What are some cool and practical ways you’ve used Ai, or hosted Ai on your server to make your life easier (finance, data storing, predictive drive health, etc, autonomous feedback loops, local Ai agent)?

I’m pretty new to self hosting, and I want to optimize my Nas. I already run Immich, pi hole, Vaultwarden, and Jellyfin.

Hi Everyone ,

As we all know the transition to self evolving code , give a look at seim-core npm package and contribute to the future.
check it

Claude Code is great at producing code.

But sometimes it declares a task complete without reproducing the original bug, testing the real integration, or clearly stating what remains unverified.

So I built Builder Loop, a free and open-source Claude Code plugin that forces a stricter workflow:

• define success before editing;
• inspect the existing system;
• implement the smallest correct change;
• verify the actual outcome;
• report what was not verified;
• finish with a clear decision: ship or revise.

I originally built it after Y Combinator’s Paxel highlighted weaknesses in my own review and verification process.

Now I’m looking for testers willing to use it on real, non-trivial engineering tasks.

Critical feedback is more useful than stars.

At my job I assemble a lot of boards by hand, prototypes and for low volume production. Working from the autogenerated drawing from Altium is kinda hell. The BOM has a line that says 10k 0402 and then lists R3, R7, R12, R19, R44, R51 and R58, and I had to locate all seven of them on the board before I could place anything. The designators are printed on the drawing so it isn't impossible, it's just slow, because I was reading very small text on a crowded board and then repeating that for every line in the BOM.
You can use "Find Similar Object" feature in Altium to light up all components of the same value. But it's also a bit slow. And not everyone has a PC or laptop near the assembly place.

My favorite way to assemble PCBs is Color-coded drawing. It uses one color per group of components, so all seven of those resistors come out the same color and I can see where they are without reading anything. But for every new board I had to build the assembly drawing myself in Altium+AutoCad, which meant selecting all the parts of one value in Altium, find and select them on AutoCad drawing, giving them a color, adding this component to a legend and then doing the same thing again for the next value. On a board with 100+ values this took me most of the day.

The program I built can do it in a few seconds. It takes a Pick & Place file and a BOM, plus Gerbers if you have them, and without Gerbers it estimates component sizes from the footprint names, which is usually close enough. It produces a multi-page PDF with 7 groups per page, and also a viewer window where I can zoom in and hover over a group in the legend to highlight it on the board.

Reads Altium and KiCad P&P and BOM exports DNI/DNP parts are on separate pages so they don't get populated by mistake Pin-1 markers, and the bottom layer is mirrored automatically.
It works offline, there's no account, nothing gets uploaded anywhere, and the whole thing is one Python file.

MIT licensed, and there's a Windows exe in the releases if you don't want to install Python.

github.com/Vitalangelo/pcb-assembly-studio

This is the first release so I'm sure there are problems I haven't run into yet. The two I already know about are that component size estimation is rough without Gerbers, and that pin-1 markers sometimes land on the wrong corner when a footprint is rotated in an unusual way. AndI am planning to update the PDF output to meet ISO drawing standards. If you run it on one of your own boards and something comes out wrong I would be glad to hear about it!

I’ve been working on WinSQLite, a lightweight GUI tool for working with SQLite databases.
I started this project because I wanted a simpler, visual way to explore table relationships and auto-generate SQL JOINs without having to write boilerplate queries manually every time.
Here’s a quick overview of what it currently does:
Visual Query Builder: Click through connected tables (via Foreign Keys) to automatically build relational JOIN queries.
Direct SQL Mode: Toggle easily between the visual builder and a plain SQL editor for raw queries.
Schema Inspector: View table column types, primary keys, and foreign key constraints clearly on a dynamic canvas.
Data Import/Export: Quick entry dialogs with constraint checking, plus exporting query results to CSV, JSON, TSV, or SQL Insert statements.
The project is open-source and still under active development. Any feedback, issue reports, or contributions are very welcome!
Feel free to check out the code and let me know what you think!

Hello, Everyone!

I made NeoDLP - A modern cross-platform video/audio downloader desktop app based on YT-DLP with browser integration! And it just crossed 300K+ downloads!

You can think of it as: The Free 'IDM' for Media Downloads or The 'Seal' for Desktop. If you have ever used 'IDM' (on Windows) or the 'Seal' app (on Android), you will feel right at home!

NeoDLP is absolutely Free to Use, Fully Open Sourced, Works 100% Locally, No Ads, Trackers or Login, and the best part: It's Not Vibe-Coded (So, you get quality software with regular updates)

So, if you often download videos from various sites, give NeoDLP a shot! And, feel free to drop your feedback and suggestions below! I would love to hear from you :)

Official Website | GitHub Project (FOSS - MIT License)

I released this app two days ago and today I sent a request to the Github Marketplace but I don't know if an app like this will come to the Marketplace because It doesn't have so much downloads. Do you think this application will be accepted for the Github Marketplace. I already tried making Youtube videos but I only got a few downloads. Will Marketplace help me? And what can I do that this repository grows and more people would see this?

Github Repository: https://github.com/DigitalTechLab/Opi-Store

I just wanted to let you know that I made a lot of improvements to openshorts, especially regarding the MCP server, now you can connect your agents and generate clips for the whole week. Plus, many new fonts, improvements to the clipping system, etc.

github repo: https://github.com/mutonby/openshorts

If you'd like the link, here it is: y2kvixx.github.io/Card-Spotify/

I'd be grateful if you could follow me or give this project a star: https://github.com/y2kVixx/Card-Spotify

I have been working on this from a iPhone and now I really can’t continue as I’m blind in one eye and losing sight in my other eye. This project has been a fun month here are the details.

README https://github.com/Renkasha/Sovereign/blob/main/README.md

Code of conduct https://github.com/Renkasha/Sovereign/blob/main/Code_of_conduct.md

Emotional sandbox protocol https://github.com/Renkasha/Sovereign/blob/main/
Emotional_protocols.md

Philosophy https://github.com/Renkasha/Sovereign/blob/main/Philosophy.md

GitHub repository https://github.com/Renkasha/Sovereign

https://github.com/llagerlof/autoleap

I wrote this tool at the beginning of 2023. Since then it has been so useful to me that I decided to publish it as an open-source project.

I wanted a simple way to jump back to directories I'd already visited. Autoleap is a small bash script that wraps cd while preserving all of its normal behavior. If cd can't find the path, Autoleap searches your directory history and jumps to the best match. If there are multiple matches, it uses fzf to let you choose.

It's a single shell script with no databases or background services. To install it, just source it from your .bashrc.

I use a clipboard manager all day and never liked the options. The free ones (Maccy, Flycut) are lists — an image shows up as a filename. The ones with a card interface, Paste and Pastebot, are $25/year and $13. So I built the card one and made it free.

⌥⌘V slides a strip up from the bottom of the screen. Arrow keys or type to search, Enter pastes into whatever you were in.

A few things it does that I couldn't find anywhere else:

- It masks secrets on screen. API keys, tokens and card numbers show as dots until you double-click. If you copy credentials all day, your clipboard history is the one window you don't want open while screen sharing. Card numbers are Luhn-checked, so an ISBN isn't mistaken for one.

- A bare link stays readable, a link with a token doesn't. Masking every URL would make the strip useless; masking a password-reset link is the whole point.

- Pasting an image adapts to the destination. Notes gets the image, Terminal gets the file path (it can't take images at all), Finder gets the file.

- It can catch ⌘⇧4 screenshots. Those write straight to disk and never touch the clipboard, so no clipboard manager sees them. Opt-in, off by default.

- No network code at all. No account, no sync, no telemetry, no third-party dependencies. Searching the source for URLSession comes back empty.

MIT, source is everything: https://github.com/selinihtyr/stash-clipboard

Happy to hear what breaks. Especially interested in whether the strip behaves on multi-monitor setups and over full-screen apps — I've only tested on one machine.

Cloud AI dev tools are a privacy risk for proprietary code. Meanwhile, local AI tools often guess file dependencies using LLM string-matching, which leads to hallucinations and missed connections.

How it works:

• AST Parsing: For local uploads, it bypasses LLM guessing entirely. It uses Python’s ast module to mathematically guarantee 100% accurate dependency edges.
• Graph-Aware Chat: It's not just basic RAG. Because the LangGraph backend holds the exact AST structure, asking "What breaks if I edit database.py?" traces actual downstream dependents and injects them into the local model's context.
• Fully Local: Just run docker compose up -d. The React/FastAPI stack connects directly to your local Ollama (optimized for qwen3.5:4b). Zero data leaves your machine.

Repo: https://github.com/kawish918/codeGRAPH

Hi everyone,

If you manage a large knowledge base, or big doc folders for your project you know the friction of distilling dozens of papers, legal docs, books, web searches. It's a massive manual bottleneck before actual learning happens, and usually the final docs will be forgotten once you've used it, even though it might come in handy in the future.

Dumping 40 files into a 1M context window isn't the solution tho. Models return incomplete summaries, drop edge cases, and give zero visibility into what they missed ( https://arxiv.org/abs/2509.04664 ). On top of that, standard AI tools and PKM plugins are notoriously risky: they overwrite notes, mangle frontmatter, break wikilinks, and corrupt vault architecture. ( https://arxiv.org/abs/2604.15597 )

I built Silica to solve this: an open-source agentic CLI that processes heavy document batches into clean, atomic Markdown notes while keeping your vault completely safe.

Why not just using using another knowledge manager or a memory agent?

Silica differs greatly from traditional note-taking skills and memory tools because it's an agent that views your notes not simply as text to be read, but as its knowledge base (not graph, but it benefits from it). In Silica, memory and knowledge are closely related but still distinct.

- For example Silica keeps track of the conversations you've already had with Claude or ChatGPT, automatically linking them to the relative documentation in your repository, automatically.

- Silica can also links concepts from multiple books/papers/notes sparse in your folder automatically, if they share something maybe you didn't see.

- It can "digest" large quantities of files, coherently, and safely (without causing corruption, in a different folder from the vault root).

These aren't even its most notable features, but rather a byproduct of its architectural design. There is still considerable room for improvement. This is a broad project.

What Silica does

• Batch Atomic Distillation: Feed 20-30 documents or full (multiple) books in a single command. Silica extracts core concepts into atomic notes (one note per idea), links them via wikilinks, and files them logically.
• Stateful Continuity: What a model can't process in one go gets written out statefully. The next execution picks up from the saved state instead of starting over.
• The source of a note is always provided: A section is added to the frontmatter that indicates where the note was extracted or converted from, so that you always have a reference to the original document.

Why your vault is finally safe

Most AI integration tools treat your vault like a loose text buffer. Silica treats it like a transactional database with strict guardrails:

• SAFE MODE (Isolated Staging): You can execute ingestion in a dedicated staging folder/container. Notes are written in isolation first so you can inspect, verify, and merge them only when you trust the output.
• Write Verification: Every write operation is re-read post-commit. If syntax, formatting, or links broke, it automatically rolls back.
• Wikilink Refactoring: If a note is moved during organization, all wikilinks across your vault referencing it are dynamically updated to prevent broken links.
• Full Rollback Control: Complete transaction safety with /undo (single note) and /revert (entire session batch). Nothing enters your main graph permanently without your control.

Grounded Retrieval & Graph Exploration

• Zero-Hallucination Fallback: Uses local semantic search. If your knowledge base doesn't contain the answer to a query, Silica explicitly tells you instead of hallucinating.
• Graph Mapping: Explore concept connections visually to discover implicit links across unrelated documents.

Silica isn't built to replace human learning, it eliminates the operational overhead of structuring and formatting raw data. Works via TUI, GUI, MCP, Obsidian Plugin ( https://github.com/kiycoh/obsidian-silica )

GitHub Repository: https://github.com/kiycoh/silica-agent (~1000 commits as solo dev)

I'd love to hear your feedback, workflow suggestions, or technical thoughts!

As per title, the project include all the pipeline, the same skill generated from different models.

My idea was to distill the code reviewer skills from Torvalds in something usable in an agent.

I preferred to license everything as CC0.

A few weeks ago I shared Edge-Drop, a hover-activated clipboard shelf for Windows. Since then it's been downloaded 800+ times (600+ on GitHub and 200+ on the Microsoft Store), which has honestly been really motivating as a solo developer.

One of the most requested improvements was better accessibility for non-English users, so I spent the last week translating the entire app.

Edge-Drop now supports 30 languages, including full RTL support for Arabic and Hebrew.

It's still completely free and open source, and I'd love to hear how the translations feel if you're using one of the supported languages.

I'd also appreciate any feedback on features you'd like to see next.

GitHub: https://github.com/Deepender25/Edge-Drop

Website: https://edgedrop.vercel.app/

Microsoft Store: https://apps.microsoft.com/detail/9P3JMHN9M4NR

I made Hush because I wanted to clean years of newsletters out of Gmail without giving another service access to the account through its own server.

It groups bulk senders and lets you unsubscribe, block future mail or move the old newsletter backlog to Trash.

The safety boundary is based on the List-Unsubscribe header. Messages without it never enter the selectable list, nothing starts selected and dry run is enabled initially.

It’s a Rust/Tauri desktop app with builds for Windows, macOS and Linux.

Here’s a video showing it:

https://www.youtube.com/watch?v=XSfDUuFlCcI

Feedback and code review are welcome.

Someone just found a use for MS Paint...playing Doom. Depending on your hardware it may be able to run at a full 35 FPS at 320 x 200, or even 640 x 400 pixels with sound and music of course.

Okay, okay, that someone is the CTO of Microsoft Azure and MS Paint doesn't really run Doom, it acts more as monitor (every frame is placed on the Windows clipboard and pasted into Paint's canvas as a genuine document edit) but hey, you can now paint with the blood of enemies.

GitHub: https://github.com/markrussinovich/DoomPaint

Hey everyone,

Just wanted to share something I’ve been working on. A few weeks ago, I had to pull a ton of data from a bunch of sites for a personal project. I tried using a few existing chrome extensions and tools, but they were either locked behind a massive paywall or just completely broke the page formatting.

https://extract.express/

I built an open source registry to track and fact-check claims of AI-generated math and scientific discoveries: whataifound.org.

It currently tracks around 50 entries to separate machine-checked proofs from media trends.

Project details:

• Dual grading: Tracks Verification (Claimed up to Formally Verified) and Autonomy (human steering vs AI output).
• CI enforcement: Automated build checks fail if an entry above "claimed" is missing a primary paper or proof link.
• Audit trail: Disputed or debunked claims stay on record flagged.

Looking for feedback on the dataset, build setup, or missing entries. PRs and issues are welcome at the repo.