The best Hacker News stories from Show from the past day
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Show HN: val – An arbitrary precision calculator language
Wrote this to learn more about the `chumsky` parser combinator library, rustyline, and the `ariadne` error reporting crate.<p>Such a nice DX combo for writing new languages.<p>Still a work in progress, but I thought I'd share :)
Show HN: Particle - News, Organized
Hello HN! Particle News product engineer here.<p>Keeping up with the news is overwhelming in an age of information overload. Particle reimagines the experience by organizing articles into comprehensive "Stories," offering clear, concise summaries to quickly grasp what matters. Today, we reached the #1 spot in "Newspapers & Magazine" on the iOS App Store—and I thought I'd share a bit of our backstory.<p>I've been connected to this team for a long time. About 20 years ago, I shared a house with our CTO and co-founder Marcel Molina. I helped him get started with programming. Since then, Marcel has had an extraordinary career—becoming a senior staff engineer at Twitter, where he helped build foundational features like Retweets, Notifications, and Lists, and later working at Tesla on manufacturing execution systems that scaled across Gigafactories.<p>At Twitter, Marcel worked closely with our CEO and product visionary Sara Beykpour, who led initiatives like Twitter Blue, Twitter Video, and the experimental app <i>twttr</i>. Sara has a background in Software Engineering and Cognitive Science from the University of Waterloo and spent over a decade at Twitter in engineering and leadership roles.<p>In late 2022, Sara and Marcel started prototyping a news app that could reduce the cognitive and emotional burden of staying informed—by using AI to help people understand more, faster. They were soon joined by a few other former Twitter colleagues who helped shape the early concept into a working iOS application.<p>I joined about 15 months ago to contribute across the entire stack. Since then, I've helped design and build major iOS features, rewritten our public website on Cloudflare Workers, and implemented new functionality in our Go backend, which is driven by Google Cloud's Pub/Sub architecture.<p>What Makes Particle News Different<p>Particle helps you navigate the news effortlessly—leveraging AI to help you understand more, faster. Some highlights:<p>• Personalized News – Your feed is tailored to your interests. You can follow specific people, places, and things so you never miss what matters to you.<p>• Clear Summaries – Get a quick overview or dive deeper with detailed, structured context—summarized in natural language.<p>• Perspective Tools – Features like "Opposite Sides" and our political spectrum chart let you explore stories through multiple lenses.<p>• Interactive Q&A – Ask questions about any story and get concise answers with sources and citations.<p>• Audio Summaries – Use the "Play" feature to listen to your feed, specific stories, or even select articles—great for hands-free or on-the-go moments.<p>One of the things we're most proud of is how Particle supports publishers. We've partnered with outlets like Reuters, AFP, and Fortune to host some of their content via APIs. These partners get prominent placement, and their links are highlighted in gold to stand out. This model aims to drive traffic back to publishers and reward high-quality journalism, rather than just aggregating and commodifying it.<p>Transparency is a core value: all sources are cited, generated answers are grounded in evidence, and we take real care to prevent AI hallucinations or misleading summaries.<p>Despite negligible marketing spend, Particle has grown to the top of its category by focusing on engagement with early users and meaningful partnerships with the media ecosystem.<p>Coming soon: weekday mini crosswords—a new feature designed by another longtime friend of ours from 20 years back who went on to work at Twitter, lead development on Firewatch, and release his own games independently.<p>It's incredibly fun and rewarding to be building something meaningful with old and new friends. I feel lucky every day to work alongside some of the best product, design, and engineering minds on a project we hope will help people stay engaged with democracy without burning out.
Show HN: HN Watercooler – listen to HN threads as an audio conversation
Hi HN, here's something fun to play with.<p>It takes any HN thread and turns it into an audio conversation so you can listen to the thread while doing other things.<p>I've seen many previous attempts to turn HN threads into podcasts, but they all shared a common issue IMO: trying to reduce the very rich back-and-forth into a single-thread single-reader boring podcast. Instead, I wanted to hear the actual debate from the actual thread!<p>So I asked Claude 3.7 to build this for me as a browser-only app. It just needs a thread URL and an Elevenlabs API key (this all remains in your browser, you can check the source code, it's only 3 files, there is no server storage of anything).<p>To make the resulting audio experience as natural as possible, each commenter has a different voice.<p>Commenters who appear multiple times in the thread have the same voice, and introduce themselves. A bit of context is also introduced when coming back "up" from deeply nested comments.<p>You can play the resulting audio or download it for later listening. I'm planning to later add the ability to load multiple threads so I can have a playlist generated for listening in the gym!<p>Any comments or improvement suggestions are appreciated!
Show HN: AgentAPI – HTTP API for Claude Code, Goose, Aider, and Codex
Show HN: We Put Chromium on a Unikernel (OSS Apache 2.0)
We’ve been building infrastructure to spin up browsers for AI agents. Originally, we built[0] it as a pool of warm Docker containers running Chromium, exposing:<p>- Chrome DevTools Protocol (for Playwright/Puppeteer)<p>- noVNC (for live view)<p>We’ve been following the unikernel space for a while, so we decided to see if we could get our image on one. We went with Unikraft Cloud[1]. Here’s how it did:<p>- Boot-up time: 10–20ms (vs. ~5s for Docker containers)<p>- Near 0 CPU/memory consumption when idle<p>- Still ~8GB RAM when active (headful Chromium)<p>Potential use cases:<p>- Standby mode during long-running jobs: unikernels can sleep after X sec of inactivity, reducing clock time costs<p>- Session reuse: auth/session cookies persist for hours/days. Basically as long as the cookies are valid<p>- Cold start speed: good for low-latency, event-based handling<p>We open sourced it with Apache 2.0! Feel free to fork or submit an issue / PR. Open to feedback or suggestions. www.github.com/onkernel/kernel-images<p>==<p>[0] <a href="https://github.com/onkernel/kernel-images">https://github.com/onkernel/kernel-images</a><p>[1] <a href="https://unikraft.cloud/" rel="nofollow">https://unikraft.cloud/</a><p>[2] Thanks to the Unikraft Cloud team @fhuici @nderjung @razvandeax for helping us figure this out (we're not affiliated)<p>[3] (OPs) @rgarcia @juecd
Show HN: We Put Chromium on a Unikernel (OSS Apache 2.0)
We’ve been building infrastructure to spin up browsers for AI agents. Originally, we built[0] it as a pool of warm Docker containers running Chromium, exposing:<p>- Chrome DevTools Protocol (for Playwright/Puppeteer)<p>- noVNC (for live view)<p>We’ve been following the unikernel space for a while, so we decided to see if we could get our image on one. We went with Unikraft Cloud[1]. Here’s how it did:<p>- Boot-up time: 10–20ms (vs. ~5s for Docker containers)<p>- Near 0 CPU/memory consumption when idle<p>- Still ~8GB RAM when active (headful Chromium)<p>Potential use cases:<p>- Standby mode during long-running jobs: unikernels can sleep after X sec of inactivity, reducing clock time costs<p>- Session reuse: auth/session cookies persist for hours/days. Basically as long as the cookies are valid<p>- Cold start speed: good for low-latency, event-based handling<p>We open sourced it with Apache 2.0! Feel free to fork or submit an issue / PR. Open to feedback or suggestions. www.github.com/onkernel/kernel-images<p>==<p>[0] <a href="https://github.com/onkernel/kernel-images">https://github.com/onkernel/kernel-images</a><p>[1] <a href="https://unikraft.cloud/" rel="nofollow">https://unikraft.cloud/</a><p>[2] Thanks to the Unikraft Cloud team @fhuici @nderjung @razvandeax for helping us figure this out (we're not affiliated)<p>[3] (OPs) @rgarcia @juecd
Show HN: Plandex v2 – open source AI coding agent for large projects and tasks
Hey HN! I’m Dane, the creator of Plandex (<a href="https://github.com/plandex-ai/plandex">https://github.com/plandex-ai/plandex</a>), an open source AI coding agent focused especially on tackling large tasks in real world software projects.<p>You can watch a 2 minute demo of Plandex in action here: <a href="https://www.youtube.com/watch?v=SFSu2vNmlLk" rel="nofollow">https://www.youtube.com/watch?v=SFSu2vNmlLk</a><p>And here’s more of a tutorial style demo showing how Plandex can automatically debug a browser application: <a href="https://www.youtube.com/watch?v=g-_76U_nK0Y" rel="nofollow">https://www.youtube.com/watch?v=g-_76U_nK0Y</a>.<p>I launched Plandex v1 here on HN a little less than a year ago (<a href="https://news.ycombinator.com/item?id=39918500">https://news.ycombinator.com/item?id=39918500</a>).<p>Now I’m launching a major update, Plandex v2, which is the result of 8 months of heads down work, and is in effect a whole new project/product.<p>In short, Plandex is now a top-tier coding agent with fully autonomous capabilities. It combines models from Anthropic, OpenAI, and Google to achieve better results, more reliable agent behavior, better cost efficiency, and better performance than is possible by using only a single provider’s models.<p>I believe it is now one of the best tools available for working on large tasks in real world codebases with AI. It has an effective context window of 2M tokens, and can index projects of 20M tokens and beyond using tree-sitter project maps (30+ languages are supported). It can effectively find relevant context in massive million-line projects like SQLite, Redis, and Git.<p>A bit more on some of Plandex’s key features:<p>- Plandex has a built-in diff review sandbox that helps you get the benefits of AI without leaving behind a mess in your project. By default, all changes accumulate in the sandbox until you approve them. The sandbox is version-controlled. You can rewind it to any previous point, and you can also create branches to try out alternative approaches.<p>- It offers a ‘full auto mode’ that can complete large tasks autonomously end-to-end, including high level planning, context loading, detailed planning, implementation, command execution (for dependencies, builds, tests, etc.), and debugging.<p>- The autonomy level is highly configurable. You can move up and down the ladder of autonomy depending on the task, your comfort level, and how you weigh cost optimization vs. effort and results.<p>- Models and model settings are also very configurable. There are built-in models and model packs for different use cases. You can also add custom models and model packs, and customize model settings like temperature or top-p. All model changes are version controlled, so you can use branches to try out the same task with different models. The newly released OpenAI models and the paid Gemini 2.5 Pro model will be integrated in the default model pack soon.<p>- It can be easily self-hosted, including a ‘local mode’ for a very fast local single-user setup with Docker.<p>- Cloud hosting is also available for added convenience with a couple of subscription tiers: an ‘Integrated Models’ mode that requires no other accounts or API keys and allows you to manage billing/budgeting/spending alerts and track usage centrally, and a ‘BYO API Key’ mode that allows you to use your own OpenAI/OpenRouter accounts.<p>I’d love to get more HNers in the Plandex Discord (<a href="https://discord.gg/plandex-ai" rel="nofollow">https://discord.gg/plandex-ai</a>). Please join and say hi!<p>And of course I’d love to hear your feedback, whether positive or negative. Thanks so much!
Show HN: Plandex v2 – open source AI coding agent for large projects and tasks
Hey HN! I’m Dane, the creator of Plandex (<a href="https://github.com/plandex-ai/plandex">https://github.com/plandex-ai/plandex</a>), an open source AI coding agent focused especially on tackling large tasks in real world software projects.<p>You can watch a 2 minute demo of Plandex in action here: <a href="https://www.youtube.com/watch?v=SFSu2vNmlLk" rel="nofollow">https://www.youtube.com/watch?v=SFSu2vNmlLk</a><p>And here’s more of a tutorial style demo showing how Plandex can automatically debug a browser application: <a href="https://www.youtube.com/watch?v=g-_76U_nK0Y" rel="nofollow">https://www.youtube.com/watch?v=g-_76U_nK0Y</a>.<p>I launched Plandex v1 here on HN a little less than a year ago (<a href="https://news.ycombinator.com/item?id=39918500">https://news.ycombinator.com/item?id=39918500</a>).<p>Now I’m launching a major update, Plandex v2, which is the result of 8 months of heads down work, and is in effect a whole new project/product.<p>In short, Plandex is now a top-tier coding agent with fully autonomous capabilities. It combines models from Anthropic, OpenAI, and Google to achieve better results, more reliable agent behavior, better cost efficiency, and better performance than is possible by using only a single provider’s models.<p>I believe it is now one of the best tools available for working on large tasks in real world codebases with AI. It has an effective context window of 2M tokens, and can index projects of 20M tokens and beyond using tree-sitter project maps (30+ languages are supported). It can effectively find relevant context in massive million-line projects like SQLite, Redis, and Git.<p>A bit more on some of Plandex’s key features:<p>- Plandex has a built-in diff review sandbox that helps you get the benefits of AI without leaving behind a mess in your project. By default, all changes accumulate in the sandbox until you approve them. The sandbox is version-controlled. You can rewind it to any previous point, and you can also create branches to try out alternative approaches.<p>- It offers a ‘full auto mode’ that can complete large tasks autonomously end-to-end, including high level planning, context loading, detailed planning, implementation, command execution (for dependencies, builds, tests, etc.), and debugging.<p>- The autonomy level is highly configurable. You can move up and down the ladder of autonomy depending on the task, your comfort level, and how you weigh cost optimization vs. effort and results.<p>- Models and model settings are also very configurable. There are built-in models and model packs for different use cases. You can also add custom models and model packs, and customize model settings like temperature or top-p. All model changes are version controlled, so you can use branches to try out the same task with different models. The newly released OpenAI models and the paid Gemini 2.5 Pro model will be integrated in the default model pack soon.<p>- It can be easily self-hosted, including a ‘local mode’ for a very fast local single-user setup with Docker.<p>- Cloud hosting is also available for added convenience with a couple of subscription tiers: an ‘Integrated Models’ mode that requires no other accounts or API keys and allows you to manage billing/budgeting/spending alerts and track usage centrally, and a ‘BYO API Key’ mode that allows you to use your own OpenAI/OpenRouter accounts.<p>I’d love to get more HNers in the Plandex Discord (<a href="https://discord.gg/plandex-ai" rel="nofollow">https://discord.gg/plandex-ai</a>). Please join and say hi!<p>And of course I’d love to hear your feedback, whether positive or negative. Thanks so much!
Show HN: Portable Giant File Viewer
I’ve been dealing with huge log files lately, several GBs in size, and got frustrated with common tools such as Notepad++ freezing and crashing a server with limited RAM. I wanted something fast, relatively lightweight, and install-free for Windows. I have been searched around the web for a while but couldn't find an equivalent, so I built Giant Log Viewer.<p>Features:<p>- It is an equivalent of the Linux' `less` pager tool for Windows, but works on Linux and macOS too<p>- Opens multi-GB UTF-8 unstructured log/text files instantly (without loading everything into memory)<p>- Navigates through the file using keyboard shortcuts -- jump to the end of the file, go to previous line, etc.<p>- Limited text/regular expression searching<p>- Portable -- just unzip and run<p>- Open-source -- welcome to contribute or fork<p>Would love your feedback, and if it’s useful, feel free to star it, suggest improvements or even contribute! Depends on the needs of myself and other users, more features might be added.
Show HN: Torque – A lightweight meta-assembler for any processor
Hello everyone, I've been working on this project for the past few months.<p>Torque is a meta-assembler: instead of having an instruction set built into the assembler, you use macros to build up a small language that decribes an instruction set and then you use that to write your program. It's designed to work for any microcontroller/processor architecture, you build from the bit level upwards so there aren't any assumptions around word widths, instruction formats, or endianness.<p>I created Torque initially to write programs for a PIC microcontroller, after running into difficulties with the official assembler. I've also used it to write programs for the Z80 processor inside an old TRS-80 computer.<p>Let me know if you try it out or have any questions!
Show HN: Torque – A lightweight meta-assembler for any processor
Hello everyone, I've been working on this project for the past few months.<p>Torque is a meta-assembler: instead of having an instruction set built into the assembler, you use macros to build up a small language that decribes an instruction set and then you use that to write your program. It's designed to work for any microcontroller/processor architecture, you build from the bit level upwards so there aren't any assumptions around word widths, instruction formats, or endianness.<p>I created Torque initially to write programs for a PIC microcontroller, after running into difficulties with the official assembler. I've also used it to write programs for the Z80 processor inside an old TRS-80 computer.<p>Let me know if you try it out or have any questions!
Show HN: Torque – A lightweight meta-assembler for any processor
Hello everyone, I've been working on this project for the past few months.<p>Torque is a meta-assembler: instead of having an instruction set built into the assembler, you use macros to build up a small language that decribes an instruction set and then you use that to write your program. It's designed to work for any microcontroller/processor architecture, you build from the bit level upwards so there aren't any assumptions around word widths, instruction formats, or endianness.<p>I created Torque initially to write programs for a PIC microcontroller, after running into difficulties with the official assembler. I've also used it to write programs for the Z80 processor inside an old TRS-80 computer.<p>Let me know if you try it out or have any questions!
Show HN: Resonate – real-time high temporal resolution spectral analysis
Show HN: Resonate – real-time high temporal resolution spectral analysis
Show HN: Resonate – real-time high temporal resolution spectral analysis
Show HN: MCP-Shield – Detect security issues in MCP servers
I noticed the growing security concerns around MCP (<a href="https://news.ycombinator.com/item?id=43600192">https://news.ycombinator.com/item?id=43600192</a>) and built an open source tool that can detect several patterns of tool poisoning attacks, exfiltration channels and cross-origin manipulations.<p>MCP-Shield scans your installed servers (Cursor, Claude Desktop, etc.) and shows what each tool is trying to do at the instruction level, beyond just the API surface. It catches hidden instructions that try to read sensitive files, shadow other tools' behavior, or exfiltrate data.<p>Example of what it detects:<p>- Hidden instructions attempting to access ~/.ssh/id_rsa<p>- Cross-origin manipulations between server that can redirect WhatsApp messages<p>- Tool shadowing that overrides behavior of other MCP tools<p>- Potential exfiltration channels through optional parameters<p>I've included clear examples of detection outputs in the README and multiple example vulnerabilities in the repo so you can see the kinds of things it catches.<p>This is an early version, but I'd appreciate feedback from the community, especially around detection patterns and false positives.
Show HN: MCP-Shield – Detect security issues in MCP servers
I noticed the growing security concerns around MCP (<a href="https://news.ycombinator.com/item?id=43600192">https://news.ycombinator.com/item?id=43600192</a>) and built an open source tool that can detect several patterns of tool poisoning attacks, exfiltration channels and cross-origin manipulations.<p>MCP-Shield scans your installed servers (Cursor, Claude Desktop, etc.) and shows what each tool is trying to do at the instruction level, beyond just the API surface. It catches hidden instructions that try to read sensitive files, shadow other tools' behavior, or exfiltrate data.<p>Example of what it detects:<p>- Hidden instructions attempting to access ~/.ssh/id_rsa<p>- Cross-origin manipulations between server that can redirect WhatsApp messages<p>- Tool shadowing that overrides behavior of other MCP tools<p>- Potential exfiltration channels through optional parameters<p>I've included clear examples of detection outputs in the README and multiple example vulnerabilities in the repo so you can see the kinds of things it catches.<p>This is an early version, but I'd appreciate feedback from the community, especially around detection patterns and false positives.
Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator
Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator
Show HN: Unsure Calculator – back-of-a-napkin probabilistic calculator