🛠️ All DevTools

[Monitoring/Observability] Moving a large-scale metrics pipeline from StatsD to OpenTelemetry / Prometheus Full disclosure - I formerly worked for Grafana Labs.<p>The size of this Grafana Mimir deployment would rank it in the top echelon of customers. The irony is that this may be a $0 revenue user for Grafana Labs.

[DevOps] Show HN: Hiraeth – AWS Emulator With the recent changes around Localstack pricing&#x2F;licensing I&#x27;ve been hunting for alternatives. I decided that it might be a fun experiment to try rolling my own. SQS is a service I use heavily so I chose that as the first service to implement. I have more services planned and in development.<p>A few things I think are cool:<p>4MB Docker Image Size<p>Instant Startup<p>AWS Sigv4 Authentication<p>A little admin UI that can be helpful for development&#x2F;troubleshooting<p>Most of the SQS API implemented, the rest will soon follow :)

[Other] Keycard – inject API keys into subprocesses, never touch shell env

[IDE/Editor] Agent - Native Mac OS X coding ide/harness

[CLI Tool] I made a terminal pager

[CLI Tool] Hacker News CLI

[Other] Show HN: Omi – watches your screen, hears conversations, tells you what to do Spent 4 months and built Omi for Desktop, your life architect: It sees your screen, hears your conversations and will advise you on what to do next<p>Basically Cluely + Rewind + Granola + Wisprflow + ChatGPT + Claude in one app<p>I talk to claude&#x2F;chatgpt 24&#x2F;7 but I find it frustrating that i have to capture&#x2F;send screenshots of my screen and that it doesn&#x27;t help proactively during my work<p>Whenever omi sees something wrong about my workflow, it will send me a proactive notification with advice. It will also point to something I&#x27;m missing.<p>The hardest part was to nail proactivity - after trying 20+ similar tools I didn&#x27;t find a single one with smart proactive notifications based on content on your screen. I made it look at your screen every second with 4 main prompts:<p>1. Is the user productive or distracted?<p>2. Is there anything useful to say right now?<p>3. is there any task to add to do later?<p>4. is there anything important to remember about the user?<p>Full stack: - Swift - Rust backend - Deepgram transcription - Claude code for messaging - GPT 5.4 summaries - Gemini for embeddings and translation<p>Open source, stores screenshots locally, uses Claude Code for chat. Has cloud to sync with hardware or mobile app but can be disabled in settings

[Package Manager] Show HN: Dependicus, a dashboard for your monorepo's dependencies Late last year, I was digging into some dependency-related tech debt, and struggling with how long it takes to run pnpm&#x27;s introspection commands like &#x27;pnpm why&#x27; in a medium-size monorepo. So I started working on a simple static site generator that would let me view the output of these expensive commands all at once, to make problems clearly visible instead of requiring deep exploration one at a time.<p>Once I had that working, I realized I had enough data to add ticket tracking. It uses the data it gathers from the package manager to keep Linear or GitHub issues updated. And by auto-assigning those issues to coding agents, I get a Dependabot-but-better experience: agents keep up with API updates in addition to just bumping versions, and group related updates automatically.<p>It&#x27;s still early days, but it&#x27;s working really well for us and I think people will find value in it, so I&#x27;m sharing here!

[CLI Tool] Show HN: Libretto – Making AI browser automations deterministic Libretto (<a href="https:&#x2F;&#x2F;libretto.sh" rel="nofollow">https:&#x2F;&#x2F;libretto.sh</a>) is a Skill+CLI that makes it easy for your coding agent to generate deterministic browser automations and debug existing ones. Key shift is going from “give an agent a prompt at runtime and hope it figures things out” to: “Use coding agents to generate real scripts you can inspect, run, and debug”.<p>Here’s a demo: <a href="https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=0cDpIntmHAM" rel="nofollow">https:&#x2F;&#x2F;www.youtube.com&#x2F;watch?v=0cDpIntmHAM</a>. Docs start at <a href="https:&#x2F;&#x2F;libretto.sh&#x2F;docs&#x2F;get-started&#x2F;introduction" rel="nofollow">https:&#x2F;&#x2F;libretto.sh&#x2F;docs&#x2F;get-started&#x2F;introduction</a>.<p>We spent a year building and maintaining browser automations for EHR and payer portal integrations at our healthcare startup. Building these automations and debugging failed ones was incredibly time-consuming.<p>There’s lots of tools that use runtime AI like Browseruse and Stagehand which we tried, but (1) they’re reliant on custom DOM parsing that&#x27;s unreliable on older and complicated websites (including all of healthcare). Using a website’s internal network calls is faster and more reliable when possible. (2) They can be expensive since they rely on lots of AI calls and for workflows with complicated logic you can’t always rely on caching actions to make sure it will work. (3) They’re at runtime so it’s not interpretable what the agent is going to do. You kind of hope you prompted it correctly to do the right thing, but legacy workflows are often unintuitive and inconsistent across sites so you can’t trust an agent to just figure it out at runtime. (4) They don’t really help you generate new automations or help you debug automation failures.<p>We wanted a way to reliably generate and maintain browser automations in messy, high-stakes environments, without relying on fragile runtime agents.<p>Libretto is different because instead of runtime agents it uses “development-time AI”: scripts are generated ahead of time as actual code you can read and control, not opaque agent behavior at runtime. Instead of a black box, you own the code and can inspect, modify, version, and debug everything.<p>Rather than relying on runtime DOM parsing, Libretto takes a hybrid approach combining Playwright UI automation with direct network&#x2F;API requests within the browser session for better reliability and bot detection evasion.<p>It records manual user actions to help agents generate and update scripts, supports step-through debugging, has an optional read-only mode to prevent agents from accidentally submitting or modifying data, and generates code that follows all the abstractions and conventions you have already in your coding repo.<p>Would love to hear how others are building and maintaining browser automations in practice, and any feedback on the approach we’ve taken here.

[Other] Show HN: MCP server gives your agent a budget (save tokens, get smarter results) As a consultant I foot my own Cursor bills, and last month was $1,263. Opus is too good not to use, but there&#x27;s no way to cap spending per session. After blowing through my Ultra limit, I realized how token-hungry Cursor + Opus really is. It spins up sub-agents, balloons the context window, and suddenly, a task I expected to cost $2 comes back at $8. My bill kept going up, but was I really going to switch to a worse model?<p>No. So I built l6e: an MCP server that gives your agent the ability to budget. It works with Cursor, Claude Code, Windsurf, Openclaw, and every MCP-compatible application.<p>Saving money was why I built it, but what surprised me was that the process of budgeting changed the agent&#x27;s behavior. An agent that understands the limitations of the resources doesn&#x27;t try to speculatively increase the context window with extra files. It doesn&#x27;t try to reach every possible API. The agent plans ahead, sticks to it, and ends work when it should.<p>It works, and we&#x27;ve been dogfooding it hard. After v1 shipped, the rest of l6e was all built with it. We launched the entire docs site using frontier models for $0.99. The kicker was every time l6e broke in development, I could feel the pain. The agent got sloppy, burned through context, and output quality dropped right along with it.<p>Install: pip install l6e-mcp<p>Docs: <a href="https:&#x2F;&#x2F;docs.l6e.ai" rel="nofollow">https:&#x2F;&#x2F;docs.l6e.ai</a><p>GitHub: <a href="https:&#x2F;&#x2F;github.com&#x2F;l6e-ai&#x2F;l6e-mcp" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;l6e-ai&#x2F;l6e-mcp</a><p>Website: <a href="https:&#x2F;&#x2F;l6e.ai" rel="nofollow">https:&#x2F;&#x2F;l6e.ai</a><p>Happy to answer questions about the system design, calibration models, or why I can&#x27;t go back to coding without it.

[Other] Elevated errors on Claude.ai, API, Claude Code

[Monitoring/Observability] MCP as Observability Interface: Connecting AI Agents to Kernel Tracepoints

[Other] Show HN: Every CEO and CFO change at US public companies, live from SEC Built this solo. It watches SEC filings for executive and board changes, extracts the data, and shows it in real time. 2,100+ changes in the last 30 days. The comp data is interesting: average new CEO total comp is $8.4M across 284 appointments. The &#x2F;explore page is fully open, no login needed.

[Other] Retrofitting JIT Compilers into C Interpreters

[Other] Turn Claude Code into a full game dev studio — 49 AI agents, 72 workflow skills, and a complete coordination system mirroring real studio hierarchy.

[Other] An open source template for building cloud agents.

[Other] Show HN: Xit – a Git-compatible VCS written in Zig The marquee feature is patch-based merging, similar to Darcs and Pijul. I think xit is the first version control system (VCS) to have this feature while still being git compatible. See the 100% human-written readme for more.

[Other] Want to Write a Compiler? Just Read These Two Papers (2008)

[Other] Direct Win32 API, Weird-Shaped Windows, and Why They Mostly Disappeared

[CLI Tool] Wacli – WhatsApp CLI: sync, search, send