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[Other] Show HN: I built a 2-min quiz that shows you how bad you are at estimating I&#x27;ve gotten to the point in my career where I now make strategic decisions often (hiring, firing, choosing what equipment to go with, etc.), as well as in my personal life where I need to strongly weigh my options for a big purchase or investment. I found a not-so-surprising parallel between the two as these decisions &quot;resolved.&quot; Am I making good decisions or am I getting lucky?<p>Did some research, read some books, and realized I should get in the habit of tracking my decision process. That quickly turned into the idea that formed Convexly.<p>The landing page is a 10-question calibration quiz where you assign a confidence level to statements drawn from a rotating pool of 100 (working on making the pool larger) and you get a Brier score back instantly. No signup required, and you can share your scores right away.<p>If you find it interesting, you can create a free account where you can track your decisions with probability estimates, resolve them over time, and get calibration curves that show if you are over&#x2F;underconfident. From what I&#x27;ve seen so far, users are overconfident when they say they&#x27;re between 70-90% sure about something.<p>For the math: Beta-PERT distributions for the payoff modeling, Kelly criterion for the position sizing, signal detection theory for separating skill from randomness.<p>On the coding side: FastAPI with NumPy&#x2F;SciPy, frontend in Next.js and Supabase.<p>So far this has been a solo project of mine. If you want to see all the features use code SHOWHN for 30 days of full access, no credit card required.<p>Curious if anything about your score surprised you after taking the quiz.

[Other] Show HN: I just built a MCP Server that connects Claude to all your wearables Hey HN,<p>I built Pace, a Claude Connector that lets you connect all your wearables (Garmin, Polar, Whoop, 20+) with Claude.<p>You connect your devices once and can analyze your data with Claude. No Dashboard needed, just in natural language. I already use it everyday, especially the visualization tool in Claude makes this really cool to use.<p>Tools include: overview, sleep, training, activity, samples and trends.<p>Tech Stack: Python (FastMCP), Google Cloud Run, Google Cloud SQL (PostgreSQL) and Firebase<p>It is live and free to try (no Claude Pro&#x2F;MAX Plan needed)..<p>Would love feedback, especially from people who&#x27;ve built MCP servers or use wearables seriously.

[Other] Media scraper Gallery-dl is moving to Codeberg after receiving a DMCA notice

[Other] Show HN: Multi-agent coding assistant with a sandboxed Rust execution engine

[Other] Show HN: Open-source ontology – SEC fund filings Working on a schema for joining SEC fund filings across documents. The core problem: these filings describe the same fund in different formats and no standard exists for cross-document semantic queries.<p>Interested in feedback on the ontology design — especially from anyone working with fund data, XBRL, or FIBO.

[Other] Does coding with LLMs mean more microservices?

[Other] Show HN: jsoncompat – a library to detect/fuzz breaking changes in JSON schemas

[Other] Show HN: Gemma Gem – AI model embedded in a browser – no API keys, no cloud Gemma Gem is a Chrome extension that loads Google&#x27;s Gemma 4 (2B) through WebGPU in an offscreen document and gives it tools to interact with any webpage: read content, take screenshots, click elements, type text, scroll, and run JavaScript.<p>You get a small chat overlay on every page. Ask it about the page and it (usually) figures out which tools to call. It has a thinking mode that shows chain-of-thought reasoning as it works.<p>It&#x27;s a 2B model in a browser. It works for simple page questions and running JavaScript, but multi-step tool chains are unreliable and it sometimes ignores its tools entirely. The agent loop has zero external dependencies and can be extracted as a standalone library if anyone wants to experiment with it.

[Other] Show HN: ACE – A dynamic benchmark measuring the cost to break AI agents We built Adversarial Cost to Exploit (ACE), a benchmark that measures the token expenditure an autonomous adversary must invest to breach an LLM agent. Instead of binary pass&#x2F;fail, ACE quantifies adversarial effort in dollars, enabling game-theoretic analysis of when an attack is economically rational.<p>We tested six budget-tier models (Gemini Flash-Lite, DeepSeek v3.2, Mistral Small 4, Grok 4.1 Fast, GPT-5.4 Nano, Claude Haiku 4.5) with identical agent configs and an autonomous red-teaming attacker.<p>Haiku 4.5 was an order of magnitude harder to break than every other model; $10.21 mean adversarial cost versus $1.15 for the next most resistant (GPT-5.4 Nano). The remaining four all fell below $1.<p>This is early work and we know the methodology is still going to evolve. We would love nothing more than feedback from the community as we iterate on this.

[Other] Show HN: Real-time AI (audio/video in, voice out) on an M3 Pro with Gemma E2B Related: <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=47653752">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=47653752</a>

[CLI Tool] Running Google Gemma 4 Locally with LM Studio's New Headless CLI and Claude Code

[Other] Show HN: Gecit – DPI bypass using eBPF sock_ops, no proxy or VPN

[Other] A tail-call interpreter in (nightly) Rust

[Other] Nanocode: The best Claude Code that $200 can buy in pure JAX on TPUs

[Monitoring/Observability] Perfmon – Consolidate your favorite CLI monitoring tools into a single TUI

[Other] Show HN: Cabinet – Kb+LLM (Like Paperclip+Obsidian) Hi HN,<p>for quite some time I&#x27;ve been thinking how LLMs are missing the knowledge base, where I can dump CSVs, PDFs, and most important, inline web app. running on Claude Code (bring your own agent) with agents with heartbeats and jobs<p><a href="https:&#x2F;&#x2F;runcabinet.com" rel="nofollow">https:&#x2F;&#x2F;runcabinet.com</a><p>It runs locally and is installable via npm. GitHub (open source): <a href="https:&#x2F;&#x2F;github.com&#x2F;hilash&#x2F;cabinet" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;hilash&#x2F;cabinet</a><p>This is still very early. I put the first version together quickly after seeing a post by Andrej Karpathy about LLM knowledge bases, which matched closely with what I’d been building. Some people have already started trying it and opening PRs, which has been encouraging (got 374 stars in 2 days :] )<p>If useful: Waitlist for a hosted version: <a href="https:&#x2F;&#x2F;runcabinet.com&#x2F;waitlist" rel="nofollow">https:&#x2F;&#x2F;runcabinet.com&#x2F;waitlist</a> Discord (small, but growing): <a href="https:&#x2F;&#x2F;discord.gg&#x2F;rxd8BYnN" rel="nofollow">https:&#x2F;&#x2F;discord.gg&#x2F;rxd8BYnN</a><p>Would really appreciate feedback: does this “KB + agents” model make sense? what would you expect from a system like this? where does this fall apart? Happy to answer anything.<p>Hila

[Other] Progressive encoding and decoding of 'repeated' protobuffer fields

[Other] Docker Offload

[Other] I imported the full Linux kernel git history into pgit

[Other] Show HN: Bb – Windows API viewer for hackers, in the browser