📦 m-nabeegh/filemorrow

FileMorrow Keeps Your Downloads Private and Tidy

FileMorrow is a macOS app that organizes your Downloads folder without ever sending your files to the cloud. It uses on-device Apple Intelligence to sort documents into subject folders like Finance or Medical, while keeping everything local and private. You can undo any changes instantly, and the app safely finds duplicates and old installers to free up space. The best part is that it respects your privacy completely, meaning your files never leave your Mac. If you want a clean, safe way to manage your downloads without compromising your data, this tool is worth a look.

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📦 ransomleak/training-security-awareness

RansomLeak's 3D Office Training

RansomLeak is the open-source security training library that actually makes you learn by doing. Most corporate security courses are boring slide decks that people forget the moment they close the tab. This project flips that on its head by dropping you into a realistic, interactive thirty-dimensional office. You sit at a desk, pick up a phone, and face off against live phishing emails, scam calls, and tricky file downloads in real time. It is designed to build muscle memory, so when a real attack happens, your hands already know the right move. The entire collection is free, fully white-labeled, and ready to drop into any learning management system.

📰 https://news.ycombinator.com/item?id=48675551

🆔 @hackernewsgithubprojects

📦 gtapps/claude-code-hermit

Claude Code Hermit: The Agent That Actually Listens

Claude Code Hermit is the plugin that finally stops your coding assistant from forgetting everything between chats. Most tools reset their memory the moment you close the window, but this one stays awake, tracks its progress, and actually learns from its own mistakes. It watches for recurring issues, drafts fixes, and sends you a simple yes-or-no prompt via your phone so you stay in control without micromanaging. The best part is that it only uses energy when something actually happens, keeping your costs down while it works quietly in the background.

📰 https://news.ycombinator.com/item?id=49394794

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📦 local-inference-lab/llm-inference-bench

LLM Inference Bench: The Live Dashboard for AI Speed

LLM Inference Bench turns chaotic server logs into a live, breathing dashboard that shows exactly how fast your AI models actually generate text. Instead of guessing if your setup is fast enough, this tool tests your system across every possible combination of user load and prompt length, revealing precisely where performance breaks down. It automatically detects your backend and displays real-time GPU temperatures alongside token speeds, so you can see the physical hardware working in sync with the data. You even get instant accuracy checks against standard datasets to prove your model hasn't lost its brain during quantization.

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📦 vorssaint/vorssaint-utils

One Icon, A Dozen Mac Utilities

Vorssaint packs a dozen paid Mac utilities into a single free menu bar icon that runs entirely locally. You can install only the features you actually use, like a per-app volume mixer or window snapping, while the rest stays completely dormant. It’s privacy-focused, meaning no accounts, no telemetry, and no cloud dependencies. The app even tells you exactly which permissions each tool needs, so you keep total control over your machine. It’s the ultimate tidy-up kit for your Mac, all in one place.

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📦 lum1104/dsh-browser

dsh Browser Control: The AI That Clicks For You

Instead of using a headless bot, DSH Browser Control plugs an AI directly into your actual Chrome window. You can tell the model to fill out forms, click buttons, and read pages, and it does so using the tab you are already logged into. The interesting part is that the AI does not see the screen as an image. It reads a structured text version of the page and interacts with numbered buttons and fields. This means it works faster and protects your passwords by masking sensitive inputs before they leave your browser.

🆔 @hackernewsgithubprojects

📦 aravpanwar/decayfmt

decayfmt: Files That Dye When You Open Them

Ever watch a file rot away? No, not metaphorically. decayfmt is a Rust tool that permanently corrupts your images and text every single time you open them. You set how fast it decays by typing a number into the filename, like three for a slow fade or ten for instant static. It’s not encryption; it’s a social contract. The moment you view it, the damage is written to the drive forever, with no undo button. If you want the original, you better have a backup. It’s a weird, fascinating reminder that digital things don’t have to be immortal.

📰 https://news.ycombinator.com/item?id=49390206

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📦 notactuallytreyanastasio/shoehorn

Shoehorn: The AI Model That Fits Perfectly

Shoehorn is the tool that squeezes any large AI model into your computer's memory without wrecking its quality. Instead of guessing a standard compression setting that leaves wasted space or crashes your machine, it calculates exactly how much room you have. It then smartly decides which parts of the model deserve high precision and which can be compressed harder. The result is a file that fits perfectly into your hardware, letting you run massive models locally that would normally be impossible to host. You finally get the best performance your specific machine can handle, with zero guesswork.

📰 https://news.ycombinator.com/item?id=49299386

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📦 mengto/threeui

ThreeUI: The Open-Source 3D Component Catalog

ThreeUI is a fully open-source catalog of live, interactive 3D web components built with Three.js, and it runs entirely in your browser without requiring an account or login. It provides over fifty parent components and more than one hundred and sixty browseable results, including complex shaders, animated backgrounds, and interactive UI elements like liquid metal buttons and particle fields. The project’s unique value is its transparency; every single component comes with its complete, readable source code and assets, allowing you to copy, paste, and modify exactly what you see.

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📦 coleam00/skills

The PIV Loop: Cole's AI Coding Skills

Skills is the collection of thirty-three plain text instructions that turns coding agents into reliable software partners by enforcing a strict plan, implement, and validate workflow. Instead of relying on massive, static configuration files that confuse the model, this repository uses modular skills that load only when needed to keep context clean. The standout feature is the ability to run parallel investigations in separate git worktrees, allowing agents to diagnose issues and build features without ever touching your current working tree. It includes a meta skill that literally runs experiments to prove which of your custom rules actually matter and which are just dead weight.

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📦 wangeai/k3flight

Running a 2.8 Trillion Parameter AI on CPU

K3 Flight lets you run a massive two-point-eight-trillion-parameter AI model locally on your CPU, without needing a GPU. The model file is nearly a terabyte, but this tool uses a smart flight plan to load only the tiny piece of the brain needed for each word, keeping active memory around fifty-five gigabytes. It turns a hardware impossibility into a workable local server, proving that even the largest models can run on your desktop if you manage the data flow correctly.

🆔 @hackernewsgithubprojects

📦 fsmargoo/dsh-at-file

Point Your AI at Any File

Stop typing out long file paths for your AI. This plugin lets you type an ampersand in your prompt to search your entire project folder with one click. It acts like a smart autocomplete that finds any document, code file, or asset you need. The coolest part is that it doesn't stuff the file content into your chat. It just tags the file's location, letting the AI agent read it only when it actually needs to. This keeps your prompts clean and your context window tidy. It’s a simple, clever way to keep your AI grounded in your real work without the mess of copy-paste.

🆔 @hackernewsgithubprojects

📦 vivekhaldar/seed

The AI Agent That Builds Itself

A tiny AI agent starts life with just one tool: the ability to run shell commands. That is the entire starting kit for Seed. It does not come with pre-made skills, memory, or codebases. Instead, it grows its own brain. It writes notes, creates tools, and saves them in a local folder that acts as its persistent mind. Because it starts so small, you can see exactly how it thinks and changes. It is not a rigid framework; it is a living system that rewrites its own instructions after every chat.

📰 https://news.ycombinator.com/item?id=49384113

🆔 @hackernewsgithubprojects

📦 drstranded/co-rl

Co-RL: How AI Models Teach Each Other To Reason Without Labels

Train language models to reason by letting them grade each other's work without using any human labels. Co-RL, or Collaborative Reinforcement Learning, solves the problem of AI models getting stuck in bad loops when they only learn from their own feedback. Instead of training alone, this method uses a diverse group of different AI models to act as a team. Each model learns by looking at the answers of its peers, which breaks the cycle of repeating mistakes. This simple shift allows the system to figure out complex logic on its own. The result is a smarter model that improves without needing expensive, hand-made data.

🆔 @hackernewsgithubprojects

📦 embeddings-benchmark/embedders-dilemma

The Embedder's Dilemma: Why Cheap Beats Smart

This open-source benchmark puts ten large language models and twenty-six embedding models on the same stage for thirty-seven text tasks, but it stops there. It doesn't just measure accuracy; it tracks every dollar spent. The surprising result? While the biggest language models often win on complex reasoning, they are orders of magnitude more expensive than simple embedding pipelines. In fact, some tiny embedding models deliver nearly identical performance for mere cents. The repository provides the raw code, data, and scripts to reproduce every single chart from the paper without needing a GPU or an API key.

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📦 leonxlnx/unlazy

unlazy

Force your coding assistant to actually finish the job instead of cutting corners. AI agents have a nasty habit of stopping at eighty percent and confidently claiming victory while the code is still broken. Unlazy fixes this by making completion a strict, mechanical requirement. Before any work starts, the agent writes specific acceptance criteria into a file. Then, it has to run actual commands to prove each box is checked. It cannot just say it is done; it has to show the evidence. If the checks fail, the agent is blocked from ending the task until the work is truly complete.

🆔 @hackernewsgithubprojects

📦 thisislt/dapm

DAPM: The Drone Depth Breakthrough

A single photo from a tilted drone now reveals exact depth, solving a problem that has plagued aerial robotics. DAPM is the first model built specifically for drones to estimate depth and camera pose simultaneously, no matter how wildly the angle shifts. Existing tools fall apart when the camera tilts or zooms, but DAPM uses clever geometric tricks to keep the math steady. It even includes a new dataset called UAPD to test these extreme scenarios. If your drone navigation relies on accurate 3D maps from a single lens, this is the framework that finally handles the chaos.

🆔 @hackernewsgithubprojects

📦 lumosai8/comfyui-orbitsheets

ComfyUI OrbitSheets: The Fix for Inconsistent AI Character Views

Stop fighting inconsistent character designs by using ComfyUI OrbitSheets. This tool turns a single image into a perfect character reference sheet by rendering a continuous camera move around your subject. The key is that it doesn't just guess new angles; it captures one unbroken shot and then uses a vision model to pick the best frames. This ensures every view of your character matches perfectly, solving the problem where AI usually changes details like clothing or features between different shots. It is a clever way to get stable, professional-looking turnaround sheets without manually fixing errors in every single frame.

🆔 @hackernewsgithubprojects

📦 longin-yu/padoc

PaDoc: The Document Parser That Thinks in Trees

PaDoc is the document parsing tool that lets a single AI model read a whole page at once instead of crawling through it line by line. It works by having the model identify the layout first, then instantly branching off to read the text in each section simultaneously. This means you get the full content of a complex document much faster, without needing a second model or a complicated setup. It’s a clever way to make AI understand where things are on a page and what they say, all in one smooth motion.

🆔 @hackernewsgithubprojects

📦 zifacorp/zifamem

ZifaMem: Emotional Memory for AI Companions

ZifaMem is the memory framework that lets AI companions actually feel like they remember you. While most systems just store raw transcripts, this tool extracts emotional signals so your agent understands trust, conflict, and shared history. It doesn't just save facts; it lets memories fade or strengthen over time, creating a living relationship instead of a static database. This means your AI stops repeating old context and starts evolving with you, remembering what truly mattered in your dynamic. If you are building an agent that needs to feel genuinely personal, this is the layer you have been missing.

🆔 @hackernewsgithubprojects