🛠️ All DevTools

[Other] Zerostack – A Unix-inspired coding agent written in pure Rust

[Other] Open-source alternative to AI video platforms — Free AI image & video generation studio with 200+ models (Flux, Midjourney, Kling, Sora, Veo). No content filters. Self-hosted, MIT licensed.

[Other] Show HN: Strava for AI coding – analytics on your Copilot/Claude/Codex usage

[Other] Pre-indexed code knowledge graph for Claude Code — fewer tokens, fewer tool calls, 100% local

[Other] Δ-Mem: Efficient Online Memory for Large Language Models

[Other] 'No way to prevent this,' says only package manager where this regularly happens

[CLI Tool] Show HN: Epiq – Distributed Git based issue tracker TUI Issue trackers typically live outside of your workflow, with poor ergonomics. Epiq aims to solve that, bringing issue tracking into your terminal. Multi-user collaboration is achieved via git using user-scoped immutable event logs that converge in memory. Put my all into it. Let me know what you think.

[Other] Orthrus-Qwen3: up to 7.8×tokens/forward on Qwen3, identical output distribution

[CLI Tool] Show HN: MIT OSS LinkedIn DMs for Agents (CLI and Example TUI) I was tired of paying $100s&#x2F;mo to access data I should own -- my own DMs on social media -- so I built Allman, a local-first cli to access linkedin messenger.<p>Starting with LinkedIn, I gave the entire compiled js binary of linkedin&#x27;s web app to claudecode and reversed engineered the entire messenger inbox in 24 hours. My goal is to bring this to all messengers so AI can handle all of this busywork, just like it can my email.<p>I had also never built a TUI so I had claudecode build me one based on top of the local CLI and filesystem.<p>Full repos:<p><a href="https:&#x2F;&#x2F;github.com&#x2F;tarkaai&#x2F;allman-cli" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;tarkaai&#x2F;allman-cli</a><p><a href="https:&#x2F;&#x2F;github.com&#x2F;tarkaai&#x2F;allman-tui" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;tarkaai&#x2F;allman-tui</a><p>Their sharding &#x2F; access is brutal, so it&#x27;ll likely break as-is -- but the point is that Reverse Engineering is trivial now (and can do it dynamically through browser access and dynamic playwright -- thanks Browserbase! ).<p>Would love to hear your feedback and what I should build on it next.<p>Shoutout to Eric Allman.

[Other] Building a UMatrix Replacement

[Other] Git Is Not Fine

[Other] Feedr v0.8.0 – a TUI RSS reader, now read the full article from your terminal

[Other] I designed a nibble-oriented CPU in Verilog to build a scientific calculator

[Package Manager] Show HN: Sx – an open-source package manager for AI skills, MCPs, and commands

[Other] Bun Rust rewrite: "codebase fails basic miri checks, allows for UB in safe rust"

[CLI Tool] Show HN: Termini – Open-Source Menu Bar Terminal for macOS

[Other] A 0-click exploit chain for the Pixel 10

[IDE/Editor] Show HN: Ane, a new chord-based terminal code editor with one-shot CLI edits I’ve had this idea for a new code editor chord grammar bouncing around in my head for over 2 years, and now I can finally release v0.1 of ane. You can run it one-shot from scripts or agents (`ane exec —chord…`) or use its full-on TUI editor. ane is pure Rust, and integrates tree-sitter and LSP to provide a pleasant and predictable terminal code editing experience. I’d love folks to try it out and give feedback! Thanks :)

[Other] Radicle: Sovereign {code forge} built on Git

[DevOps] Show HN: GlycemicGPT – Open-source AI-powered diabetes management I&#x27;m a Type 1 diabetic and software engineer. Last year I went months between endocrinologists with no clinician reviewing my data. I&#x27;m an engineer, so I built the tool I needed — and now I&#x27;m open sourcing it. GlycemicGPT is a self-hosted platform that connects continuous glucose monitors, insulin pumps, and existing Nightscout instances to an AI analysis layer running on your own infrastructure. Data sources:<p>Dexcom G7 (cloud API) Tandem t:slim X2 and Mobi pumps (direct BLE) Nightscout (point it at your existing instance and you&#x27;re running in minutes)<p>What the AI layer does:<p>Daily briefs summarizing overnight and 24-hour patterns Meal response analysis Conversational chat with RAG-backed clinical knowledge Predictive alerting with configurable thresholds and caregiver escalation<p>Important: this is monitoring and analysis only. GlycemicGPT does not deliver insulin, does not control your pump, and is not a closed-loop system. It reads your data and gives you insight on top of it. Your clinical decisions stay between you and your care team. Architecture:<p>Self-hosted via Docker or K8S — the GlycemicGPT stack runs entirely on your hardware BYOAI — bring your own AI provider. Use Ollama for fully local operation (no data leaves your hardware), or point it at Claude, OpenAI, or any OpenAI-compatible endpoint if you prefer a hosted model. Data flows directly from your instance to the provider you choose; nothing is routed through any centralized service operated by the project. GPL-3.0, no subscriptions, no vendor lock-in<p>Stack:<p>Backend API: FastAPI, Python 3.12, PostgreSQL 16, Redis 7 Web Dashboard: Next.js 15, React 19, Tailwind CSS, shadcn&#x2F;ui AI Sidecar: TypeScript, Express, multi-provider proxy Android App: Kotlin, Jetpack Compose, BLE Wear OS: Kotlin, Wear Compose, Watch Face Push API Plugin SDK: Kotlin interfaces, capability-based, sandboxed<p>Looking for contributors — especially folks with BLE&#x2F;Android experience or anyone in the diabetes tech space. Plugin SDK is documented if you want to add support for new devices. GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;GlycemicGPT&#x2F;GlycemicGPT" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;GlycemicGPT&#x2F;GlycemicGPT</a>