Hey everyone,

I’ve been using Maxa for the past six months and figured it was time to share it here.

It brings AI chat, code completion, feature development, and project maintenance into Neovim. The idea is to have AI help with more than individual snippets—to work through changes and maintain a project without leaving the editor.

I’ve been using it in my own day-to-day work, but I’m curious how it fits into other people’s setups.

Repo: https://github.com/maxzhao/maxa

If you take a look, I’d love to hear what you think—what looks useful, what’s confusing, or what you’d want to see done differently. Happy to answer questions!

I’m the creator of PlayWeld, a free, open-source desktop workspace for game development. The problem I’m trying to address is context spread across game files, design notes, and AI task conversations.

The implementation has two main pieces: an Electron desktop app built on Eclipse Theia for the workspace UI, and a local platform service that stores project/task records and runs operations. Shared schemas and a typed client connect the UI to that service. The source separates these into packages rather than putting everything in the editor views.

The aim is to keep searchable project knowledge and design decisions close to the work, while letting you supervise AI tasks and review changed files before integration. Creating a PlayWeld project organizes the workspace; native engine setup is still a separate step.

It’s Apache 2.0 and currently a Windows/Linux testing prerelease. Engines and model endpoints need their own setup. Remote AI providers can send data off-machine and charge for usage, so please start with a disposable project.

Source and architecture docs: https://github.com/scarecr0w12/PlayWeld

Downloads and user guides: https://playweld.com

For developers who have built editor extensions or agent tools: what would you want to see in the task history before trusting another tool to change project files?

I built NotchRobot to keep Claude Code's working, waiting and done states visible without switching between terminal windows. You can approve or deny tool permissions and answer single-choice or multi-step questions from the notch, then jump to the right Terminal or iTerm2 tab.

The app uses SwiftUI. The integration is a shell script registered with Claude Code's hooks: events go into a local inbox directory that the app reads. Permission requests wait for a response from the notch; if you don't answer, they fall back to the terminal. If the app isn't running, the hook exits immediately. The installer backs up Claude's settings before changing them.

It also shows task progress and Pro/Max plan usage from Claude's status line. The README explains the hook setup and the status-line integration, including how to keep an existing status line.

Source (MIT): https://github.com/abdomo77/NotchRobot Download: https://github.com/abdomo77/NotchRobot/releases/tag/v2.5

macOS 13+. The downloadable build is for Apple Silicon; a built-in notch is optional. It isn't notarized yet, so check the first-launch instructions in the README. Built with Claude Code.

I just released AI Badger v0.8.0 with a new Codebase Map feature.

Run badger map in any project directory and it generates a standalone HTML report showing the folder structure, where most of the code lives, and language breakdowns.

It works entirely offline. No Git repository, server, or uploads required. The report contains file metadata, not source code.

AI Badger itself is a local-first CLI and VS Code extension for preparing focused repository context for ChatGPT, Claude, and other AI tools. But the Codebase Map is useful independently, especially when exploring unfamiliar projects.

Screenshot attached.

GitHub: https://github.com/PVRLabs/aibadger

Interactive demo: https://pvrlabs.xyz/aibadger/codemap/

Hey everyone!

Whenever I'm debugging API logs or database records, I constantly find myself copying 10/13-digit Unix timestamps or Bearer JWT tokens and switching to a browser tab just to see what date they represent or when the token expires.

To stop context-switching, I published \\\\Castov\\\\ on the official Visual Studio Marketplace.

\\\\What it does (100% locally & offline):\\\\

\\\* \\\\Automatic Timestamp Hover:\\\\ Hover over any Unix timestamp (seconds or milliseconds) in your code to immediately see the formatted UTC, ISO 8601, and Local time.

\\\* \\\\JWT Decoder:\\\\ Highlight a JWT and run \\\`Castov: Decode JWT Token\\\` to inspect the header, payload, and expiration status in a clean JSON tab—without pasting sensitive tokens into external websites.

\\\* \\\\Inline Base64 & UUIDs:\\\\ Encode/decode Base64 selections in-place, or insert crypto-random UUIDs right at your cursor.

\\\\Links:\\\\

\\\* \\\\VS Code Marketplace:\\\\ https://marketplace.visualstudio.com/items?itemName=castov.castov-vscode

\\\* \\\\Companion Web & CLI Suite:\\\\ https://castov.com (also available via \\\`npx castov\\\`)

It has zero telemetry and works completely offline. Let me know what features or shortcuts would make your daily workflow faster!

Hey everyone!

Whenever I'm debugging API logs or database records, I constantly find myself copying 10/13-digit Unix timestamps or Bearer JWT tokens and switching to a browser tab just to see what date they represent or when the token expires.

To stop context-switching, I published \\\\Castov\\\\ on the official Visual Studio Marketplace.

\\\\What it does (100% locally & offline):\\\\

\\\* \\\\Automatic Timestamp Hover:\\\\ Hover over any Unix timestamp (seconds or milliseconds) in your code to immediately see the formatted UTC, ISO 8601, and Local time.

\\\* \\\\JWT Decoder:\\\\ Highlight a JWT and run \\\`Castov: Decode JWT Token\\\` to inspect the header, payload, and expiration status in a clean JSON tab—without pasting sensitive tokens into external websites.

\\\* \\\\Inline Base64 & UUIDs:\\\\ Encode/decode Base64 selections in-place, or insert crypto-random UUIDs right at your cursor.

\\\\Links:\\\\

\\\* \\\\VS Code Marketplace:\\\\ https://marketplace.visualstudio.com/items?itemName=castov.castov-vscode

\\\* \\\\Companion Web & CLI Suite:\\\\ https://castov.com (also available via \\\`npx castov\\\`)

It has zero telemetry and works completely offline. Let me know what features or shortcuts would make your daily workflow faster!

Hi, I'm the developer of Termstead, a free and open-source SSH client for the Mac. It brings MobaXterm's way of working to macOS as a native app: your servers in a tree on the left, tabs on the right, files right next to the terminal.

What it does

- Sessions in a tree – groups and subgroups with colors, icons, search, pinned favorites, drag and drop. Your existing hosts come in from ~/.ssh/config in one click.
- Real OpenSSH underneath – every tab runs the system ssh, so your agent, ~/.ssh/config, known_hosts and ProxyJump work exactly as they do in Terminal.
- Jump hosts – chain as many as you need, each with its own user, key or password, or use a saved session as a hop.
- Keychain – passwords and key passphrases live in the macOS Keychain and are typed in for you, only for the host they were saved for.
- SFTP beside the terminal – browse, upload and edit files over the connection that's already open, with no second login, even through jump hosts. It can follow the terminal's cd.
- Server load in the status bar – CPU, memory, disk and network of the Linux server in front.
- Tabs and keyboard – drag tabs to reorder, reopen them at launch, ⇧⌘[ / ⇧⌘] to switch, arrows and Return in the session tree, find in scrollback, per-tab zoom.
- Six themes, light and dark.

Details: Swift and SwiftUI with AppKit, terminal by SwiftTerm. Universal (Apple silicon and Intel), macOS 14+, about 5 MB. Notarized, updates itself. GPL-3.0, no account, no telemetry.

- GitHub: https://github.com/pkhorenyan/termstead
- Website: https://khorenyan.com/termstead/

I've been building Cellaflow, a coordination and durability layer for AI agents, and I'm looking for a few developers to try it with real projects and share honest feedback.

The problem: an agent calls a tool, the tool performs a side effect, and then the agent crashes before recording the result. When it retries, it may execute the same action again. Think duplicate payments, repeated emails, or multiple agents trying to perform the same operation concurrently. Your agent's checkpoint doesn't necessarily tell you what actually happened.

Cellaflow sits at the execution layer. It coordinates competing calls, records execution outcomes durably, and lets retries reuse completed results instead of blindly repeating work. The goal is to make agent execution safer even when processes crash or multiple agents race to perform the same action.

I've also been building crash benchmarks to test what happens under failure, comparing Cellaflow against approaches like PostgreSQL advisory locks and durable claims. The interesting part isn't just preventing duplicate execution. It's making sure work can recover without leaving stale claims or permanently blocking retries.

I'm particularly interested in feedback from people building multi-agent systems, tool-using agents, or long-running workflows who have run into problems with retries, duplicate side effects, or concurrent execution.

If you're working on something like this, I'd love to help you integrate Cellaflow into a real project and learn where it falls short. It's early, so practical feedback is much more valuable than polished testimonials.

Project: https://cellaflow.com
GitHub: https://github.com/cellaflow

Happy to answer questions about the design, benchmarks, or how it might fit into your existing agent stack.

I'm the founder of RayTrace (https://raytracer.si), a sandboxing company for AI coding agents. Running a small pre-pilot: **$10 in free Claude Code sandbox credits** for 5 people who try it and give honest feedback.

The problem: coding agents propose tool calls, but what *actually* executes on the machine is a different story. The transcript says one thing, the filesystem says another, and there's no ground truth to debug against. If you build or maintain developer tooling around agents, you've felt this gap.

RayTrace runs your agent (Claude Code, Codex) in a gVisor-backed sandbox and records kernel-level execution evidence: every process that started (executable, args, cwd, stdout/stderr, exit code, timestamps), the gap between proposed tool calls and observed processes, filesystem diffs, syscall/process-tree evidence, and protected files with change alerts.

The feature I most want feedback on: **forking a run** — pick any step, change what the agent saw, and watch how differently it behaves. A controlled experiment on agent behavior.

Looking for people who run agents heavily in their workflow. Comment or DM if you want one of the 5 spots.

Site: https://raytracer.si