ModularDot
Make your site clear to people and answer engines
What it does
ModularDot runs a free, deterministic 16-check answer-readiness scan on an authorized public website. It shows the exact evidence behind identity, access, proof, and decision-support results—without claiming AI rankings or citations. The $149 founding Fix Pack adds a prioritized page map, three publish-ready answer blocks, corrected JSON-LD, and before/after evidence. Two disclosed owned production references moved 62→98 and 49→98 under the same v2 method.
A free, evidence-based AI answer-readiness scan and fixed-price pack of publish-ready fixes for public websites with real work to explain.
If someone—or the AI helping them—lands on your site, can they tell what you do, who it is for, and why to trust it? ModularDot finds missing explanations, evidence, decisions, and structured identity, then delivers publish-ready fixes. AI answers move. Personalization, location, model updates, and prompt wording all change what appears. A single mystery score can’t promise future citations. So ours doesn’t. Can a machine identify your site, organization, offer, and audience? Are core pages and machine-readable signals available without ambiguity? Can evaluators find attributable evidence and the people or organization behind it? Do you answer next-step, fit, comparison, and participation…from modulardot.com
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Hey HN, Henry from Cactus here! We previously released Cactus Needle, a 14MB agentic LLM for tool call, device use, and structured extraction for phones, wearables, smart homes, small robots and microcontrollers. We got really great feedback here, and have now incorporated the suggestions to release Needle 2. The whole model is a single 14MB binary that runs a full session in 28MB of RAM; 45m parameters at 2bit compression. Needle hits 500 tokens/sec decode speed on a Raspberry Pi 5, sits between 400-1,500 tokens/sec on VR devices like Meta Quest 3S and Apple Vision Pro, and ranges…
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Launched alongside, August 2026
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Life & fun · 10d ago · louisabraham.github.io


- SA
Hello HN! I found that picking out plausible but diverse skin tones for my digital art and game development projects was kind of difficult, and I got curious about if there was a way to define a color space that made it easy. I've built a color picker and procedural generation algorithm based on the space as well as a bunch of other fun js features and demos throughout the page that use the equations. If you find it interesting, I have lots of explanations of how I built it and what properties the space has. The methodology might be a bit shaky, but hopefully the result is as helpful for…
Life & fun · Aug 2026 · toneyalexander.github.io


I trained a 125M-parameter transformer to autocomplete piano performances in real time (~108 notes/sec on an iPhone 15). The idea is basically GitHub Copilot or Tabnine, except instead of prompting it with code, you prompt it by playing a few notes on a MIDI piano. The model then continues what you played, entirely on-device. The app is free if anyone wants to try it. Happy to answer questions about the model, training, Core ML, or the many things that didn't work.
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