📦 jkudish/jev-mcp

Jev MCP: The Bouncer for Your AI Agent

Give your AI agent a built-in bouncer that actually reads the room. Jev MCP plugs into your coding assistant to run ten quick, cheap judgment calls. It screens fetched pages for sneaky prompt injections before they touch your context, verifies that every claim in a report matches the source, and even scores a code change to see if it is actually safe to merge. Instead of letting a massive, slow model guess, it uses a specialized model to return a typed verdict in under half a second for less than a cent. It is the difference between trusting a random intern and having a rigorous editor checking the work.

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📦 ghalebdweikat/winnow

Winnow: The Context Sieve for Claude Code

Winnow stops your coding assistant from wasting time reading irrelevant information. It acts as a smart filter that checks every large result from your code tools before the model sees it. A fast, specialized judge decides which parts of the file or command output actually matter for your current task. Anything deemed unnecessary gets swapped for a tiny summary, saving hundreds of tokens and keeping the AI focused. The full text is safely stored locally, so you can bring it back instantly if you change your mind.

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📦 ellipsis-dev/blink

Blink: Find Code by Asking Questions

Ask a plain English question to locate specific code files within a massive project. Blink uses an AI model to read directory names and assign likelihood scores to every path. It then releases hundreds of digital walkers that roam the file tree, with the most likely routes getting the biggest crowds. When a walker hits a file, it stops, and the final table shows which files captured the most traffic. This turns a chaotic search through nested folders into a simple probability report. It is a clever way to navigate complex codebases without manually guessing where to look.

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📦 skhanzad/selective-amnesia

Selective Amnesia: The Memory System That Forgets On Purpose

Selective Amnesia is the memory framework that teaches AI agents to forget on purpose. It builds a knowledge graph to track what a chatbot learns about you, but adds a smart pruning module that deletes less important details over time. This mimics how human brains work, keeping recent or critical facts while letting minor trivia fade away. By testing this against standard benchmarks, researchers show that this controlled loss of data actually helps the AI answer questions more accurately. It proves that for long-term digital memories, knowing when to drop information is just as vital as knowing what to keep.

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📦 modelscope/diffsynth-webui

DiffSynth-WebUI: Train AI Models in Your Browser

DiffSynth-WebUI runs the entire process of training custom AI models for images, video, and audio directly inside your web browser. Usually, fine-tuning these complex systems requires memorizing obscure command-line flags and manually editing text-based configuration files, which is a common source of errors and frustration for developers. This tool removes that technical barrier by replacing the terminal with a simple visual interface where you can upload your data, let AI automatically write descriptions for your images, and select training settings using clear menus. Because it tracks every choice you make, you can always reproduce your results later.

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📦 blackwell-systems/gcf

GCF: The Format That Speaks AI

GCF is the data format that finally lets AI read your info without the bloat. Instead of dumping giant blocks of JSON, it squeezes the same facts into a tiny, plain-text package that models understand perfectly. The real magic happens in long conversations. As your chat gets longer, GCF remembers what you already shared and only sends the tiny difference, dropping the cost by nearly one hundred percent. It is lossless, so nothing gets lost in translation, and it works with tools you already use. If you are building agents that talk a lot, this cuts your bills and speeds up every response.

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📦 quchangle1/turnsight

TurnSight: How AI Learns From Its Own Mistakes

TurnSight teaches AI models to learn from their own past mistakes without needing a human teacher. It works by looking back at a conversation where the AI already called a tool and saw the result. The system then compares what a smarter version of itself would have predicted with what the model actually did. By finding the gap between these two views, the model learns exactly where it went wrong in each specific step. This makes the AI much better at multi-step tasks involving external tools. It is a clever way to improve reasoning using only the data the model already generated.

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📦 tpyun/justdepth

JustDepth: Real-Time Radar Depth

JustDepth is the real-time radar depth tool that finally makes autonomous driving see clearly without expensive sensors. It takes a standard camera photo and a cheap automotive radar scan to instantly predict exactly how far away every object is. The magic happens because it skips the slow, messy steps usually needed to combine these signals. Instead, it compresses the radar data into a tiny, fixed-size format so the math stays lightning fast no matter how cluttered the road gets. This means your computer gets a complete depth map in under fifteen milliseconds.

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📦 snitro/pointer-cad-v2

Pointer CAD v2

Pointer CAD v2 is a new model from the recent computer vision conference that changes how computers draw technical designs. Instead of guessing shapes, it plans the construction steps first, using specific measurements to build precise parametric objects. The team says the actual code is still coming soon, so right now this is just the official announcement and paper details. It is interesting because it aims to make AI generated engineering drawings much more accurate and structured than before. This is a placeholder for a future tool, not a ready to use app.

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📦 kerpopule/hermes-jev-skills

Hermes Jev Skills: The Cheap Second Brain

Hermes Jev Skills is the agent plugin that offloads the boring decisions to a tiny, cheap model. Your expensive AI usually burns cash picking which model to use or which of hundreds of skills to load, but those are just picks, not prose. This project hands those quick choices to a specialized service that answers in under half a second, letting your main model focus entirely on the actual writing and thinking. It even sorts your inbox and picks the next browser click without you asking. If you run agents, this is how you stop paying premium prices for simple logic, keeping your setup fast and your costs down.

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📦 benvinegar/termdraw

termDRAW: The Terminal Drawing Editor

Sketch editable architecture diagrams, user interface mocks, and text-based graphics directly inside your command line. TermDRAW turns your terminal window into a functional drawing canvas where you can place boxes, connect them with lines, and add text labels using your mouse. Instead of generating image files, it exports your artwork as plain text or formatted markdown, making it perfect for pasting into documentation or tickets. This keeps your diagrams crisp, readable, and easily updatable without switching to a graphics application. If you want to keep your visual notes and code in the same place, this tool gives you a simple, text-native way to make it happen.

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📦 hydra-db/hydradb

HydraDB: The Graph Database That Lives on S3

HydraDB is the graph database that finally stops you from worrying about expensive, fragile hardware. It stores your entire graph directly on cheap, durable cloud object storage like S3, meaning your data survives even if your servers crash. Instead of keeping data on fast, local disks, HydraDB treats those disks as temporary caches that can be discarded and rebuilt anytime. This design lets you scale up or down without moving your data, keeping your graph safe and consistent while paying only for the storage you actually use.

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📦 tlennon-ie/cull

Cull: The AI Image Curation Engine

Your AI model is only as good as the photos you feed it. Cull solves the messy problem of finding, cleaning, and organizing those images. It scrapes sources like Reddit or local folders, then uses a vision model to grade every single photo for quality and relevance. It automatically filters out low-resolution or off-topic junk, sorting the keepers into clean folders with their prompts saved right next to them. No databases, just plain files on your computer. If you are building a custom model, this tool does the tedious grunt work for you, leaving you with a perfectly curated dataset ready for training.

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📦 openbkn-ai/bkn-foundry

BKN Foundry

BKN Foundry turns scattered business rules and expert knowledge into a network that artificial intelligence can actually execute. It acts as the engine room for a platform called OpenBKN, taking messy data from documents and systems and turning it into a structured map that agents can trust. This means software can do real work in your business with safety and clear tracking, rather than just guessing at answers. It is a backend foundation that provides secure data access and governance, letting machines verify every step of the process.

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📦 fullsend-ai/fullsend

Fullsend: Autonomous Code Agents

Fullsend lets software agents handle your entire coding workflow without human intervention. It reads new issues, writes the actual code to fix them, checks that work for errors, and pushes the final changes straight to your production servers. This tool targets teams using popular hosting platforms like GitHub and GitLab who want to move faster by automating the heavy lifting of development. The standout feature here is the complete cycle: it does not just suggest changes; it executes the entire process from discovery to deployment on its own. The design prioritizes security, ensuring these independent workers act safely within your existing systems.

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📦 heyputer/builder

Builder: The Open-Source AI Website Creator

This open-source tool lets you describe an app in plain English and watch it build itself right in your browser. It handles the boring backend stuff like user logins and databases automatically, so you can focus on design instead of infrastructure. It is basically the open-source version of those popular AI builders you see online. If you want to create a site without touching a single line of code, this project does the heavy lifting for you. It is a genuinely cool way to see your idea become a live website in minutes. Give it a spin if you want to skip the coding grind.

📰 https://news.ycombinator.com/item?id=49800217

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📦 uipath/skills

UiPath Skills: AI Knows Your Workflow

UiPath just handed AI developers the keys to their entire automation platform. Their new Skills repository is essentially a massive, structured brain for coding assistants, packed with hundreds of specific guides on how to build, deploy, and troubleshoot enterprise bots. The most surprising part is that it doesn't just show you how to drag and drop boxes; it teaches the AI how to write the actual code behind the scenes, like building custom API connectors or setting up complex logic flows from scratch.

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📦 antonio-ivanovski/spliit-cloud

Spliit Cloud: The Expense Splitter That Doesn't Need Your Email

Spliit Cloud is the open-source expense splitter that finally works across all your devices without forcing you to hand over your email address. It solves a common annoyance where shared trip costs vanish if you change phones, by storing your groups in a secure cloud account instead of just one browser tab. The surprising part is that you can create a completely anonymous account using just a display name and a recovery link, meaning no social media login or corporate identity required. This makes it easy to track shared bills, split bills with friends, and settle debts privately.

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📦 fluidinference/fluiduse

FluidUse: On-Device AI Form Filler

FluidUse automates boring form filling on your Mac by letting a tiny model decide what belongs in every field. It reads the screen through accessibility tools, asks a local model which option fits best, and types the answer into the real app in about one millisecond. Because everything runs on your chip, your data never leaves the machine, making it fast and private. It also handles quick yes-or-no questions on text, proving how light these decisions can be. No cloud, no lag, just instant help for repetitive work. Check out the project if you want smart automation that stays local.

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📦 tencentarc/gae-geometricautoencoder

GAE: 3D Video Generation

GAE is the video generation model that finally bakes three-dimensional structure directly into every frame it creates. Most AI video tools just guess at shapes, which often leads to objects warping or disappearing as the camera moves, but this system takes a single photo and a text prompt to render a full video sequence paired with an actual three-dimensional point cloud. It achieves this by learning a hidden space that understands physical geometry, ensuring the virtual world looks consistent from every angle. It is a powerful step toward making synthetic video as reliable as real footage.

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📦 tencentarc/gae

GAE: The Geometry-Native Latent Space

Tencent ARC’s new project, GAE, turns a single image and a text prompt into a multi-view video that includes a perfectly consistent three-dimensional point cloud. Most generation tools create flat pixels, but this system learns a compact internal representation where geometry is built into the data from the start. It compresses frozen features into a state that decodes into both color and depth, ensuring the virtual world stays physically coherent no matter how the camera moves. This approach solves the problem of generated scenes that look visually rich but fall apart in three-dimensional space. By embedding structure directly into the latent space, it allows for stable, realistic world generation.

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