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You write instructions for your coding agent. It ignores one of them. You rewrite it more forcefully, in bold, with "IMPORTANT" in front. It still ignores it. Before blaming the model, check whether it ever saw the text. Each of the three cases below is documented behaviour of a tool you already use, each one drops part of your instructions on the floor, and none of them prints a warning. 1. Cursor ignores .md files in .cursor/rules Project rules in Cursor must use the .mdc extension. Cursor's own docs put it plainly: a plain .md file there is ignored by the rules system, because it has nowhere to declare the description , globs and alwaysApply frontmatter that tells Cursor when to apply it. So a file sitting in exactly the right directory, with exactly the right content, does nothing. No error at startup, no "rule skipped" line, nothing in the UI. Ten-second check: find .cursor/rules -name '*.md' 2>/dev/null Any output is a rule that isn't loading. Rename to .mdc and add the frontmatter. A detail that makes this worse: people who set up .md rules a while ago report that they used to work. If that's right, a working setup stopped working at some point during an update, and nothing announced it — so "I checked this once" is not protection. 2. Codex truncates your AGENTS.md files — as a set, not one by one Codex reads the AGENTS.md files that apply to your working directory: a global one, the repo root, and the nested ones on the path. It concatenates them, and the 32 KB truncation applies to that combined payload . This is the part that catches people, because every individual file looks fine: AGENTS.md 12 KB ✓ fine packages/api/AGENTS.md 12 KB ✓ fine packages/web/AGENTS.md 12 KB ✓ fine ----- 36 KB ✗ 4 KB never reaches the model Nobody wrote a "too big" file. The rule you carefully put at the bottom of the last one simply isn't there when the model reads. Check it: find . -name AGENTS.md -not -path '*/node_modules/*' | xargs wc -c Add your global ~/.codex/AGENTS.md t

The Seattle Times and Newsday are just the latest plaintiffs to take OpenAI to court, alleging copyright infringement. The two outlets say the company used their journalism as training data for its AI models without permission and often reproduces passages from their reporting in response to user queries. This is similar to lawsuits filed by […]

Frontier AI models are expensive to call directly. A single day of heavy Claude or GPT-5 usage in an agentic coding loop can rack up real money. But a small cluster of gateways and coding-agent products has figured out how to hand developers meaningful free access anyway. This post breaks down four of them — Freebuff, AgentRouter, OpenRouter, and Experiential Labs — and the actual tactics each one uses to keep the lights on while giving inference away. 1. OpenRouter — the "free router" and community-subsidized models OpenRouter is a unified, OpenAI-compatible API that sits in front of hundreds of models from dozens of providers. Its free tier isn't a special OpenRouter model — it's a curated set of models, mostly open-weight ones like DeepSeek R1, Llama variants, and Qwen releases, that carry a literal $0/M-token price tag because providers or OpenRouter itself are subsidizing the compute. The tactic: instead of making you pick a free model by hand, OpenRouter built openrouter/free , a router that automatically picks a working free model for each request, smart enough to filter for whatever the request needs — image understanding, tool calling, structured outputs, and so on. That's a neat trick: it turns "which free model works today" from a research chore into a solved problem, since free-model availability shifts constantly and the router absorbs that churn for you. To keep this sustainable, OpenRouter caps usage per key — community trackers put it at roughly 20 requests per minute and 200 requests per day on the free tier — and openly frames free access as ecosystem-building: it says free models help democratize access to AI and let large numbers of people experiment and learn, while it keeps expanding capacity by onboarding new providers and covering some costs directly. In plain terms, the free tier is marketing and community goodwill; paid usage across the rest of the catalog is the actual business. Using it is as simple as pointing any OpenAI-compatible SDK a

GitHub热门项目 | AI-assisted PCB design for KiCAD 10. Native KiCAD plugin — a single Rust binary exposing 217 schematic, layout, routing, placement, design-review, and manufacturing tools to Claude, or the LLM of your choosing | Stars: 453 | 31 stars today | 语言: Rust

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My harness flagged the model for sending the wrong arguments. It compared what the model actually...

Google has open-sourced Mantis, an AI-agent framework designed to automate the software vulnerability lifecycle, from identifying and validating vulnerabilities to reproducing and fixing them. Google says it developed Mantis to address the high rate of false positives and hallucinated vulnerabilities produced by conventional AI-powered code scanning. By Sergio De Simone

TL;DR 📌 🕰️ Then: I built google-chat-electron by hand , over months , reading tutorial after tutorial. ⚡ Now: I rebuilt the whole thing as google-chat-tauri in less than 24 hours — and I did not write the code. Claude did. 🦀 Plot twist: I don't know Rust. Not a little — at all . The AI wrote every line of it. 📦 Result: a ~ 3 MB Linux installer instead of a bundled Chromium. 🧪 Status: pre-release. Fun project. Stable version coming after real-world testing. Let's dive in. 👇 The Electron Era: Months of Honest, Manual Labour 😅 A few years ago I wanted Google Chat in a real window — with a tray icon, an unread badge and native notifications — instead of a browser tab that disappears among thirty other browser tabs. So I built it. In Electron. By hand. And it took months . Not because Electron is bad, but because every single thing was a tutorial: How do I make a tray icon that actually behaves? How do I keep the app alive when the window closes? How do I intercept a link and open it in the real browser? How do I package a .deb ? A .dmg ? An installer for Windows? Why does this work on my machine and nowhere else? 🙃 Every answer was a blog post, a GitHub issue thread, or a Stack Overflow reply from 2017 that almost applied. It shipped, people used it, and I was genuinely proud of it. The Tauri Rewrite: One Evening, One Prompt Loop 🤖 Last week I opened Claude Code and asked it to port the app to Tauri v2 . I did not open the Rust book. I did not read the Tauri docs. I described what the app should do, reviewed what came back, ran it on my actual laptop, and reported what broke. Timeline: Time What happened 15:42 git init 17:01 Full Electron → Tauri v2 port committed 17:25 Desktop notifications working < 24h later v0.0.1 tagged and released 🎉 38 commits. ~3,600 lines of Rust and JavaScript. Zero lines typed by me. This is what people mean by vibe coding — and honestly, it felt less like programming and more like directing . My job became: describe the behaviour, test it on

This is a shortened version of my original post . My wife and I have blogged about every trip since our honeymoon 10 years ago. For the people at home, for ourselves later, and by now for our children. We took turns writing, but both had photos and videos on their phones. The text was never the hard part. The photos and videos were: every day one of us sent them from the phone to the other, who had to upload them and sort them into the entry in the right order. So I wrote Texttile , an open-source blog engine built for writing together. One entry, two screens Multiple people can have the same entry open. One of them has the text and types, the other watches the words arrive and can take the text over with one click. Both can still work on the gallery. Photos and videos belong in the same gallery. Videos come from your own server. Drop one in and Texttile converts it, thumbnail included. No YouTube embed, no player from anywhere else. One container, one folder Phoenix, LiveView, ffmpeg and SQLite live in one Docker image. Everything is in /data . Move that folder and you move the blog. A reader's browser talks to your server and nothing else. No CDN, no tracker, no hosted font. What it is not There are no roles, no permission matrix, no plugins, no theme marketplace. Everybody with an account is an admin. I built it for people who trust each other, because that is who writes a blog together. You can try it or read the source . The full story includes a video showing both screens. How do you blog on the road?

A library isn't code. A library is thirty or forty decisions somebody already made, correctly,...

I Built a Mobile Terminal Around My herdr + Codex Workflow I am building Termish , an open-source mobile remote-work tool for SSH/Mosh terminals, file management, remote screens, and AI-assisted development. The unusual part is that I built much of Termish through Termish itself. My daily workflow is: Termish on my phone → herdr on my host → Codex in the project The development environment and AI tools run on my own machine. My phone is where I enter commands, describe tasks, upload screenshots, inspect changes, and check the resulting UI. Termish is both the product I am building and a tool I use to build it. Put remote work in your pocket. Source code: github.com/ttermish/termish Why do AI-assisted coding on a phone? A phone is not a replacement for a desktop machine. Its screen is smaller. Reading a large codebase is harder. Long debugging sessions are more comfortable on a larger display. Those limitations are real. But AI-assisted development changes part of the workflow. Many tasks become: Describe a requirement. Provide context. Let an agent make changes. Review the output. Run a command or test. Decide what to change next. Some of that loop works well on a phone. For example, when I think of a feature away from my desk, I can open the project and ask an agent to start implementing it. When I find a UI problem, I can upload a screenshot to the host and ask the agent to inspect it together with the code. After the change is done, I can review the diff, run tests, and check the actual UI through a remote screen. The goal is not to write an entire application on a phone. The goal is to make a phone a useful place to start work, inspect work, and keep a task moving. Why another SSH and AI coding tool? This is a fair question. Tools such as Termius and Blink already provide strong SSH, Mosh, and file-management experiences. If you already have a setup that works well, you can run Codex, Claude Code, or other agents through a terminal today. Happy and similar produ

Struct tags are just strings — a typo'd checker name, a wrong-typed field, or a renamed cross-field target all compile fine and fail silently at runtime. checkerlint catches all three before you ship. Struct tags are string literals. The Go compiler checks that your struct compiles — it has no idea what checkers:"eq-field:Passwrd" means, so a typo in a field name, a checker applied to a field of the wrong type, or a renamed field that a cross-field rule still points at all compile fine. They fail later, at runtime, sometimes silently, sometimes as a panic in the middle of handling a request. type Registration struct { Password string `checkers:"trim required"` ConfirmPassword string `checkers:"required eq-field:Passwrd"` // typo: no such field Age int `checkers:"email"` // email is string-only } Nothing here trips go build , go vet , or a normal linter — they all treat checkers:"..." as an opaque string. The first bug only surfaces the moment someone submits a registration form and eq-field can't find a field called Passwrd . The second is worse: email assumes a string under the hood, so calling it on an int field panics at validation time instead of returning a normal error. checkerlint is a go/analysis -based static analyzer, shipped as its own module in the Checker repo, that reads these tags at build/lint time and catches exactly this class of bug before it ships: ./registration.go:3:2: checkerlint: eq-field references field "Passwrd", which doesn't exist on this struct ./registration.go:4:2: checkerlint: email requires a string, but the field's type is int What it actually checks Three things, all specific to how checkers / validate tags can go wrong: Unknown checker names. Every token in the tag has to be a registered checker, normalizer, field-relative checker, omitempty , or a name your own code registered via RegisterMaker / RegisterFieldMaker with a string literal. Typo requird instead of required and checkerlint flags it — nothing else in your toolchain w

Background : In migration projects involving different databases, incompatibility of SQL syntax is often encountered. Question : If there is a large amount of code that needs to be rewritten, manual processing would be time-consuming and prone to errors. Is it possible to achieve automatic conversion of code syntax in large quantities through tools? Solution : The open-source tool ZGLanguage can be utilized to perform automated conversion of SQL code in large batches. For example： Suppose SQL PIVOT function is as follows : SELECT * FROM ( select country , state , yr , qtr , sales , cogs from table111 ) PIVOT ( SUM ( sales ) AS ss1 , SUM ( cogs ) AS sc FOR qtr IN ( 'Q1' AS Quarter1 , 'Q2' AS Quarter2 , 'Q3' AS Quarter3 , 'Q4' AS Quarter4 ) ) tmp ; Using the ZGLanguage conversion rule, execute the conversion to obtain the result : SELECT * FROM ( select ### , ### , ### SUM ( case when qtr = 'Q1' then sales else null end ) AS Quarter1_ss1 , SUM ( case when qtr = 'Q2' then sales else null end ) AS Quarter2_ss1 , SUM ( case when qtr = 'Q3' then sales else null end ) AS Quarter3_ss1 , SUM ( case when qtr = 'Q4' then sales else null end ) AS Quarter4_ss1 , SUM ( case when qtr = 'Q1' then cogs else null end ) AS Quarter1_sc , SUM ( case when qtr = 'Q2' then cogs else null end ) AS Quarter2_sc , SUM ( case when qtr = 'Q3' then cogs else null end ) AS Quarter3_sc , SUM ( case when qtr = 'Q4' then cogs else null end ) AS Quarter4_sc from ( select country , state , yr , qtr , sales , cogs from table111 ) where qtr IN ( 'Q1' , 'Q2' , 'Q3' , 'Q4' ) group by ### , ### , ### ) tmp ; The conversion rule is as follows : __DEF_FUZZY__ Y __DEF_DEBUG__ N __DEF_CASE_SENSITIVE__ N __DEF_LINE_COMMENT__ -- __DEF_LINES_COMMENT__ /* */ __DEF_STR__ __IF_KW__ <1,100> [1,1]ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz [0,100]ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789_ [NO] XXX __DEF_PATH__ __FROM_PIVOT_1_1__ 1 : frm @ %__IF_KW__ | from : tab @ | __TABLE_NAME__ : ssl @