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[Other] Show HN: I'm building a browser for reverse engineers

[Other] Show HN: I built an open-source AI data layer that connects any LLM to any data Excited to share a project I’ve been building for months! Would love to receive honest feedback :)<p>My motivation: AI is clearly going to be the interface for data. But earlier attempts (text-to-SQL, etc.) fell short — they treated it like magic. The space has matured: teams now realize that AI + data needs structure, context, and rules. So I built a product to help teams deliver “chat with data” solutions fast with full control and observability (agent tracing, quality scores, etc) — am I wrong?<p>The product allows you to connect any LLM to any data source with centralized context (instructions, dbt, code, AGENTS.md, Tableau) and governance. Users can chat with their data to build charts, dashboards, and scheduled reports — all via an agentic, observable loop. With slack integration as well!<p>* Centralize context management: instructions + external sources (dbt, Tableau, code, AGENTS.md), and self-learning<p>* Agentic workflows (ReAct loops): reasoning, tool use, reflection<p>* Generate visuals, dashboards, scheduled reports via chat&#x2F;commands<p>* Quality, accuracy, and performance scoring (llm judges) to ensure reliability<p>* Advanced access &amp; governance: RBAC, SSO&#x2F;OIDC, audit logs, rule enforcement<p>* Deploy in your environment (Docker, Kubernetes, VPC) — full control over infrastructure<p>GitHub: github.com&#x2F;bagofwords1&#x2F;bagofwords<p>Docs &#x2F; architecture &#x2F; quickstart: docs.bagofwords.com

[Monitoring/Observability] GPU Hot: Dashboard for monitoring NVIDIA GPUs on remote servers

[Other] Show HN: Turn your OpenAPI spec into negative tests

[Other] Show HN: I've build a platform for writing technical/scientific documents

[Other] Build a VPN Tunnel with Wintun on Windows – Part 1

[Other] Django: One ORM to rule all databases

[Testing] QA-use-MCP: MCP for E2E testing

[DevOps] Show HN: Envirobly – Efficient App Hosting This is my, fully bootstrapped, take on an application hosting platform. I designed it primarily for myself, to meet the following goals:<p>* Utilize the best parts of the cloud, leave expensive value added services behind. * Host anywhere in the world, close to your users. * Batteries included: backups, logging, monitoring, auto-scaling, containerization, databases. * Simple and user friendly.<p>The journey was tough. It took me round about 3 years to get everything just right. This goes against the conventional wisdom of getting something simple out quick. With a hosting platform however, in my mind, reliability, stability and certain maturity are a must have from the start.<p>I definitely need to work on the presentation, it&#x27;s barely covering the basics. But you have to start somewhere :-)<p>I&#x27;d love to hear some critique from the community. Thanks!

[Other] Flightcontrol: A PaaS that deploys to your AWS account

[CLI Tool] Show HN: A Node.js CLI tool to generate ai.txt, llms.txt, robots.txt, humans.txt

[DevOps] Show HN: Volant– spin up real microVMs in 10 seconds(Docker images or initramfs) I’ve been building Volant, a modular microVM orchestration engine that makes running microVMs feel as simple as Docker.<p>It supports cloud-init, GPU&#x2F;VFIO passthrough (yes, you can run AI&#x2F;ML workloads in isolated microVMs), booting Docker images via a plugin system, and Kubernetes-style deployments with replication, all from a single CLI(soon to be web UI, see next)<p>Coming soon: a built-in PaaS mode with snapshot-based cold start elimination, sort of like Dokploy, but designed for serverless workloads that boot from memory snapshots instead of containers.<p>Volant is intentionally a bit opinionated to make microVMs more accessible, but it’s fully extensible for power users.<p>Check out the README and the docs for more details.<p>It’s free and open source (under BSL), would love to hear feedback or thoughts from anyone!<p>tl;dr: 6-second GIF in the README shows the full flow: install → create VM → get HTTP 200.

[CLI Tool] Show HN: DidMySettingsChange – A tool that checks changed windows settings Microsoft has been under heavy scrutiny with how they manage Windows over the years, particularly concerning privacy and telemetry settings. Many users find that after disabling certain settings, these settings are mysteriously re-enabled after updates or without any apparent reason. DidMySettingsChange is a Python script designed to help users keep track of their Windows privacy and telemetry settings, ensuring that they stay in control of their privacy without the hassle of manually checking each setting. Features<p><pre><code> Comprehensive Checks: Automatically scans all known Windows privacy and telemetry settings. Change Detection: Alerts users if any settings have been changed from their preferred state. Customizable Configuration: Allows users to specify which settings to monitor. Easy to Use: Simple command-line interface that provides clear and concise output. Logs and Reports: Generates detailed logs and reports for auditing and troubleshooting.</code></pre>

[CLI Tool] Show HN: ut – Rust based CLI utilities for devs and IT Hey HN,<p>I find myself reaching for tools like it-tools.tech or other random sites every now and then during development or debugging. So, I built a toolkit with a sane and simple CLI interface for most of those tools.<p>For the curious and lazy, at the moment, ut has tools for,<p>- Encoding: base64 (encode, decode), url (encode, decode)<p>- Hashing: md5, sha1, sha224, sha256, sha384, sha512<p>- Data Generation: uuid (v1, v3, v4, v5), token, lorem, random<p>- Text Processing: case (lower, upper, camel, title, constant, header, sentence, snake), pretty-print, diff<p>- Development Tools: calc, json (builder), regex, datetime<p>- Web &amp; Network: http (status), serve, qr<p>- Color &amp; Design: color (convert)<p>- Reference: unicode<p>For full disclosure, parts of the toolkit were built with Claude Code (I wanted to use this as an opportunity to play with it more). Feel free to open feature requests and&#x2F;or contribute.

[Other] Show HN: A Vectorless LLM-Native Document Index Method The word &quot;index&quot; originally came from how humans retrieve info: book indexes and tables of contents that guide us to the right place in documents.<p>Computers later borrowed the term for data structures: e.g., B-trees, hash tables, and more recently, vector indexes. They are highly efficient for machines; but abstract and unnatural: not something a human, or an LLM, can understand and directly use as a reasoning aid. This creates a gap between how indexes work for computers and how they should work for models that reason like humans.<p>PageIndex is a new step that &quot;looks back to move forward&quot;. It revives the original, human-oriented idea of an index and adapts it for LLMs. Now the index itself (PageIndex) lives inside the LLM&#x27;s context window: the model sees a hierarchical table-of-contents tree and reasons its way down to the right span, much like a person would retrieve information using a book&#x27;s index.<p>PageIndex MCP shows how this works in practice: it runs as a MCP server, exposing a document&#x27;s structure directly to LLMs&#x2F;Agents. This means platforms like Claude, Cursor, or any MCP-enabled agent or LLM can navigate the index themselves and reason their way through documents, not with vectors&#x2F;chunking, but in a human-like, reasoning-based way.

[Code Quality] Show HN: Pyscn – Python code quality analyzer for vibe coders Hi HN! I built pyscn for Python developers in the vibe coding era. If you&#x27;re using Cursor, Claude, or ChatGPT to ship Python code fast, you know the feeling: features work, tests pass, but the codebase feels... messy.<p>Common vibe coding artifacts:<p>• Code duplication (from copy-pasted snippets)<p>• Dead code from quick iterations<p>• Over-engineered solutions for simple problems<p>• Inconsistent patterns across modules<p>pyscn performs structural analysis:<p>• APTED tree edit distance + LSH<p>• Control-Flow Graph (CFG) analysis<p>• Coupling Between Objects (CBO)<p>• Cyclomatic Complexity<p>Try it without installation:<p><pre><code> uvx pyscn analyze . # Using uv (fastest) pipx run pyscn analyze . # Using pipx (Or install: pip install pyscn) </code></pre> Built with Go + tree-sitter. Happy to dive into the implementation details!

[Other] Adding Stride Scheduling to Xv6

[CLI Tool] Show HN: Run – a CLI universal code runner I built while learning Rust Hi HN — I’m learning Rust and decided to build a universal CLI for running code in many languages. The tool, Run, aims to be a single, minimal dependency utility for: running one-off snippets (from CLI flags), running files, reading and executing piped stdin, and providing language-specific REPLs that you can switch between interactively. I designed it to support both interpreted languages (Python, JS, Ruby, etc.) and compiled languages (Rust, Go, C&#x2F;C++). It detects languages from flags or file extensions, can compile temporary files for compiled languages, and exposes a unified REPL experience with commands like :help, :lang, and :quit. Install: cargo install run-kit (or use the platform downloads on GitHub). Source &amp; releases: <a href="https:&#x2F;&#x2F;github.com&#x2F;Esubaalew&#x2F;run" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;Esubaalew&#x2F;run</a> I used Rust while following the official learning resources and used AI to speed up development, so I expect there are bugs and rough edges. I’d love feedback on: usability and UX of the REPL, edge cases for piping input to language runtimes, security considerations (sandboxing&#x2F;resource limits), packaging and cross-platform distribution. Thanks — I’ll try to answer questions and share design notes.

[Other] A comparison of Ada and Rust, using solutions to the Advent of Code

[Other] Microformats – building blocks for data-rich web pages