🔥 anthropics/claude-code
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows - all through natural language commands. — Trending on GitHub today with 10749 new stars.
Claude Code is an agentic coding tool that lives in your terminal, understands your codebase, and helps you code faster by executing routine tasks, explaining complex code, and handling git workflows -- all through natural language commands. Use it in your terminal, IDE, or tag @claude on Github.
Learn more in the official documentation.
Get started
Note
Installation via npm is deprecated. Use one of the recommended methods below.
For more installation options, uninstall steps, and troubleshooting, see the setup documentation.
- Install Claude Code:
MacOS/Linux (Recommended):
curl -fsSL https://claude.ai/install.sh | bash
Homebrew (MacOS/Linux):
brew install --cask claude-code
Windows (Recommended):
irm https://claude.ai/install.ps1 | iex
WinGet (Windows):
winget install Anthropic.ClaudeCode
NPM (Deprecated):
npm install -g @anthropic-ai/claude-code
- Navigate to your project directory and run claude.
Plugins
This repository includes several Claude Code plugins that extend functionality with custom commands and agents. See the plugins directory for detailed documentation on available plugins.
Reporting Bugs
We welcome your feedback. Use the /bug command to report issues directly within Claude Code, or file a GitHub issue.
Connect on Discord
Join the Claude Developers Discord to connect with other developers using Claude Code. Get help, share feedback, and discuss your projects with the community.
Data collection, usage, and retention
When you use Claude Code, we collect feedback, which includes usage data (such as code acceptance or rejections), associated conversation data, and user feedback submitted via the /bug command.
How we use your data
See our data usage policies.
Privacy safeguards
We have implemented several safeguards to protect your data, including limited retention periods for sensitive information, restricted access to user session data, and clear policies against using feedback for model training.
For full details, please review our Commercial Terms of Service and Privacy Policy.
Sign in to highlight and annotate this article
Conversation starters
Daily AI Digest
Get the top 5 AI stories delivered to your inbox every morning.
More about
githubtrendingopen-source
How to Finally (and Iteratively) Kill Every Last 'npm audit'
Let’s be honest: npm audit is a necessary evil. If you manage a monorepo, a large scale-backend microservice architecture, or even just have fifty toy projects in your /dev folder, you know the dread. You run an audit, get 400 vulnerabilities, and standard npm audit fix just breaks things. The real problem isn't fixing the vulnerability; the problem is the management of the vulnerabilities. Manually cd -ing into 30 different directories, running the audit, deciphering the output, deciding which package.json to edit, and then doing the work? That's an efficient way to burn out an afternoon. Here is the tool you didn’t know you needed. The Problem: Multi-Directory Triage You are working across multiple contexts (multiple directories). You have dozens of tasks: Find the package.json . Navigat
How We Cut Claude Code Session Overhead with Lazy-Loaded Personas
If you use Claude Code with a heavily customized CLAUDE.md , every message you send carries that full file as context. Not just once at session start — on every turn. That matters more than most people realize. The Problem: Eager-Loading Everything The naive approach to building a multi-persona system in Claude Code is to define all your personas directly in CLAUDE.md . It feels clean — everything in one place, always available. The cost: if you have 23 specialist personas, each defined in 150-200 lines, you're looking at 3,000-5,000 tokens of persona definitions loaded on every single message — regardless of whether the current task has anything to do with a UX designer or a financial analyst. Claude Code's CLAUDE.md is not a one-time setup file. It is re-injected into context on every tu
The Type System: What You Know, What's New, and What's Weird
My project: Hermes IDE | GitHub Me: gabrielanhaia You'll reach for class hierarchies and abstract classes. Stop. TypeScript has something better for most of those cases. In Post 1 , we covered the big mental shifts: structural typing, type erasure, null vs undefined, how overloading isn't really overloading. That was the "prepare yourself" post. This one is where we actually build things with the type system. I'll split it by feel: the stuff that'll be instantly familiar, the stuff that's genuinely new, and the stuff that'll trip you up because it looks familiar but behaves differently. Primitives, Arrays, Objects: The Familiar Stuff I'll keep this short because you already know what types are. const name : string = " Gabriel " ; const age : number = 31 ; const isActive : boolean = true ;
Knowledge Map
Connected Articles — Knowledge Graph
This article is connected to other articles through shared AI topics and tags.
More in Open Source AI
Show HN: Screenbox – Self-hosted virtual desktops for AI agents
Screenbox gives AI agents their own isolated Linux desktop with a real Chromium browser, controlled via MCP. I run multiple agents in parallel and they kept fighting over the same browser. Each desktop is a Docker container (~2GB RAM, no GPU). You can watch agents work in real time and take control when needed. Open source (AGPL-3.0), self-hosted. Site: screenbox.dev GitHub: github.com/dklymentiev/screenbox Comments URL: https://news.ycombinator.com/item?id=47617846 Points: 1 # Comments: 0
p-e-w/gemma-4-E2B-it-heretic-ara: Gemma 4's defenses shredded by Heretic's new ARA method 90 minutes after the official release
Google's Gemma models have long been known for their strong "alignment" (censorship). I am happy to report that even the latest iteration, Gemma 4, is not immune to Heretic's new Arbitrary-Rank Ablation (ARA) method, which uses matrix optimization to suppress refusals. Here is the result: https://huggingface.co/p-e-w/gemma-4-E2B-it-heretic-ara And yes, it absolutely does work. It answers questions properly, few if any evasions as far as I can tell. And there is no obvious model damage either. What you need to reproduce (and, presumably, process the other models as well): git clone -b ara https://github.com/p-e-w/heretic.git cd heretic pip install . pip install git+https://github.com/huggingface/transformers.git heretic google/gemma-4-E2B-it From my limited experiments (hey, it's only been
Discussion
Sign in to join the discussion
No comments yet — be the first to share your thoughts!