Show HN: PixelDraw – simple drawing software for web(WASM) and desktop https://ift.tt/7UYNMGx

Show HN: PixelDraw – simple drawing software for web(WASM) and desktop https://ift.tt/1ptAkNo September 6, 2026 at 09:23PM

Show HN: Cowbull – Wordle-like game where you only get match counts https://ift.tt/lbhWvsN

Show HN: Cowbull – Wordle-like game where you only get match counts CowBull is a word game where you have to find the hidden four-letter word. You make guesses and get back the count of exact letter matches (bulls) and partial matches (cows). It’s a bit like Wordle, but you are not told the exact letters which match, only the count of matching letters. Scoring is based on the number of guesses and time used. There is a single player mode and a multi-player mode (no account required). The game source code is at https://ift.tt/c2nysQH . When I was younger, we used to play this game on paper at the back of the classroom during school and college in India. During Covid, I made this online version of the game to play with my kids. https://cowbull.co/ September 6, 2026 at 06:07AM

Show HN: I made Blocknado, an orbital stacker. Think Tetris with square rings https://ift.tt/9keEQKc

Show HN: I made Blocknado, an orbital stacker. Think Tetris with square rings I've loved stacker type games for as long as I can remember. But I've always wanted a version with a bit more strategy and puzzle dynamics. Blocknado is a game I've always wanted to play, maybe others will too. https://ift.tt/qBnJXxE September 6, 2026 at 05:46AM

Show HN: Merge Wikipedia articles across languages into one page https://ift.tt/ERUGfNn

Show HN: Merge Wikipedia articles across languages into one page https://ift.tt/6kers85 September 6, 2026 at 02:18AM

Show HN: Fast Cut Video tool for cutting video for Agents https://ift.tt/8QNLeWK

Show HN: Fast Cut Video tool for cutting video for Agents Hi HN, Build this tool in a couple of hours with OpenAI Codex to scratch an itch. As part of my videos workflows I needed to cut the videos myself since the agent is pretty bad cutting and timing using only the transcription. But using a big app like Premiere or DaVinci Resolve was overkill so I used Astra to build an app tailored to that very task. It will be useful to others with the same problem. Tested only on Silicon Macs, so any feedback is welcome. As part of my workflow when the agent get the video it can open the app with the video or videos loaded in the timeline for me to cut and then export the cuts in a format the agent can use and continue the workflow. https://ift.tt/ma91Cfx September 6, 2026 at 02:36AM

Show HN: Coder Eval – A Framework for Evals https://ift.tt/qB9DYMJ

Show HN: Coder Eval – A Framework for Evals We needed a framework to write our evals in and easily update them, run A/B tests, set all kinds of constraints (ex: timeouts, number of turns), and configure the execution environment (ex: sandboxes, dependencies, how to handle AskQuestion). We also have an agent judge. It’s all in a YAML file now. We seem to be moving toward a world where companies rely more and more on evals to decide what to ship, so this should be super helpful for normalizing evals across teams. https://ift.tt/R6F5bgI September 5, 2026 at 12:39AM

Show HN: TERMy – A fast terminal assistant that does not use LLMs https://ift.tt/IKuSDxg

Show HN: TERMy – A fast terminal assistant that does not use LLMs I love research and development, you may have heard of me because of PJON (Padded Jittering Operative Network). It is a network protocol I started developing in 2010, which was recently implemented in silicon by the ETH Zurich university thanks to the research of Pius Sieber. I am excited to share with you TERMy, a terminal assistant built on top of the NPC-Forge framework. Unlike everything else being built today, TERMy does not use embeddings, machine-learning or LLMs. It runs on the CPU (even on a Raspberry Pi Zero) both in the terminal or client-side in a browser tab and responds in milliseconds. It is a cynical but very knowledgeable Linux terminal assistant that translates your natural language into shell commands without relying on a single artificial neuron. I had a chance to focus for 2 months on my personal projects since early July, during the strange times of AI price hikes and the end of subsidized tokenmaxing. I was curious to see if I could develop from scratch a terminal assistant capable of handling simple natural language requests. I have a bad memory and got used to ask to copilot "activate the virtual environment" or similar trivial operations spending a non negligible sum every month. I started thinking, maybe I can do something to make my workflow more efficient? Do I really need trillions of parameters to accomplish those tasks? How it Works When you type a prompt, it goes through a lightweight NLU pipeline written in ~1000 lines of Python that implement the following steps: 1. Strip expletives, interjections, encouraging, discouraging and thanking words (remove noise) 2. Sentiment analysis 3. Exact Match (very fast) 4. Template Match (slower) 5. Probabilistic Match (even slower) Step 5 relies on: 1. IDF (Inverse Document Frequency) to identify rare words. 2. BOW (Bag Of Words) to accommodate word inversions. 3. IDF weighted Levenshtein to safely handle typos. Permission gating is hardcoded into the dataset and enforced for all potentially destructive commands, so it's inherently safer than letting an unpredictable LLM run wild on your machine. - TERMy in operation: https://www.youtube.com/watch?v=qeIp0xePLBg - Variance and typo tolerance: https://www.youtube.com/watch?v=tQvGDk6fkk0 - Copilot integration: https://www.youtube.com/watch?v=Wzzouhq2a8A - Advanced features: https://www.youtube.com/watch?v=qeIp0xePLBg - Source Code: https://ift.tt/HKc7avw https://ift.tt/IKOyoTD September 4, 2026 at 02:33PM