下面是一份面向具体开源项目 github/spec-kit 的“入门指南 + 进阶最佳实践”整理与扩展，结合其仓库现有 README、文档结构与 Spec‑Driven Development（SDD）方法论进行体系化梳理，帮助你快速、规范、可持续地使用它。
Spec Kit 旨在把“规格（Spec）”置于开发核心：先沉淀项目原则与功能需求，再逐步澄清、规划、分解、实现，减少“一句话→直接写代码→返工”的低效模式。它通过一组 slash 命令与模板驱动你的 AI 编码代理（Copilot / Claude Code / Gemini CLI / Cursor 等）执行结构化过程，而不是一次性大模型代码生成。
核心价值：
Did you just install kernel-cachyos and got hit by bad shim signature when booting? Me too. This is how I fixed it.
First, make sure you have Secure Boot with mokutil --sb-state.
Note, there's a second way of doing this by using sbctl, but I didn't want to wipe my Secure Boot keys.
Need help? Feel free to leave a comment below, contact me (@mikaeldui) on the CachyOS Discord, or send me an email.
| ! ============================ | |
| ! YouTube Top Nav Bar | |
| ! ============================ | |
| ! always show normal YouTube logo, never that distracting doodleyoodle | |
| www.youtube.com##ytd-topbar-logo-renderer > a > ytd-yoodle-renderer | |
| www.youtube.com##ytd-topbar-logo-renderer > a > div:remove-attr(hidden) | |
| ! hide "Search with your voice" button (YouTube users have no voice) | |
| www.youtube.com###masthead #center #voice-search-button |
| i386 : iPhone Simulator | |
| x86_64 : iPhone Simulator | |
| arm64 : iPhone Simulator | |
| iPhone1,1 : iPhone | |
| iPhone1,2 : iPhone 3G | |
| iPhone2,1 : iPhone 3GS | |
| iPhone3,1 : iPhone 4 | |
| iPhone3,2 : iPhone 4 GSM Rev A | |
| iPhone3,3 : iPhone 4 CDMA | |
| iPhone4,1 : iPhone 4S |
If you ever need to download an entire website, perhaps for off-line viewing, wget can do the job — for example:
$ wget --recursive --no-clobber --page-requisites --html-extension --convert-links --restrict-file-names=windows --domains website.org --no-parent www.website.org/tutorials/html/
This command downloads the website www.website.org/tutorials/html/.
The options are:
--recursive: download the entire website--domains website.org: don't follow links outside website.org
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.
| Visual Studio 2026 18.x | |
| Professional: NVTDK-QB8J9-M28GR-92BPC-BTHXK | |
| Enterprise: VYGRN-WPR22-HG4X3-692BF-QGT2V | |
| Product Year Version Product Keys | |
| Visual Studio 2022 2021 17.x | |
| Professional: TD244-P4NB7-YQ6XK-Y8MMM-YWV2J | |
| Enterprise: VHF9H-NXBBB-638P6-6JHCY-88JWH | |
| Visual Studio 2019 2019 16.x |
