spotted on GitHub Trending: addyosmani/agent-skills β let's break it down.
π https://github.com/addyosmani/agent-skills
π Production-grade engineering skills for AI coding agents.
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The addyosmani/agent-skills GitHub repository provides a comprehensive set of production-grade engineering skills for AI coding agents. These skills encode workflows, quality gates, and best practices used by senior engineers across various development phases.
The repository includes 8 slash commands that map to the development lifecycle, allowing for automatic activation of the right skills. Key features include
/spec for defining what to build, /plan for planning how to build it, and /build for incremental implementation.
Technical highlights of the repository include the use of npx skills add addyosmani/agent-skillsnpx skills add addyosmani/agent-skills --skill code-review-and-quality