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@cursor_ai is helping us ship 3× more committed code across large, complex codebases. By accelerating onboarding and automating workflows from code generation to debugging, we can scale development quickly — with measurable gains in both speed and quality. Learn more →
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Cursor AI Accelerates Code Shipping Across Complex Codebases
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HunyuanOCR Technical Report on Advanced Character Recognition
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HunyuanOCR Technical Report https://
bit.ly/4bkGbyA
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AgentLinter: Security Linter for Agent Configuration Files
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For vibe coders:https://t.co/lYlaCQ18g1 is the law your agent must follow.
— Ki Young Ju (@ki_young_ju) 7 février 2026
If it's naive, the agent trusts everything and leaks everything to hackers.https://t.co/CNh9dLb29Z scans and fixes https://t.co/lYlaCQ18g1 security issues in 30 seconds. It found 15 security issues in… https://t.co/QRE8LCH1k7 pic.twitter.com/SBCc3bWoJPFor vibe coders: claude.md is the law your agent must follow. If it's naive, the agent trusts everything and leaks everything to hackers. AgentLinter.com scans and fixes claude.md security issues in 30 seconds. It found 15 security issues in my agent. Highly recommend if you're running OpenClaw. Simon Kim (@simonkim_nft) AgentLinter is here! Is your agent sharp & secure? I built AgentLinter, a linter for CLAUDE.md and agent config files. Here's why. agentlinter.com Whether you're vibe-coding or agent-coding, your AI's output quality comes down to one thing: how well you wrote your CLAUDE.md. But managing these files properly? Way harder than it looks. 🎯 The Silent Failure Problem Vague instructions like "write good code" let the agent interpret however it wants. Output gets inconsistent, but nothing throws an error. The failure is silent. Anthropic's own docs say write "Use 2-space indentation" not "Format code properly." But as the file grows, spotting these with your eyes alone is nearly impossible. 🔐 The Security Problem People hard-code API keys and tokens directly into CLAUDE.md or TOOLS.md and commit them, way more often than you'd think. AgentLinter stats show 1 in 5 workspaces has exposed credentials. .gitignore doesn't catch secrets buried inside markdown files. 💥 The Consistency Problem Multiple config files = contradictions. SOUL.md says "be a friendly assistant," CLAUDE.md says "concise, direct tone." The agent gets confused. TOOLS.md references files that don't exist. Past 5 files, these conflicts triple. So I thought: CLAUDE.md is code. Code has ESLint. Why doesn't this have a linter? 🔍 What AgentLinter Does It diagnoses your agent config across 8 categories: 1) Structure: file organization 2) Clarity: instruction specificity 3) Completeness: missing definitions 4) Security: exposed secrets 5) Consistency: cross-file contradictions 6) Memory: session handoff 7) Runtime Config: gateway/auth settings 8) Skill Safety: dangerous shell commands & injection patterns Each scored 0–100 with concrete fix suggestions. Write "be helpful" and it tells you to specify response length, tone, and format. Find an API key? Instant CRITICAL alert to rotate. 🔒 Privacy-First & 100% Local Everything runs on your machine. Files never leave. Only the results are shared, and you can turn that off in settings. This matters — these files can contain system prompts, security rules, and personal context. Fully open source, MIT license, 100% free. 🛠️ Multi-Tool Support Works with Claude Code, Cursor, Windsurf, and Clawdbot. Detects CLAUDE.md for project mode, AGENTS.md or clawdbot.json for agent mode and adjusts diagnostics automatically. 🚀 Get Started with one line npx agentlinter Node.js 18+, no config needed. Run it, check your score, fix what needs fixing. Happy vibe-coding & happy agent life! 🤙 Website: agentlinter.com Github: github.com/seojoonkim/agentl… — https://nitter.net/simonkim_nft/status/2020004197693845716#m
→ View original post on X — @ki_young_ju, 2026-02-07 15:46 UTC
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Simple Innovations and AI Agents Transform the World
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It is humbling how simple innovations (in retrospect only) can profoundly change the world. “Claude Code does more than just code and is the best example of an AI Agent. You can interact with a computer with natural language to describe objectives and outcomes rather than
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Scikit-learn Cookbook (3rd Ed.) — 80+ Machine Learning Recipes
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Scikit-learn Cookbook — 80+ recipes for #MachineLearning in Python with scikit-learn [3rd Edition]: http://
amzn.to/4oDGOq7 v/ @PacktDataML 𝓒𝓸𝓷𝓽𝓮𝓷𝓽𝓼:
Common Conventions & API Elements of Scikit-Learn
Pre-Model Workflow and Data Preprocessing
Dimensionality -

Design Scalable Generative AI with LangChain on Google Cloud
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Generative AI on Google Cloud with #LangChain — Design scalable #GenerativeAI solutions with #Python, LangChain, and Vertex AI on Google Cloud: http://
amzn.to/4frbkPA v/ @PacktDataML 𝓚𝓮𝔂 𝓕𝓮𝓪𝓽𝓾𝓻𝓮𝓼:
Turn challenges into opportunities by learning advanced techniques -

Practical Guide to Building LLM and RAG Apps with LangChain
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"Generative AI and RAG for Beginners: A Practical Step-by-Step Guide to Building LLM and RAG Applications with LangChain and Python" Get your copy at http://
amzn.to/3MZZ9R5 Independently published: December 2025
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LangChain crash course for building OpenAI LLM apps
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#LangChain Crash Course — Fast track to building OpenAI LLM-powered Apps using #Python: http://
amzn.to/3TFlQJT
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#LLMs #AI #DeepLearning #GenerativeAI #ML #MachineLearning #LLMOps #DataScience #DataScientist -

Building practical OpenAI agents with Agents SDK
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"Building Agents with OpenAI Agents SDK: Create practical #AI agents and agentic systems through hands-on projects" at http://
amzn.to/4h6x1qg v/ @PacktDataML 𝓦𝓱𝓪𝓽 𝓨𝓸𝓾 𝓦𝓲𝓵𝓵 𝓛𝓮𝓪𝓻𝓷:
Understand the core principles of AI agents and why they matter
Use the OpenAI -

The AI Engineering Bible: Guide to Production-Ready AI Systems
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"The AI Engineering Bible: The Complete and Up-to-Date Guide to Build, Develop and Scale Production Ready AI Systems" Stay Ahead. Become Irreplaceable. …with this book: http://
amzn.to/4jOVbXG The AI Engineering Bible takes a full-stack engineering perspective—helping you