#developer-tools

200,000 tokens before a single answer feels less like a feature and more like a leak. That’s the part of this story that stuck with me. Not because token spend is automatically evil — sometimes you pay a lot for context and get something useful back — but because the reported behavior sounds wildly out of proportion to the task. If a Claude Code skill is quietly dragging in a mountain of docs just to get started, that’s not clever retrieval. That’s the sort of thing that makes people stop trusti

If you build with Claude or spend time inside Claude Code, stories like this matter because they reveal where the developer ecosystem is getting more opinionated, not less. The source here is basically a redirect to a post titled “zig-creator-calls-spade-a-spade,” which suggests the real discussion is about a sharp, direct take from Zig’s creator rather than a polished marketing piece. The page itself is just a redirect from a misleading slug to `/post/zig-creator-calls-spade-a-spade`. The desti

OpenUsage Community is a lightweight desktop app that pulls your usage and quota from 25+ AI coding services — Claude, Copilot, Cursor, Codex, Gemini, Grok and more — and shows them together in your menu bar or system tray, so you never have to open a single provider dashboard to know where you stand. It is an independent, community-maintained continuation of the original OpenUsage project. The community fork was created after the original moved toward a Swift / macOS-first direction; this versi

`tokenspeed` は、LLMの tokens-per-second（1秒あたりに出るtoken数） を「数字」ではなく「体感」で理解するためのツール `code` / `text` / `think` / `agent` の4モードがあり、出力内容によって「同じ速度でも速くも遅くも感じる」ことを見せてくれる 5 tok/s から 800 tok/s までのプリセットがあり、実際のモデル速度の感覚をつかみやすい tokenの数え方は各社の厳密なtokenizerではなく、BPE風の近似 「tok/sの数字は同じでも、コードと文章では体感がまるで違う」という点が、このツールの一番おもしろいところ LLMのベンチマークを見ていると、よく出てくるのが「47 tok/s」「180 tok/s」「500 tok/s」といった数字です。 でも正直、こういう数字ってピンと来にくいんですよね。 1秒に30 tokenって、速いの？ 遅いの？ 生活の中のどの感覚に近いの？ となりがちです。 そこで登場するのが `tokenspeed` です。 これは、LLMが出力する to