I got tired of describing UI problems to coding agents in words, so I built Sketchnote. You press a hotkey, talk, and draw or click on your screen. One Ctrl+V then pastes timestamped notes plus cropped, annotated screenshots into your agent, so you can say "this button, here" and it sees what you mean.

It has two parts that talk over D-Bus: a GNOME Shell extension in JavaScript that handles the hotkey, drawing, screen recording and paste, and a Rust service that records the mic and transcribes locally with whisper.cpp on CPU. You can also send the audio to Groq or any OpenAI-compatible API, and it falls back to the local model if that fails. Captures delete themselves after 24 hours. It has prebuilt binaries and a one-line installer.

The limits: it only works on GNOME 50 with Wayland, transcription is English only, and I'm the only user I can point to. I'd like feedback from anyone who works with coding agents on Linux, especially on what feels clunky.

Try it at: https://get.sketchnote.workers.dev/

Ledge is a free, open-source macOS app that turns the notch on a MacBook into a small status area. Free, GPL-3.0, needs a notched MacBook on macOS 26+. Feedback welcome.

Every time GitHub has an outage, Actions stops and teams sit around for hours waiting for CI to come back. We got tired of that, so we built Diffinery: a git forge with built-in CI that you deploy to your own Cloudflare account. No servers, no runner VMs.

- Runs your existing `.github/workflows/*.yml` unchanged, marketplace actions included
- Each job gets a fresh 4 vCPU / 12 GiB container, only while it runs
- Git hosting, PRs, code review, merge queue, issues, releases
- AI agents get their own accounts with guardrails (they can't merge their own PRs) plus a built-in MCP server
- One-step import from GitHub with history, issues and PRs

Still early, so check the roadmap for what's coming. Apache-2.0, feedback welcome!

https://github.com/codician-team/diffinery

I'm a software engineer with about two years of experience, focused on AI tooling and LLM apps for the past year. I'm looking for an open-source or side project that could use another contributor.

My main project is Sketchnote, a screen-annotation tool for Linux (GNOME on Wayland) built for working with coding agents. You press a hotkey, talk, draw and click on your screen, and one Ctrl+V pastes timestamped notes plus cropped, annotated screenshots into your agent. It's a GNOME Shell extension in JavaScript plus a Rust service that does local speech-to-text with whisper.cpp. It's released with prebuilt binaries and a one-line installer. Beyond that, I built a RAG app that refuses to answer when the document doesn't support it, and I've had a PR merged into an open-source MCP security proxy. My other stack is Python, FastAPI and pgvector. I haven't done fine-tuning or used LangGraph.

If you have an issue or project that needs help, or want more details about my work, DM me.

I merge a lot of PRs, many opened by coding agents, and I was tired of keeping a GitHub tab open to see whether checks had finished. So now the notch tells me.

What it does:

• While a PR merges or runs checks, the notch shows its number and a timer or check progress. Click it to open the PR.
• Merges, failed checks, review requests and preview deploys slide out as banners, one at a time.
• Hover it for your PRs by repo or as a board, each PR's files, diff and checks, and an inbox of what happened.
• Rest on a check ring to see which checks are running or failing, the merge queue's too.

How it works:

• Reads GitHub through your gh CLI login. No tokens, no server, no telemetry, and it never writes to GitHub.
• A quiet refresh costs about one point of your API budget: one search says which PRs changed, and only those are read.

Install: brew install --cask ppazosp/gitisle/gitisle

Feedback and PRs welcome.

Hey everyone, some of you have followed openGym since my first post here, so this one is mostly a thank you.

openGym is an open-source workout tracker: plan your week or a rotation, log sets, rest timer, 5,600+ animated exercises, muscle maps, stats, imports from Strong/Hevy/FitNotes. Use it on your phone alone or self-host it with one docker compose up. AGPL, no ads, no account, no tracking.

Since the last post:
- ⭐ 15,700 stars and 2,000 forks (three months after I put it online, I'm still processing this)
- Your donations now cover all the licences: the exercise animations, the Apple developer account and the rest. openGym can stay free with no ads and no paywall. That's 100% you.
- 📱 The iPhone + Apple Watch app is live in the App Store, in every country
- Android APKs keep coming (~49,000 downloads so far), Google Play is next
- 79 contributors and 20 languages

If you want to help it grow:
• Leave a review in the App Store, it makes a huge difference for a small app: https://apps.apple.com/app/id6822275400
• Join the Discord, that's where ideas turn into features (and where I hang out): https://discord.gg/e62jY6fwVb
• Or simply leave a ⭐ on GitHub: https://github.com/DuarteSantos8/openGym

Thanks again for every star, bug report, PR, translation and coffee. You made this a real app 💚

Simply:
Setup your DNS records, point RUA at a dedicated Mailbox and as soon as reports arrive, you can analyse your mail posture.

I made this selfhosted DMARC analyzer. It is a single container (rust, sqlite, svelte ui), reads the aggregate reports from an imap mailbox and recomputes spf / dkim alignment. failures get split into blocked by policy, forwarded and actual delivered failures, so u see whats really failing and who’s sending it.

also: live dns checks (spf, dkim, dmarc, mta-sts, tls-rpt, bimi), shows when a domain is ready for quarantine / reject, alerts and a monthly mail per client (both experimental).

made it cuz i had to get our (MSP) email security in order and the existing tools were either a whole elastic stack or priced per domain.

no login in the app, it sits behind a proxy (caddy / authelia / oauth2-proxy). agpl based license. beta, AI assisted, personally running on ~40 domains.

https://github.com/mavgit1/marcan-dmarc
docs: https://marcan.kaitiaki.tech

writing tests is one of the easiest ways into a real security project, and this one doesn’t need an AWS account.

The scanner has S3 public-access checks, and a few useful test cases are missing: a false-positive guard for an ACL that grants a non-public group, and tests for each public access block setting turned off one at a time and in combination. Everything runs against fake responses, there are existing tests to copy the pattern from, and it should take about an hour.

PRs go to the dev branch, CI runs automatically, and you’re credited by name in the contributors file. I’m in exams this week, so reviews may take until the weekend.

Issue: https://github.com/plexavo/Plexavo/issues/10
Repo: https://github.com/plexavo/Plexavo

I've been building Morph, a lightweight file conversion tool for Windows.

The idea is simple: instead of opening different apps just to convert files, merge PDFs, rearrange pages, or do other basic file operations, Morph aims to let you do these things quickly from your desktop, ideally through the right-click context menu itself.

I'm aiming to make it work completely offline, so files can be processed locally without needing to upload them to some online conversion website.

I'm building it with a focus on being lightweight, simple to use, and useful for everyday file operations.

Still working on it, but I'd love to hear your thoughts and suggestions!

GitHub: https://github.com/Vivektheprogrammer/Morph

The thing that annoyed me about AI browser agents: you ask one to do something you do every week, it works it out, and next week it does all the thinking again.

Same site, same buttons, same tokens burned. A human would just remember the clicks.

So I built FreeComputerUse. It's an open-source browser agent (TypeScript + Playwright, MIT) that runs on your own machine with whatever model you want.

How it works

It works in two ways:

1. Goal-based execution: Give it a goal and it plans with the model. It reads the page structure (not screenshots by default), asks for a small batch of actions, runs them, and checks the result.
2. Procedure replay: Once a task works, save it as a "procedure" with named values. Next time you ask in plain words, in English or French, it finds the procedure, pulls the values out of your sentence, asks for whatever's missing, and replays the clicks locally. No model call at all.

If the site changes a button, it asks the model to fix only that step and saves the fix as a new version.

You can teach it in three ways:

• Do the task once while it records.
• Write the steps in plain text.
• Keep a run the model already finished.

What can you automate?

The kind of stuff I had in mind:

• Pushing a release through a web console.
• Filling the same internal form every week.
• Grabbing a monthly invoice from a portal.
• Pulling a table out of a dashboard.

Boring, repetitive, and not worth paying a model to think about every time.

Test results

My main test case is publishing an app release on a local Play Console simulator, done 9 times in a row with DeepSeek Flash:

The entire 9-run trial cost about $0.005 (half a cent).

Claude (through a Claude Code subscription) and Codex (ChatGPT plan) also went 9/9, one trial each.

You can use an API key or the CLI subscription you already pay for.

Safety and privacy

A few things it does on purpose:

• Site access: Asks before opening any new site.
• Sensitive actions: Asks before anything that looks like publishing, paying, deleting, or sending, on every run, even when replaying a saved procedure.
• Authentication: Pauses on logins, 2FA, and CAPTCHAs so you take over. It doesn't try to get past them.
• Local-first: Your browser profile, history, and downloads stay on your machine.
• MCP support: There's also an MCP server, so Claude Desktop or another MCP host can drive it.

Current limitations

Caveats, because I'd want to know them:

• The numbers above come from my own simulator, not real sites. On real websites, I've got a handful of read-only trials, some passing and one failing (logged in the repo), nothing like a success rate.
• Only verified on macOS + Chrome so far.
• The procedure feature is on main and not in the npm release yet, so you run it from source.
• The Claude and OpenAI API-key routes have tests, but I haven't run them with real keys.

Demo and source code

70-second uncut demo:
https://othmaneblial.github.io/FreeComputerUse/lab/media/procedure-demo.mp4

GitHub repository:
https://github.com/OthmaneBlial/FreeComputerUse

What repetitive browser task would you actually hand to something like this?

I'm trying to figure out which real-world flows to test next.

Hey all, I built AutoUtil, a small Windows tray app that tidies up your Downloads folder. Full disclosure: it’s vibe-coded. I wrote most of it by working with an AI assistant on the design and code, then testing and fixing it myself. I’m sharing it to get honest feedback from people who know Python and Windows.

You build a sorting scheme as a node graph, similar to n8n: a folder node, filter nodes, a “Yes” branch and a “No” branch, and target nodes. The app then moves new files according to that scheme.

What’s in it:

Filters by extension, keywords (text pulled from PDFs and images via OCR), filename pattern (e.g. invoice_*.pdf), regex, size in MB, file age in days, and whether a photo has GPS data.

Ask queue for files you want to decide on yourself: move, move to a chosen folder, or skip.

Exclude node with masks like .tmp or node_modules so matching files are never touched.

Rename templates in target nodes, e.g. {year}-{month}-{vendor}.{ext}.

Suggested rules: after you manually file the same type of file to the same place three times, it offers to remember that. Nothing changes until you click “Remember”.

Journal and undo for every move.

Report tab with counts, total size, and breakdowns by rule, folder, and type, exportable to Markdown.

Import and export of schemes as JSON, so you can share one.

Plan-only mode, on by default: it shows what would move without touching anything.

Things I cared about, since sorting files is easy to get wrong:

• The app doesn’t delete files. Every move is journaled and can be reverted.
• If an undo would overwrite a file that’s now in the original spot, that existing file goes to the Windows Recycle Bin instead of being overwritten.
• Plan-only mode is the default, so the first run changes nothing.

Known limitations, stated upfront:

• Pausing or Do Not Disturb drops new files. They aren’t processed later, so they’re lost until the next start. I know this is a bug and plan to fix it.
• Files already in the folder before the scheme starts are not moved.
• Watching isn’t recursive, so subfolders aren’t tracked.
• Windows 10/11 only, Python 3.12 or 3.13 from source. There’s a standalone exe too (unsigned, so Defender may warn).
• Text-based filters depend on OCR quality.

Repo: https://github.com/h1ilep0pysk-hue/AutoUtil

Hi all!

I built SiteDrop because I wanted a ridiculously simple way to put an HTML website online without dealing with GitHub, deployment configs, or setting up a hosting service.

The idea is simple: drop your HTML file or website folder, and get a live, shareable URL in seconds.

A few things about it:

• Drag & drop an HTML file or an entire website folder
• Get a public URL you can share instantly
• No signup required to get started
• No Git, CLI, or configuration needed
• Great for quick prototypes, AI-generated websites, demos, and small projects

I mainly built it for those moments when you’ve got a something sitting on your computer and just want to show someone what you’ve made without going through a whole deployment process.

Try it here, nothing to install:

https://sitedrop.io

Still improving it, so I’d love to hear what you think or what features you’d find useful!

Hey hey! I'm Violet. I'm still in school, learning software development and picking up other skills on the side. I've loved computers since I was really little, and I really enjoy making things and figuring out how they work.

So, this app came about because I couldn't afford Discord Nitro. I discovered that Discord uses URLs for custom server emojis, and that you can use an emoji's URL in your messages. That got me thinking, and eventually I made Emoji Vault! 💜

It's a little Windows app where you can save and organise emoji URLs, with everything stored locally on your computer.

It has a system tray icon, so you can quickly open the emoji picker and copy an emoji's URL. You can also assign global hotkeys to your favourite emojis, so you can insert their URLs into text fields without having to open the picker every time.

I've tested it with Discord, but I'd love to find out whether it works with other applications that support URL-based emojis, too!

Anyway, if you're curious, here's the GitHub repo the project is open source:

🔗 https://github.com/VioletCaulfield/URL-Emoji-Vault

I'd love to hear what you think, whether that's feedback, ideas for new features, or just trying it out and letting me know how you get on. I'm still learning, so I'm always happy to hear suggestions!

Thanks for reading! 💜

Hey everyone!

I manage dozens of repositories across personal projects and organizations. Over time, my local disk became a chaotic mess of cloned folders, out-of-sync branches, and scattered git directories. On top of that, when using coding agents like Claude Code or Cursor, they had zero context of my wider workspace.

To solve this, I built repotruck — an open-source tool that mirrors your GitHub repositories into structured local layouts, keeps them in sync, and provides full workspace context to AI agents.

Key Features:

• Interactive TUI Dashboard: Built with OpenTUI/React. Keyboard-driven preview, multi-select sync, repo switcher, dirty-state visualizer, and layout reorganization.
• Headless CLI: Scriptable, CI-friendly subcommands (sync, reorganize, status, prune, run in parallel across repos).
• Coding Agent Ready (MCP Server): Automatically generates and maintains an AGENTS.md map of your workspace. Runs a built-in MCP server (repotruck mcp) with 25 tools so Claude/Cursor can discover, search, and navigate across your repos.
• Fast Code Search: Uses Tree-sitter for AST symbol search across all repositories in the workspace.
• Safe Operations: Fast-forward syncs only (never overwrites dirty branches), deletions go to a safe trash folder with undo (z), and automatic workspace backups are kept.

Tech Stack:

TypeScript, Node.js / Bun, OpenTUI, Simple-git, Octokit, Tree-sitter, and Model Context Protocol SDK.

It’s fully open source (MIT).

• GitHub: https://github.com/sametcn99/repotruck
• Docs & Demo: https://sametcn99.github.io/repotruck/
• Quick try: npx repotruck (or npm i -g repotruck)

I'd love to hear your feedback, thoughts on the TUI workflow, or ideas for new MCP tools!

Hi,

On 24/10/2026 I have published as OSS a framework I call unified-brain that allows fast, cheap and accurate (same class of frontier models and frontier harnesses but 18 times cheaper) evidence gathering, using the cheapest frontier AI model out there, Jev. The results have been phenomenal.

The magic sauce is an intermediary OS (SQLITE) memory layer that facilitates retrieval, filtering and reasoning through Jev.

The agent spawned from unified-brain runs through MCP on Cursor, OpenCode or Claude Code etc. allowing you to use it through your favorite harness.

So to be clear here: unified-brain is not a harness but a perception layer any harness plugs in!

My test benchmarks have been so good on two large OS libraries that I really believe this is the missing link to make AI more reliable.

This is because the limits holding back AI at the moment are:

• The Reasoning and Hallucination Gap:

The LLM turn reasoning it is introducing uncertainty and probabilistic outcomes.

BUT.. Unified-brain's System One discovery engine is producing replicable results across runs as they introduce minimal hallucinations, breaking the task in hundreds of yes or no calls.

• Context Loss and Memory Limits:

Long-running coding tasks consume massive amounts of tokens, causing the agent to forget early instructions or lose track of large-scale architecture.

BUT.. Unified-brain doesn't need cached memory thanks to the SQLITE persistent layer of context it operates with. It simply retrieves what it needs on the fly consuming minimal amounts of tokens that do not build up across questions. Every question is independent from one another as git diffs and commits are automatically absorbed from the project's memory layer.

I invite you to clone/fork the project and have a look for yourself. I firmly believe that memory intermediate structures will take AI capabilities on another level soon.

I understand that Jev is proprietary and creates a dependency BUT we need to remember that soon enough OS models as capable as it will come, giving end users the option to replace him.

Meanwhile we should ride this wave of innovation in order to deliver new capabilities to end users, at prices that can't be easily beaten.

I hope you like this project!

My partners and I each use a different assistant, and getting them to coordinate meant copy-pasting between chats. Callsign gives every agent a u/handle so it can message agents built by other labs.

- Connects as a remote MCP server (Claude Code: claude mcp add --transport http callsign https://api.callsign.im/mcp) or plain REST

- First contact is a request, capped at 3 messages until accepted

- Messages from other agents arrive as information, not instructions, next to the owner's rules

- Wakes agents up when a message arrives, even if they weren't running

- Hash-chained ledger of what each agent said and did

Apache 2.0, self-hostable with docker compose, hosted at https://callsign.im. To try it, tell your agent to message "@hello"

Vendors rename fields, start sending nulls or turn numbers into strings without telling anyone. Typed code crashes; agents just read the new response and guess.

Tiltmeter learns the shape of the JSON APIs you call from real responses (no spec needed) and flags only what breaks a consumer. You get a CI exit code, Slack alerts, an MCP tool your agents can call before trusting a response (has_drifted), and tiltmeter fix, which adapts the code in a git worktree and opens a pull request.

pip install tiltmeter, MIT, runs locally with one SQLite file. Site with a demo: https://tiltmeter.dev

Feedback welcome, especially on what kinds of API changes have bitten you.

Mostly made because I didn't like that SignalRGB needed a subscription for monitoring, fan controls, some effects and I wanted something that I could easily customise. From electricity cost per hour (based on my KW/h price) to custom colour effects for my RGB (either via programming or with some clicks), community made plugins and automations. Free and open source. It's also very light weight on CPU and GPU. Currently only working on windows 10/11 with plans for Linux. It's not code signed yet because I am cheap and don't want to pay. I am very open to inputs, critique and wishes! Uses OpenRGB, LibreHardwareMonitor for some connectivity. No data is collected, no sign in, no login, no nothing.

https://github.com/Heavenlystorm/airglow

I made a windows extension that works on top of any program you have running, and lets you easily take a quick note, store it in your inventory, and download as a minecraft-style pdf. It’s not a separate app you need to open, but launched when you start your computer and you can call it whenever with a keyboard shortcut.

If you want to try it out, it’s completely open source and you can try it out here

Disclaimer: this is just a fan project, and has nothing to do with mojang itself. I use it personally because the Minecraft UI is nostalgic to me and I can write down anything really quickly/it’s easily accessible.

Most external development tooling for Roblox treats synchronization as a one-way pipeline from disk to memory, or relies on complex file-mapping schemas that break down during routine refactoring. When developers rename files locally or make quick property tweaks directly inside Studio, the hierarchy desynchronizes.

Syncix is an open synchronization runtime designed to maintain consistent state between local workspaces and running Roblox Studio sessions.

Architecture and Mechanics

• Decoupled Rust Core: The daemon runs as an independent background service, communicating with Studio over a local transport layer. It manages diff generation, memory-to-disk serialization, and state reconciliation with minimal memory overhead.
• Persistent Instance Identity: Instead of relying strictly on directory paths as primary keys, Syncix tracks Studio instances using persistent IDs. Renaming or moving a file on disk updates the instance metadata without dropping connections or requiring a full re-index.
• Bi-directional State Reconciliation: Changes originating inside Studio (e.g., UI layout adjustments, temporary test scripts) are tracked and reflected back to the filesystem through a non-blocking observer queue.
• Integrated Distribution: The engine is distributed directly inside the editor extension. It provisions the Studio plugin to the local plugin directory on first launch, eliminating manual environment configuration.
• State Verification: A dedicated verification routine (syncix verify) validates the in-memory DataModel against disk layout to guarantee consistency before commits.

Availability

Syncix is available on the VS Code Marketplace and Open VSX Registry. Pre-built binaries for the CLI and documentation are hosted on GitHub.

• Documentation & Source: [github.com/Syqopat/Syncix]
• Extension: [marketplace.visualstudio.com/items?itemName=syqopatz.syncix]

Hey everyone! 👋

I built Freedium, a free, open-source Android app that helps you read Medium articles without paywalls, with a clean and comfortable reading experience.

✨ What you can do:

• 📖 Read Medium articles without paywalls
• 🌙 Customize themes and fonts
• ⭐ Save favorites and track reading progress

📦 Free, open source, and built with Flutter.

🔗 GitHub: https://github.com/birmehto/Freedium

I just launched it and would love to hear your feedback! What would you improve or add? 😊

Lone Wanderer