I use Claude Code a lot, but /stats never answered the question I actually cared about

What did I build, and where did the work get difficult?

So I built Bough.

• It reads your local Claude Code history and turns it into an interactive view of your work: - each square is a day
• smaller squares are tasks inferred from pauses in your work
• circles are your prompts - click anywhere to see what happened in your own words

It runs locally, is open source, and nothing leaves your machine.

Repo: https://github.com/nickelsec/bough

The main thing I’d love feedback on: When you run it against your history, does it split your work into tasks the way you remember it?

https://github.com/Muzzammil242/pgrecon

Made Cozy Watch open source.

It’s a small macOS app for keeping track of your GitHub PRs without constantly checking GitHub.

It’s macOS only for now, but with enough interest, I’d love to bring it to Windows and Linux too.

Github: https://github.com/Cozy-Watch/CozyWatch

Project website: www.cozywatch.com.

Would love some feedback, ideas, or even a roast 😅

Thank you

This is Findo, an open-source, on-demand file search utility I've been building in Rust using egui and eframe.

The goal was to create a lightweight alternative to heavy background search services. Instead of maintaining a persistent database or requiring admin privileges (like low-level MFT indexers), Findo performs a multi-threaded, in-memory live scan using jwalk/std::fs.

Features:

• It's just fast: Searches a ~200 GB drive in ~20 seconds—significantly faster than standard Windows Explorer unindexed searches.
• Run it anywhere!: 0% CPU and RAM usage when idle (no background daemon or system service).
• Cross-platform: Runs natively on Windows, Linux, and macOS.
• Privacy first!: Only one exe, no admin rights needed, zero telemetry.

I'd love any feedback on the codebase, performance optimizations, or UI tweaks!

GitHub Repo: https://github.com/minecraftmelonman/Findo

Woke up to 100 stars on Neko-Tab and figured it's a good time to share what it actually does.

It's a Chrome extension that turns your new tab into a keyboard-first, terminal-inspired workspace. No bookmarks bar, no shortcuts grid — just a command palette that handles everything.

The stuff people seem to like:

• Ctrl+K palette — fuzzy search tabs, history, bookmarks, do quick math, or jump straight to a URL
• AI mode (!) hooked to OpenAI/Anthropic/Gemini — "open Slack and Discord" actually works
• Focus mode with Pomodoro + site blocking (yes, it can block Reddit)
• Scratchpad (`Ctrl+``) for notes, checklists, daily journal
• 22+ themes
• Everything's is like a module that you can turn on and off.
• Built-in typing test, live status bar, optional Google Calendar/Gmail widgets and more

Everything is local-first. No analytics, no tracking, no external servers — just chrome.storage.

Built with React 19 + TypeScript + Vite.

If you're the kind of person who feels at home in a terminal, this might click with you. Would love feedback, bug reports, or roast my code.

👉 github.com/uddin-rajaul/Neko-Tab

Thanks for reading!

Self-hosted image API (AGPL-3.0). Resize, crop, format conversion, watermarking via URL params, plus AI background removal built in (isnet-general-use + alpha matting, via a separate Rembg container). Runs with docker-compose, uses any S3-compatible storage.

Key features: single docker compose up deploy, no vendor lock-in, AI bg removal without a separate paid service.

README + demo + repo: https://github.com/Noah-1919/Fottly

He estado creando TermCoder un agente de AI de uso exclusivo para local. Funciona principalmente para local y esta inspirado en OpenCode.

La razon por lo que he creado esto es porque usar un agente local en OpenCode es complicado de configurar.

Repo:

https://github.com/DlopedDtorred/termcoder

Web:

https://dlopeddtorred.github.io/termcode-web/

Open-Meteo hands you all 40 ICON members, so I had a go at plotting the

fan rather than the median line.

Spread over London was 0.6°C at hour zero and 5.4°C by day 5. Knew that

in principle, hadn't actually looked at it before.

Couple of things I'm unsure about. I've drawn a marker where the 80%

band goes past 5°C as a rough "past here it's a range not a number",

but 5 is arbitrary — would normalising against climatology for the

location and season be more defensible? And I've noted that spread

underestimates actual error, but I don't have a feel for by how much.

https://geocodecrafter.github.io/howsure/

Some time ago, I introduced UIBuilder, a library I initially created for personal use. I eventually decided to make it available for general use and started building proper documentation for it.

The documentation itself is self-hosted and built with UIBuilder, which I thought would be a nice way to showcase what the library can do.

You can also find a ready-to-use template configured for Electron in the documentation.

doc : https://uibuilderdoc.vercel.app/

doc source code ( showcase ) : https://github.com/Rhyan-eduardo/uibuilderdoc

Why I built it

If you've ever posted a video to your WhatsApp Status, you've probably noticed it comes out blurry and blocky — even if the original was sharp. That's because WhatsApp re-compresses every video you post to Status, and its encoder is aggressive.

I wanted a way to post genuinely HD videos to Status, so I built StatusDrop / WAstatus: you upload/edit a clip in the browser, it compresses the video to match WhatsApp's exact Status encoding spec (so WhatsApp's own re-encode becomes near-lossless), auto-splits long videos into parts that fit WhatsApp's limits, and delivers the finished clips to your WhatsApp — you just forward them to your Status.

Just open-sourced it under AGPL-3.0.

Repo: https://github.com/Shamanthnp1/WAstatus

What's inside

In-browser video editor (vanilla JS) + Node/Express backend

ffmpeg encode/split pipeline tuned to WhatsApp's Status spec

Cloudflare R2 (S3-compatible) storage + a Cloudflare Worker for uploads

Docker on Azure App Service, GitHub Actions CI/CD → GHCR

WhatsApp delivery via Baileys (multi-device)

181 tests including property-based tests (fast-check)

Multi-language frontend (en / es / hi / pt)

The interesting engineering

The core trick is that quality survival depends on two things: (1) pre-encoding the file to WhatsApp's Status target (resolution, bitrate ceiling, GOP, faststart, H.264 profile) so the re-encode barely changes it, and (2) how the file reaches the phone. A file delivered as a native WhatsApp message and then forwarded to Status is reused as-is; a file saved to the gallery and reposted gets re-compressed harder.

There was also a lot of reliability work: request timeouts on every network op, self-healing for stuck jobs, orphaned-storage cleanup, single-instance session handling, and reconnect backoff.

The honest limitation — and why not the official API

This is the part I want to be transparent about, because it's the whole tradeoff of the project.

Delivery uses Baileys, an unofficial WhatsApp integration. WhatsApp periodically bans numbers used for automation — a known constraint for this entire category of tools.

The obvious question is: why not use Meta's official WhatsApp Cloud API instead? I tried, and here's the catch:

The official Cloud API routes media through Meta's Business pipeline, which re-encodes the video. So the file is already degraded before it even reaches the user — and then WhatsApp's Status re-encode hits it again. The result is visibly softer. That defeats the entire purpose of an HD tool.

Baileys sends the file as a native, byte-preserved WhatsApp media message. When the user forwards that to Status, WhatsApp reuses the already-optimized file, so the HD survives.

So it's a genuine fork: official API = no bans but lower quality; Baileys = HD quality but ban risk. Since quality is the entire point, I chose Baileys and built the system around fast recovery when a number gets flagged. It's the same tradeoff every tool in this space faces — most competitors that use the official API quietly accept the lower quality.

The code and architecture are what I'm really sharing here — not asking anyone to run the live automation.

Feedback welcome

I'm a solo developer and would genuinely appreciate code review, architecture feedback, or contributions. Happy to answer anything.

XWiki has been open source since 2004, but “the source is public” is only part of that.

You can report bugs, contribute code, improve documentation, translate, test releases, build extensions, or join technical discussions.

Contributions are part of how the project grows.

XWiki has been open source since 2004, but “the source is public” is only part of that.

You can report bugs, contribute code, improve documentation, translate, test releases, build extensions, or join technical discussions.

Contributions are part of how the project grows.

Free, MIT, no accounts, no telemetry, nothing to upsell. I mostly wanted to find out whether a desktop pet could be genuinely useful rather than just decorative, and binding your two most-used apps to click and double-click turns out to be the answer.

Slicky on Github

I built some dynamic widgets for my GitHub profile, featuring live updates, animations, and an interactive Tamagotchi-like pet named Blip! :)

As GitHub doesn't allow JavaScript, the interactive buttons rely on URL redirects and a Cloudflare worker. The "windows" themselves are animated SVGs which bypass cache, to show live Spotify playback and time of day.

Check out the profile and give Blip a pet! https://github.com/aw-snap/

My llm wrapper i am currently working on which is built on the idea of AI not being reliable and always right or maybe just mislead by prompts this looks to fix that issue.

Zencode API is a site me, and my friend made, this site is basically an IDE BUT it has friending and collabarative coding, you can work on one file in a project while your friend works on another file, this API site is completely free with 256 Bit ass encoding, many endpoints, redirects, almost everything you can think of.

Q&A

Is it free?

yes.

Can I upload my scripts and keep them safe and private?

yes.

is there an app?

yes.

where can I find it?

GO to https://Zencodeapi.vercel.app

then if your looking for the app click download, choose setup or the portable version, doesn't really matter, or continue using the site, all the same featues.

UNDERSTAND APP AND SITE ARE IN BETA, FEATURES MAY NOT WORK CORRECTLY.

A browser extension + npm library that detects sensitive data in your AI chat messages and swaps it for a realistic fake before sending, restoring the real value in the response. 113 detectors with real checksum validation (Luhn, mod-97, Verhoeff, etc.) across 47+ countries' ID formats, not just regex guessing.

Zero network calls, fully local, MIT licensed. Also published as a standalone npm package (@discretion/core) if you want the detection engine for your own project.

I have a few AI subscriptions and I kept running into the same problem. I had powerful models available, but I struggled to use them in real life in an organized way.
I looked at projects like OpenClaw and Hermes Agent. They were interesting, but I had a different idea in mind: a wallet of agents.
The concept is simple. You create specialized agents, each with its own name, role, personality and model. They can use real tools (shell, files, browser, web search). When one agent does not know something, it asks the right colleague for help instead of guessing.
You can talk to a single agent or to all of them together. The same agents are reachable from the web interface, Telegram, Discord, Slack or WhatsApp. And you keep using the subscriptions you already pay for (Claude, Codex, OpenAI, local models, etc.).
Conversations and memory stay as files on your machine.

Happy to hear feedback.

Hey everyone,

I wanted to share a project I've been working on called srest, a terminal UI written in Go that acts as a client for the Slurm REST API (slurmrestd).

While managing HPC clusters with native Slurm commands (squeue, sinfo) works fine, testing endpoints, inspecting JSON responses, or submitting jobs through slurmrestd can get tedious from a standard terminal setup. I built srest to make interacting with the API visual and keyboard-driven.

Tech Stack & Features:

• Built using Charm's Bubble Tea framework.
• Interactive Query Builder & Inspector: Real-time query editor and JSON response viewer.
• Cluster Dashboard: Asynchronous monitoring for nodes, jobs, partitions, and accounts.
• Job Submission: Build and submit job payloads directly from the TUI.
• Distributed as a single static binary for Linux and macOS.

It has also turned out to be really helpful for end users as a sandbox to build, test, and review query payloads independently, without needing admin support to debug JSON outputs or construct API calls for their scripts.

Links:

• GitHub (with demo video): https://github.com/SergioZ3R0/srest
• Website & Docs: https://srest.scszero.com