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Decker, a platform that builds on the legacy of Hypercard and classic macOS

Scientists link oral bacteria to heart disease and cognitive decline

Make an Origami Circuit Board

Show HN: A browser-based video editor that renders videos directly with FFmpeg Weave is a React app that provides a multi-track timeline editor to perform basic video edits like trimming, stitching, transitions, audio tracks etc. which maps directly to an FFmpeg command to render the video.<p>I tried my best to have the React &quot;video&quot; preview closely replicate the FFmpeg lavfi filtergraph output, but naturally this is not perfect (especially replicating the `eq` filter using SVG filters is quite inaccurate).<p>I&#x27;ve built this as a prototype for another project I&#x27;m working on, so I don&#x27;t plan to actively maintain it, but I thought it&#x27;d be cool to share it.<p>Try it live: <a href="https:&#x2F;&#x2F;weave.salviano.xyz&#x2F;" rel="nofollow">https:&#x2F;&#x2F;weave.salviano.xyz&#x2F;</a>

Show HN: Managing on-premise servers without Kubernetes

Go Analysis Framework: modular static analysis by go team

Show HN: QueryTuner – SQL diagnostics across 5 DBs, no database connection

Amnezia VPN Client (Desktop+Mobile)

Jenkins automation server

No Stack Overflow, No Autocomplete: What Coding Felt Like in the 80s

Show HN: Reproducibility Benchmark a Risk Quantitative Model

Agentic test processes, LLM benchmarks, and other notes on agentic coding

Show HN: I mapped every US golf course – 16k+ courses, free, no signup I got tired of Googling basic course info, so I made a free directory of every US course<p>Google filters for golf course results are terrible so I built a better way to browse courses using OSM as the backbone.... <a href="https:&#x2F;&#x2F;golfcoursebrowser.com&#x2F;" rel="nofollow">https:&#x2F;&#x2F;golfcoursebrowser.com&#x2F;</a><p>It&#x27;s a work in progress and mostly US for now, but I want to expand to the rest of North America, the EU, and the rest of the world ASAP.<p>It&#x27;s free, no ads, no login, no bs. If you spot anything wrong (bad info, a missing course, wrong scorecard), you can flag it right on the course page. I actually read those and fix them.<p>Still a lot of missing info, but I&#x27;m filling out more and more each day. The goal is the most complete, and current golf course directory in the world, verified and maintained by actual golfers. I think is attainable in the next few months. The base layer is OpenStreetMap, cross-checked against course websites and enriched with scorecards, USGA rating&#x2F;slope, and public&#x2F;private status. User corrections from golfers who know their home course have beaten every commercial data source we check against.

Show HN: What 180k words look like as a temporal knowledge graph (Oz series) The graph is free to explore and requires no registration.<p>SynapTale builds a model of a story as a temporal graph made up of nodes (entities) and edges (their actions and relationships). The graph is not a visualization of the wiki. The wiki, timelines, relationship histories, and analytics are projections of the graph.<p>The current demo contains 232 entities, 1,852 edges, and a snapshot of the story’s state at every chapter. By chapter 100, it still remembers a promise made in chapter 8 and turns the story into a set of source-verifiable facts.<p>The most interesting things can be found in the graph itself and in the Analytics tab. A few things I found:<p>1. The character with the highest kill count is the Tin Woodman—the same character who cries over a beetle he accidentally crushed. Dorothy comes second, with three killing events. 2. Dorothy never deceives anyone during the first 100 chapters of the series. 3. The Scarecrow’s debt to the stork has remained active for 92 chapters, starting in chapter 8. 4. The Cowardly Lion ranks third by number of threats. 5. The first 100 chapters contain 60 secrets and 254 dialogue events.<p>Technical details<p>1. Five different multi-agent pipelines combining LLMs and NLP: a prescan, ontology construction, chapter-by-chapter graph extraction, retrospective validation over spans of dozens of chapters, and a linguistic prescan for speech profiles and linguistic edges.<p>2. A living story needs a living graph. It has to account for time, because entities and the relationships between them evolve. A simple is_active field is not enough.<p>I ended up with three types of edges:<p>event: an instantaneous action; identity: a fact; state: a persistent action whose termination requires justification and a supporting quote from the text.<p>The vast majority of edges are events and end in the same chapter in which they began. This allows the system to scale well, since only a minority of state and identity edges remain continuously active.<p>3. Ontology. You cannot simply ask an LLM to extract entities and relationships into a graph. With every chapter, even the smartest model will keep inventing unimportant fields, creating new aliases for existing fields, and representing the same fields inconsistently.<p>Before extracting the graph, the system therefore performs an ontology scan across the entire story. It captures story-specific entity and edge types, along with their fields and descriptions.<p>4. Epistemics. Events are only one part of a story. It is also important to understand how information is distributed, which is difficult to represent using event edges alone.<p>I addressed this by introducing a new node type: epistemic nodes, which capture different entities’ perspectives on the same fact. Subtle hints can still be missed, the system is not yet perfect in this area.

Alien World Chemistry Found Inside Meteorite That Struck New Jersey Home

Possible invasive species superspreader event near Strait of Hormuz

Git rebase -I is not that scary

Clinical Failure Rates over the Decades: Yikes

Show HN: Hubo – two agents that implement and review code until they agree

Show HN: Rudoc – a 4.5MB Rust document converter I built Rudoc because I wanted a smaller tool for simple file convertion workflow. (Pandoc was so heavy for me) I once wanted to try Pandoc, but after I downloaded it from GitHub, I found that it is around 70 MB. It also needed a lot of dependencies.<p>Rudoc is not a substitue of Pandoc, it supports limited set of formats (only txt, md, html, typ, docx, pdf, pptx, xml, json) and doesn&#x27;t support advanced formatting. The most common workflow is just turn a markdown file to a html. PDF generation can work without Typst, but PDF input conversion requires Typst as a backend. It has no other runtime dependencies and can run as a single binary, by the way.<p>It is pretty easy to use, just use the format of rudoc input.file output.file One sample usage is like this: ```powershell rudoc OhPDF_ROADMAP.md.txt r.md [rudoc] OhPDF_ROADMAP.md.txt → r.md (txt→md) [rudoc] done in 52ms (6286 bytes) rudoc r.md r.html [rudoc] r.md → r.html (md→html) [rudoc] done in 4ms (7363 bytes) ```<p>Some complex formats (such as pptx) still have limited compatibility. I planned to add standard error messages and better format compatibilities. I&#x27;d be pleased to see feedback or issues on my project.<p>QA: Why not Pandoc? Pandoc is a great tool, but sometimes we only need a convenient little one to handle common conversion tasks.<p>How compatible is it to docx&#x2F;pptx? Currently it supports basic text conversion, and I&#x27;m trying to make it be able to keep advanced formatting.