covid20212022

Tuesday, April 21, 2026

Show HN: Ctx – a /resume that works across Claude Code and Codex https://ift.tt/6Bt2TUw

Show HN: Ctx – a /resume that works across Claude Code and Codex ctx is a local SQLite-backed skill for Claude Code and Codex that stores context as a persistent workstream that can be continued across agent sessions. Each workstream can contain multiple sessions, notes, decisions, todos, and resume packs. It essentially functions as a /resume that can work across coding agents. Here is a video of how it works: https://ift.tt/8Wgb4DE I initially built ctx because I wanted to try a workstream that I started on Claude and continue it from Codex. Since then, I’ve added a few quality of life improvements, including the ability to search across previous workstreams, manually delete parts of the context with, and branch off existing workstreams.. I’ve started using ctx instead of the native ‘/resume’ in Claude/Codex because I often have a lot of sessions going at once, and with the lists that these apps currently give, it’s not always obvious which one is the right one to pick back up. ctx gives me a much clearer way to organize and return to the sessions that actually matter. It’s simple to install after you clone the repo with one line: ./setup.sh, which adds the skill to both Claude Code and Codex. After that, you should be able to directly use ctx in your agent as a skill with ‘/ctx [command]’ in Claude and ‘ctx [command]’ in Codex. A few things it does: - Resume an existing workstream from either tool - Pull existing context into a new workstream - Keep stable transcript binding, so once a workstream is linked to a Claude or Codex conversation, it keeps following that exact session instead of drifting to whichever transcript file is newest - Search for relevant workstreams - Branch from existing context to explore different tasks in parallel It’s intentionally local-first: SQLite, no API keys, and no hosted backend. I built it mainly for myself, but thought it would be cool to share with the HN community. https://ift.tt/moFVkZp April 20, 2026 at 11:35PM

Monday, April 20, 2026

Show HN: Agentkit-CLI, one canonical context file for AI coding agents https://ift.tt/E8gBR2a

Show HN: Agentkit-CLI, one canonical context file for AI coding agents https://mikiships.github.io/agentkit-cli/ April 20, 2026 at 10:04PM

Sunday, April 19, 2026

Show HN: A privacy-first, local-LLM note app for iOS (Google Keep alternative) https://ift.tt/KrmxHaX

Show HN: A privacy-first, local-LLM note app for iOS (Google Keep alternative) https://ift.tt/P6rQswD April 19, 2026 at 11:59PM

Show HN: Free PDF redactor that runs client-side https://ift.tt/dbNrwXy

Show HN: Free PDF redactor that runs client-side I recently needed to verify past employment and to do so I was going to upload paystubs from a previous employer, however I didn't want to share my salary in that role. I did a quick search online and most sites required sign-up or weren't clear about document privacy. I conceded and signed up for a free trial of Adobe Acrobat so I could use their PDF redaction feature. I figured there should be a dead simple way of doing this that's private, so I decided to create it myself. What this does is rasterize each page to an image with your redactions burned in, then it rebuilds the PDF so the text layer is permanently destroyed and not just covered up and easily retrievable. I welcome any and all feedback as this is my first live tool, thanks! https://redactpdf.net April 20, 2026 at 01:39AM

Show HN: Faceoff – A terminal UI for following NHL games https://ift.tt/9gnRhIw

Show HN: Faceoff – A terminal UI for following NHL games Faceoff is a TUI app written in Python to follow live NHL games and browse standings and stats. I got the inspiration from Playball, a similar TUI app for MLB games that was featured on HN. The app was mostly vibe-coded with Claude Code, but not one-shot. I added features and fixed bugs by using it, as I spent way too much time in the terminal over the last few months. Try it out with `uvx faceoff` (requires uv). https://ift.tt/NVuyAMC April 20, 2026 at 12:44AM

Show HN: Google Gemini Is Scanning Your Photos – and the EU Said No https://ift.tt/q2CGbs6

Show HN: Google Gemini Is Scanning Your Photos – and the EU Said No Google has expanded its Personal Intelligence feature so that Gemini can now access your Google Photos face data, Gmail, YouTube history, and search activity to generate personalized AI images — live for US paid subscribers as of April 2026. https://ift.tt/r5T7NsL... April 19, 2026 at 11:36PM

Saturday, April 18, 2026

Show HN: AI Subroutines – Run automation scripts inside your browser tab https://ift.tt/jJLSZRb

Show HN: AI Subroutines – Run automation scripts inside your browser tab We built AI Subroutines in rtrvr.ai. Record a browser task once, save it as a callable tool, replay it at: zero token cost, zero LLM inference delay, and zero mistakes. The subroutine itself is a deterministic script composed of discovered network calls hitting the site's backend as well as page interactions like click/type/find. The key architectural decision: the script executes inside the webpage itself, not through a proxy, not in a headless worker, not out of process. The script dispatches requests from the tab's execution context, so auth, CSRF, TLS session, and signed headers get added to all requests and propagate for free. No certificate installation, no TLS fingerprint modification, no separate auth stack to maintain. During recording, the extension intercepts network requests (MAIN-world fetch/XHR patch + webRequest fallback). We score and trim ~300 requests down to ~5 based on method, timing relative to DOM events, and origin. Volatile GraphQL operation IDs are detected and force a DOM-only fallback before they break silently on the next run. The generated code combines network calls with DOM actions (click, type, find) in the same function via an rtrvr.* helper namespace. Point the agent at a spreadsheet of 500 rows and with just one LLM call parameters are assigned and 500 Subroutines kicked off. Key use cases: - record sending IG DM, then have reusable and callable routine to send DMs at zero token cost - create routine getting latest products in site catalog, call it to get thousands of products via direct graphql queries - setup routine to file EHR form based on parameters to the tool, AI infers parameters from current page context and calls tool - reuse routine daily to sync outbound messages on LinkedIn/Slack/Gmail to a CRM using a MCP server We see the fundamental reason that browser agents haven't taken off is that for repetitive tasks going through the inference loop is unnecessary. Better to just record once, and get the LLM to generate a script leveraging all the possible ways to interact with a site and the wider web like directly calling backed API's, interacting with the DOM, and calling 3P tools/APIs/MCP servers. https://ift.tt/J5mrUDp April 18, 2026 at 04:03AM

Show HN: Praxis – Lab data to publication-ready figures in one Python package https://ift.tt/itwyvOA

Show HN: Praxis – Lab data to publication-ready figures in one Python package https://ift.tt/u5Nj9xO April 19, 2026 at 01:15AM

Show HN: I built Panda to get up to 99% token savings https://ift.tt/NL73vPK

Show HN: I built Panda to get up to 99% token savings https://ift.tt/dVw9mNM April 18, 2026 at 05:00PM

Friday, April 17, 2026

Show HN: Waputer – The WebAssembly Computer https://ift.tt/nlCwDAr

Show HN: Waputer – The WebAssembly Computer Waputer is an operating system that runs entirely in the browser. When you visit the website at https://waputer.app , a kernel written in JavaScript sets up a filesystem and launches a WebAssembly program, which in turn talks to the kernel to handle the display and input. A purely terminal-based version is at https://waputer.dev . My original intention was to create programs that run in the browser that have a lot more in common with the desktop. The traditional "hello world" program is not really suited for the web. Waputer changes that. The GitHub repo at https://ift.tt/g5z06Up gives a very brief overview of compiling a C program and running it on Waputer. There is a blog available from the main site that has a long-form explanation of Waputer and my motivations if you want some additional reading. https://waputer.app April 18, 2026 at 12:46AM