GitHub热门项目 | 🦸 AI 编程超能力 · 中文增强版 — superpowers（116k+ ⭐）完整汉化 + 6 个中国原创 skills，让 Claude Code / Copilot CLI / Hermes Agent / Cursor / Windsurf / Kiro / Gemini CLI 等 16 款 AI 编程工具真正会干活 | Stars: 6,504 | 66 stars today | 语言: JavaScript

GitHub热门项目 | All parts of Claude Code's system prompt, 27 builtin tool descriptions, sub agent prompts (Plan/Explore/Task), utility prompts (CLAUDE.md, compact, statusline, magic docs, WebFetch, Bash cmd, security review, agent creation). Updated for each Claude Code version. | Stars: 11,638 | 28 stars today | 语言: JavaScript

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Solos announced a new version of its AirGo smart glasses, one that forgoes cameras for a sleeker design and an AI assistant that relies on voice interactions. Last year's AirGo A5 weighed 36 to 40 grams depending on the frame style, but the new AirGo A6 weigh around 19 grams. Part of the weight savings […]

Google is going to give content creators and website owners a better idea of how people find their social media profiles and YouTube content through Search. With a new feature in the Google Search Console called "platform properties," Google says that you'll be able to "easily track which search terms lead people to your Instagram, […]

You can clip a cover over the cameras, which could be a double-edged sword.

It feels like childhood.

iFixit is best known for its detailed gadget teardowns and toolkits designed to help you crack open and troubleshoot your own electronics. Today it announced a new toolkit that's instead tailored to household repairs or DIY projects like fixing appliances or assembling flat-packed furniture. iFixit describes its $34.95 Megalodon Driver Kit as a "compact kit […]

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Most of the "AI for observability" work I see right now hands the language model the judgment. I think that's backwards. Feed it the alert, feed it some metrics, ask it what's wrong, what should be done, and let it make the judgement call. Based on my experience working with language models, I decided that inverting the process provides better results. The short version: in my alerting pipeline, the set of allowable classifications is fixed in deterministic Python, and the model has to pick from it. The LLM's only job is to turn a structured verdict into an easily digestible sentence. It never decides whether something is bad, how bad it is, or what category of problem it is. It narrates within a decision space the code has already locked down. TL;DR: Instead of letting an LLM decide what's wrong with an alert, I let deterministic Python make every operational decision and restrict the model to explaining the result in plain English. The code classifies, validates, and aggregates; the LLM only narrates. That keeps the data consistent, prevents hallucinated classifications, and ensures the monitoring pipeline continues working even if the model fails. The problem I run a small managed monitoring service. Alertmanager fires, a webhook lands, and historically that webhook produced a line like HighMemoryUsage on host web-vm, severity warning, which is accurate, but not terribly helpful. The person reading it still has to know what HighMemoryUsage implies, whether this host always runs hot, and whether to care. I wanted plain-English context attached to the alerts without altering the alert delivery process. The obvious move was to throw the whole alert at an LLM and ask it to explain. I tried that in the first iteration of this experiment, expecting it to be somewhat accurate, but not entirely reliable, and it did not disappoint, the model was confidently inconsistent. The same alert, fired three times, produced three different "root cause" categories. One run called a

Part 1: Solving GOP Structure and Compatibility Issues Operating a digital television network isn't just about keeping channels on air—it's about maintaining quality that viewers expect and troubleshooting issues before they escalate. When something goes wrong in live broadcasting, every second counts. But how do you quickly pinpoint whether the problem lies in encoder settings, transport stream structure, or temporal metadata? This is where specialized stream analysis tools become essential. In this series of articles, we'll walk through real-world scenarios that broadcast engineers face daily and show practical approaches to diagnosing and resolving them. When File Analysis Becomes Critical While live monitoring catches issues as they happen, file-based analysis is your diagnostic microscope. Here's the typical workflow: something breaks in production, engineers capture a few minutes of the problematic stream, and now they need to understand exactly what went wrong. File analyzers serve three primary purposes: Troubleshooting: Identifying the root cause of broadcast issues Encoder optimization: Fine-tuning compression settings Quality control: Validating compliance with standards and specifications Let's explore how this works in practice with actual tools and techniques. The GOP Structure Problem Here's a scenario every broadcast engineer has encountered: legacy set-top boxes or older TV models suddenly can't play your stream. The audio works, video starts and stops, or you see freezing. The culprit? Often, it's the GOP (Group of Pictures) structure. H.264 has been around since 2003—over 20 years. Almost everything supports it, yet you'll still find legacy equipment that struggles with certain configurations. Specifically, the number of B-frames can make or break compatibility. Why B-frames matter: They enable lower bitrates while maintaining quality by increasing encoding complexity through bidirectional prediction. But this comes at a cost—a more complex refere

After visiting Japan for the first time a decade ago I became completely enamoured with Tokyo's Yamanote Line railway loop. Particularly the sonic experience of it. Like so many others I fell in love with the charming departure melodies and enjoyed discovering experiences like Yamanot.es ( https://news.ycombinator.com/item?id=45045307 ) here on Hacker News when I returned home. But it wasn't until my second trip to Tokyo that I truly appreciated how much the door chimes, on-board announcements a