📦 sazardev/goca

Goca

Build perfectly structured Go applications in seconds without writing any boilerplate code. If you are starting a new Go service, this tool scaffolds an entire Clean Architecture setup with one command. Instead of manually creating domain entities, use cases, database repositories, and HTTP or gRPC handlers, you just tell it what fields you need. It generates clean, decoupled layers, hooks up dependency injection, and even writes your integration tests automatically. It even includes safety guards like dry-run previews and automatic file backups so you never accidentally overwrite your work. Grab goca and start writing clean Go code today.

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📦 rodiun/frugon

Frugon

frugon is the local command-line tool that finally shows you how to slash your artificial intelligence bills without sending your private data anywhere. It runs entirely on your own machine, analyzing your raw API logs to calculate exactly how much cash you would save by swapping out expensive models for cheaper alternatives. You can set up its local proxy shim to capture your traffic, and the tool immediately highlights which simple requests can be routed to budget-friendly models and which complex ones need the premium tier. It is the ultimate way to stop overpaying for token usage and optimize your setup today.

📰 https://news.ycombinator.com/item?id=48816724

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📦 markfulton/claude-antigravity-agents

claude-antigravity-agents

The claude-antigravity-agents skill is the Claude Code extension that finally lets you run heavy background coding tasks in parallel without burning your subscription tokens. It turns Claude into an active orchestrator that delegates massive jobs like full-repo audits, security reviews, and large refactors to Google's Antigravity CLI. While you and Claude keep building your main features, a secondary model runs the grind work in an isolated background sandbox. Once the sub-agent finishes, Claude automatically runs build checks and reviews the code changes before merging them, giving you a safe, multi-model workflow that multiplies your coding speed.

📰 https://news.ycombinator.com/item?id=48817248

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📦 gokapso/whatsapp-cloud-inbox

WhatsApp Cloud Inbox

Manage multiple corporate chat accounts from a single dashboard using an elegant web interface. This project handles the official chat network API, giving you a shared interface that mimics the familiar messaging experience. The coolest part is how it automatically solves API limitations, like checking if your last customer interaction was within twenty-four hours and switching to authorized messaging templates if it has been longer. It handles custom interactive buttons, documents, and live media while tracking read receipts across different business numbers. Try running this simple self-hosted setup to keep all your customer chats organized in one place.

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📦 op7418/guizang-material-illustration

guizang-material-illustration

guizang-material-illustration is an AI assistant skill that creates high-quality explanatory diagrams and material-style charts featuring integrated Chinese text labels. Instead of generating generic decorative images, it translates complex ideas, data, or concept drafts into clear visual guides like flowcharts, mechanism diagrams, and beautiful 3D charts. By focusing on the central illustration layer, it cleanly extracts data from messy screenshots or raw text, packages the visual metadata, and renders readable diagrams perfect for slides, documentation, or social media cards. It is an incredibly clever tool for transforming abstract explanations into instantly understandable visual summaries.

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📦 anomalyco/terminal-control

terminal-control

Terminal-control is the terminal testing tool that lets AI agents and developers drive complex terminal applications with actual screen-based feedback. Instead of blindly guessing from raw text logs, this tool creates a real virtual terminal, allowing you to start background sessions, send precise keystrokes, and read the visible screen exactly as a human sees it. You can write robust automated tests, wait for specific on-screen text, and even capture screenshots or record MP4 videos of terminal sessions. It takes the guesswork out of terminal automation by providing a stable, reliable way to control, inspect, and test interactive terminal apps.

📰 https://news.ycombinator.com/item?id=48867841

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📦 dicklesworthstone/destructive_command_guard

Destructive Command Guard

AI coding assistants are incredibly productive until they accidentally run a rogue command that wipes out your entire database or deletes your git history. That is why destructive_command_guard is such a clever project: it acts as a high-speed firewall specifically designed to intercept and block dangerous terminal commands before an AI agent can execute them. Built in Rust for blazing speed, it parses incoming tool requests, runs them through a modular safety checklist, and instantly stops destructive operations while offering safe alternatives. It is a simple, brilliant way to let autonomous agents write your code without worrying they will accidentally destroy your entire workspace.

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📦 gostonx/uninstally

Uninstally

Uninstally is the native macOS uninstaller that finally cleans up the hidden junk other apps leave behind when you throw them away. Instead of just dumping an app in the Trash, it uses smart bundle detection to hunt down orphaned caches, logs, and support files buried deep in your system. You get a built-in safety score to preview exactly what is being deleted, batch uninstall tools, and even a right-click Finder menu to wipe apps instantly. It runs entirely on your Mac with zero trackers. Next time you clean house, let this app do the deep scrubbing.

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📦 jbarrow/commonforms

Commonforms

Static PDF documents can now be automatically transformed into interactive, fillable forms using open-source machine learning models. A new tool called commonforms analyzes the layout of any standard PDF to detect where empty spaces, text boxes, and signature areas should go, instantly embedding functional input fields. Instead of manually drawing boxes in expensive editing software, developers can run a single command in their terminal or write a few lines of Python code to update their files. It uses specialized lightweight models trained on a massive custom dataset to accurately pinpoint form fields, making digital paperwork dramatically easier to handle.

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📦 nebusec/cybermeowfia

cybermeowfia

A security vulnerability called GhostLock has quietly lingered inside every single Linux distribution for fifteen years, and researchers just released the code to prove it. The cybermeowfia repository gathers real-world proof-of-concept exploits for critical vulnerabilities discovered by the security team at Nebula. Its main focus is a sophisticated memory flaw in the Linux kernel where timing-based lock requests are forced into a state of confusion. By carefully coordinating background threads and manipulating process scheduling, the exploit bypasses kernel protections to gain complete control. It is a fascinating look at how tiny, decades-old code oversights can eventually lead to complete system takeovers.

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📦 vinhhien112/three.js-object-sculptor-codex-plugin

Three.js Object Sculptor

You can now transform flat images into interactive, animation-ready 3D models using pure code. Instead of relying on heavy mesh files or photogrammetry, the three.js-object-sculptor-codex-plugin uses a brilliant AI-guided workflow to analyze an image, plan the structure, and write a procedural Three.js factory in TypeScript. It blocks out the shapes, layers realistic physical materials, and sets up real pivots and joints so the object is ready for physics and motion. It even compares browser screenshots against the original image to auto-correct itself, giving web developers lightweight, highly customizable 3D assets directly from a reference photo.

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📦 robtand/prismaquant

PrismaQuant

Most mixed-precision tools guess how to compress artificial intelligence models, but PrismaQuant actually measures end-to-end performance to find the perfect fit. Instead of forcing every part of a massive language model into the same restrictive format, this clever allocator analyzes each individual layer to see exactly how sensitive it is. It assigns higher precision to the critical parts and compresses the rest using a fast mathematical knapsack solver. By validating every decision against real performance metrics, it produces incredibly light models that run natively on standard engines like vLLM with zero custom software required. It is the ultimate way to shrink your models without sacrificing their intelligence.

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📦 davidhariri/life-system

Life System

Your local AI is finally ready to help you run your life from the terminal instead of just writing code. A minimal template called life-system uses Claude Code to transform markdown files into an interactive, deeply personal life planner. It works by having the AI read your long-term goals and values before every session, meaning it will actively call you out when your daily task list drifts away from what you actually said matters. You manage your schedule, daily journals, and decisions in plain text, while a custom command-line skill allows the AI to act as an objective, zero-subscription accountability partner that never forgets your plans.

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📦 aashish-thapa/wlctl

wlctl

Manage your Linux wireless, wired, and VPN connections straight from your terminal with wlctl. If you love the clean keyboard-driven interface of modern terminal tools but do not want to rip out your default network manager stack, this tool has you covered. It runs beautifully on top of NetworkManager, letting you toggle saved VPNs, import WireGuard configurations by pasting text, and see exactly which connection is routing your traffic. It even includes a built-in doctor mode to instantly troubleshoot network issues when things go wrong. Give it a spin to keep your hands on the keyboard and your connection solid.

📰 https://news.ycombinator.com/item?id=48868851

🆔 @hackernewsgithubprojects

📦 fabiotosi92/zipdepth

ZipDepth

You can now run state-of-the-art 3D depth estimation on a standard mobile phone in real time. This is possible thanks to zipdepth, an incredibly compact model that packs the power of massive AI foundation models into a tiny, six-million-parameter package. By learning directly from giant vision networks, it calculates the depth of any scene—from night driving to close-up textures—without needing any fine-tuning. It runs fast on everyday hardware, shifting effortlessly from high-end graphics cards to portable devices. For developers, this means you can build instant, zero-shot 3D depth mapping directly into on-device applications.

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📦 meigen-ai/opsd-v

opsd-v

opsd-v is the post-training framework that finally keeps long-form AI videos from falling apart after just a few seconds. Usually, when you generate long videos in short chunks, the AI relies on its own messy, half-baked history to write the next frames. Naturally, small errors build up until the motion freezes or turns to absolute mush. This project solves that by using real, clean video history as a smart teacher during training, while the model practices generating the next step. It learns to correct its own drift, giving you rock-solid, extended motion without slowing down the actual generation process at all.

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📦 hku-mmlab/uniclawbench

UniClawBench

UniClawBench is the evaluation benchmark that finally tests how smart AI assistants really are when left alone with a computer. Instead of just asking these digital agents simple questions, it drops them into a secure virtual environment to see if they can actually solve multi-step problems. It challenges them to browse the web, edit files, use desktop applications, and figure things out across four hundred distinct bilingual tasks. A hidden evaluator watches their moves and grades their success, while a visual dashboard lets researchers inspect exactly where the systems got stuck. It is a major step toward building AI that can safely handle real-world desktop chores.

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📦 tommasocerruti/linear-attention-architectures

linear-attention-architectures

The linear-attention-architectures repository is a research toolkit that makes scaling alternative language models incredibly simple by integrating modern linear attention mechanisms directly into a powerful training framework. Instead of relying on standard, resource-heavy attention, this project implements clever alternatives like DeltaNet and smart cross-layer routing strategies to pass key information smoothly through the model layers. It is built as a specialized fork of Megatron-LM, meaning you can easily train and test these fast architectures at a massive scale using ready-to-go SLURM launch scripts. If you want to experiment with highly efficient architectures without building the scaling infrastructure from scratch, this is your perfect playground.

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📦 lionsr/tnlean

tnlean

Researchers have successfully formalized the fundamental theorem of matrix product states in Lean 4. This math library, called tnlean, mathematically proves how different tensor representations generate the exact same physical quantum states. By translating complex quantum physics concepts into computer-verified proofs, it rigorously shows that these identical states are mathematically locked together by a change of basis. This project builds a solid foundation of computer-checked quantum information theory, including quantum channels and representations, ensuring absolutely zero room for human error in the math. It is a brilliant example of how modern coding tools are making cutting-edge quantum physics completely airtight.

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📦 cvsp-lab/moe-gs-studio

MoE-GS Studio

Researchers have figured out how to combine different 3D rendering algorithms into a single system that handles movement and motion far better than before. The repository moe-gs-studio serves as a central hub for this new approach, which uses a mixture of specialized AI experts to divide and conquer the complex task of rendering dynamic 3D scenes. Instead of relying on one massive, slow model to calculate how objects bend and move, this project coordinates multiple smaller, specialized models that work together in real-time. It is an exciting step forward that makes creating high-fidelity, movable digital worlds much more practical and efficient.

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📦 ugness/self-conditioned-fmlm

self-conditioned-fmlm

Generating high-quality text using continuous flow models usually requires dozens of slow, sequential steps, but a clever new approach achieves state-of-the-art text generation in just one or two steps. The project self-conditioned-fmlm implements a training technique called fixed-point flow distillation. Traditionally, models use self-conditioning to clean up their own drafts, but nobody quite understood how to optimize this for ultra-fast generation. This repository proves that self-conditioning is actually solving a mathematical fixed-point iteration, compressing that entire complex process into a highly efficient model. If you are experimenting with fast language generation, you can run this distillation pipeline to build incredibly fast text generators.

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