🛠️ All DevTools

[Other] Arch Linux Now Has a Bit-for-Bit Reproducible Docker Image

[Other] OpenAI's response to the Axios developer tool compromise

[Other] OpenAI model for masking personally identifiable information (PII) in text

[Other] Cljfx: A declarative desktop UI framework in Clojure

[Other] Over-editing refers to a model modifying code beyond what is necessary

[CLI Tool] Show HN: ShellTalk brings deterministic text-to-bash Hi HN! I built a CLI tool called ShellTalk for macOS, Linux, and web (WebAssembly) that maps English text to the corresponding Bash commands.<p>ShellTalk is written in Swift and available under the Apache 2.0 license on GitHub. I was inspired a few weeks ago after reading the Meta-Harness paper and seeing a tool called Hunch that did something similar using the Apple Foundation model. I often forget flag names and orders, but I wanted something that worked consistently. The 3B AFM worked surprisingly well with Hunch, but it felt slow and sometimes slight changes in what I wrote would result in very different outputs.<p>ShellTalk attempts to match the input with an intent category (Git, File I&#x2F;O, etc), then a template, and finally to slot-fill and adapt to the specific command version and BSD vs GNU syntax. It has a few other tricks including using NSSpellChecker on macOS to auto-correct certain typos, and scores the output on safety (i.e. is the action destructive or non-reversible).<p>It&#x27;s clearly far from perfect, but has very tight testing and validation cycles compared to using an LLM, is very portable, and might eventually work in other languages or environments like Windows. I&#x27;m curious to hear what others think.

[DevOps] Show HN: Broccoli, one shot coding agent on the cloud Hi HN — we built Broccoli, an open-source harness for taking coding tasks from Linear, running them in isolated cloud sandboxes, and opening PRs for a human to review.<p>We’re a small team, and our main company supplies voice data. But we kept running into the same problem with coding agents. We’d have a feature request, a refactor, a bug, and some internal tooling work all happening at once, and managing that through local agent sessions meant a lot of context switching, worktree juggling, and laptops left open just so tasks could keep running.<p>So we built Broccoli. Each task gets its own cloud sandbox to be executed end to end independently. Broccoli checks out the repo, uses the context in the ticket, works through an implementation, runs tests and review loops, and opens a PR for someone on the team to inspect.<p>Over the last four weeks, 100% of the PRs from non-developers are shipped via Broccoli, which is a safer and more efficient route. For developers on the team, this share is around 60%. More complicated features require more back and forth design with Codex &#x2F; Claude Code and get shipped manually using the same set of skills locally.<p>Our implementation uses:<p>1. Webhook deployment: GCP 2. Sandbox: GCP or Blaxel 3. Project management: Linear 4. Code hosting &amp; CI&#x2F;CD: Github<p>Repo: <a href="https:&#x2F;&#x2F;github.com&#x2F;besimple-oss&#x2F;broccoli" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;besimple-oss&#x2F;broccoli</a><p>We believe that if you should invest in your own coding harness if coding is an essential part of your business. That’s why we decided to open-source it as an alternative to all the cloud coding agents out there. Would love to hear your feedback on this!

[Database] DuckDB 1.5.2 – SQL database that runs on laptop, server, in the browser

[Other] Qwen3.6-27B: Flagship-Level Coding in a 27B Dense Model

[Other] Our eighth generation TPUs: two chips for the agentic era <a href="https:&#x2F;&#x2F;cloud.google.com&#x2F;blog&#x2F;products&#x2F;compute&#x2F;tpu-8t-and-tpu-8i-technical-deep-dive" rel="nofollow">https:&#x2F;&#x2F;cloud.google.com&#x2F;blog&#x2F;products&#x2F;compute&#x2F;tpu-8t-and-tp...</a>

[Other] OpenMetadata is a unified metadata platform for data discovery, data observability, and data governance powered by a central metadata repository, in-depth column level lineage, and seamless team collaboration.

[Monitoring/Observability] 🪢 Open source LLM engineering platform: LLM Observability, metrics, evals, prompt management, playground, datasets. Integrates with OpenTelemetry, Langchain, OpenAI SDK, LiteLLM, and more. 🍊YC W23

[CLI Tool] GitHub CLI now collects pseudoanonymous telemetry

[Other] Kernel code removals driven by LLM-created security reports

[Other] Show HN: Gemini Plugin for Claude Code I built a plugin that lets Claude Code delegate work to Gemini CLI.<p>I started this after finding myself reaching for Gemini more often on long context repo work. I have been especially liking Gemini’s codebaseinvestigator for long context.<p>This is inspired by openai&#x2F;codex-plugin-cc.<p>Code Review, adversarial review. Under the hood its Gemini CLI over ACP<p>Would love feedback from people using Claude Code, Gemini CLI, or ACP. I am especially curious whether this feels useful outside my own workflow.<p>Its a great combo with Opus 4.7 + Gemini 3.1 workflows

[Other] A curated collection of 1000+ agent skills from official dev teams and the community, compatible with Claude Code, Codex, Gemini CLI, Cursor, and more.

[Other] Show HN: Open Chronicle – Local Screen Memory for Claude Code and Codex CLI I built an open source version of OpenAI Chronicle.<p>Some design decisions I made:<p>1. Local first: OCR uses Apple Vision, summarization supports local AI providers via Vercel AI SDK. Nothing leaves your computer. 2. Multiple Provider: exposes MCP so any coding agents can use it. 3. Swift menubar app: efficient, low-footprint 4. Blacklist apps: password managers, messaging apps (Slack, WhatsApp, Messenger), mail clients are on default blocklist.<p>Current Limitations: 1. Mac only. Mac-first is a feature. 2. Small local models with weak structured-output support will fail on generateObject. 3. Retrieval is LIKE-query keyword search. FTS and optional embeddings are on the list.<p>Demo video (6s): <a href="https:&#x2F;&#x2F;youtu.be&#x2F;V75tnvIdovc" rel="nofollow">https:&#x2F;&#x2F;youtu.be&#x2F;V75tnvIdovc</a><p>Curious what you think the right balance between exclusionlist allowlists. Happy to answer anything.

[Other] Show HN: MemFactory: Unified Inference and Training Framework for Agent Memory Memory-augmented Large Language Models (LLMs) are essential for developing capable, long-term AI agents. Recently, applying Reinforcement Learning (RL) to optimize memory operations, such as extraction, updating, and retrieval, has emerged as a highly promising research direction. However, existing implementations remain highly fragmented and task-specific, lacking a unified infrastructure to streamline the integration, training, and evaluation of these complex pipelines. To address this gap, we present MemFactory, the first unified, highly modular training and inference framework specifically designed for memory-augmented agents. Inspired by the success of unified fine-tuning frameworks like LLaMA-Factory, MemFactory abstracts the memory lifecycle into atomic, plug-and-play components, enabling researchers to seamlessly construct custom memory agents via a &quot;Lego-like&quot; architecture. Furthermore, the framework natively integrates Group Relative Policy Optimization (GRPO) to fine-tune internal memory management policies driven by multi-dimensional environmental rewards. MemFactory provides out-of-the-box support for recent cutting-edge paradigms, including Memory-R1, RMM, and MemAgent. We empirically validate MemFactory on the open-source MemAgent architecture using its publicly available training and evaluation data. Across the evaluation sets, MemFactory improves performance over the corresponding base models on average, with relative gains of up to 14.8%. By providing a standardized, extensible, and easy-to-use infrastructure, MemFactory significantly lowers the barrier to entry, paving the way for future innovations in memory-driven AI agents.

[CLI Tool] Show HN: gcx – The Official Grafana Cloud CLI Hi HN,<p>We’re excited to share gcx, a new CLI we’ve been building for Grafana Cloud.<p>With the rise of agentic coding tools like Claude Code and Codex we&#x27;re building faster than ever, but these agents are often blind to what’s actually happening in production.<p>gcx brings the full power of Grafana Cloud observability to your terminal. Query production. Investigate alerts. Let the Assistant root-cause issues. Ship fixes with observability built in. Without leaving your editor. gcx also comes packaged with a skills bundle that allow agents to see and act on your production telemetry. You can ask an agent to root-cause a latency spike, and it can actually fetch the telemetry, analyze the spans, and suggest a fix—all while having the full context of your codebase.<p>Do check it out and give us feedback!<p>Github link: <a href="https:&#x2F;&#x2F;github.com&#x2F;grafana&#x2F;gcx" rel="nofollow">https:&#x2F;&#x2F;github.com&#x2F;grafana&#x2F;gcx</a>

[Other] Show HN: Almanac MCP, turn Claude Code into a Deep Research agent I am Rohan, and I have grown really frustrated with CC&#x27;s search and read tools. They use Haiku to summarise all the search results, so it is really slow and often ends up being very lossy.<p>I built this MCP that you can install into your coding agents so they can actually access the web properly.<p>Right now it can:<p>- search the general web<p>- search Reddit<p>- read and scrape basically any webpage<p>Install it:<p>npx openalmanac setup<p>The MCP is completely free to use. We have also built a central store where you can contribute things you learned while exploring. If you find something useful, you can contribute it to the encyclopedia we&#x27;re building at Almanac using the same MCP.