| "references": { | |
| "effect": { | |
| "repository": "Effect-TS/effect", | |
| "description": "Use for canonical Effect source, APIs, tests, and implementation patterns." | |
| }, | |
| "effect-monorepo": { | |
| "repository": "lucas-barake/effect-monorepo", | |
| "description": "Use for Lucas Barake's full-stack Effect monorepo patterns, composable policies, HttpApi contracts, Schema classes, and Layer composition." | |
| }, | |
| "accountability": { |
Some people do not want to autocomplete when they enter.
They will choose tab key instead since you have to press esc when you want to use enter key and at the same the unwanted suggestion shows up.
But some people find enter key is more handy instead.
Anyway, below shows 2 ways to turn this off.
| CLAUDE CODE: 15 GİZLİ AYAR VE KOMUT | |
| =================================== | |
| Videodaki tüm maddelerin kısa özeti. Komutları kopyalayıp doğrudan kullanabilirsiniz. | |
| Not: Ayarların çoğu ~/.claude/settings.json (genel) veya projedeki .claude/settings.json dosyasına yazılır. | |
| Dosyayı elle düzenlemek yerine Claude Code'a "bu ayarı settings dosyama ekle" demeniz de yeterli. | |
| 1. /init KOMUTUNU BAŞTAN YARATAN AYAR |
| name | better |
|---|---|
| description | Push the current task, or a prompt the user gives, to a deeper version of itself. Use only when the user explicitly types /better or $better. |
I want a deeper version of this task, not a bigger one. Before rewriting it: (1) say what a top professional in this field would do here that I'm not asking for; (2) name the rawest material they would start from instead of what has already been digested for me; (3) name the specific methods and tools they would use; (4) say what, other than you or me, would show the result is right. Then rewrite my prompt to ask for exactly that.
ONLY do this if you understand what this script does and when you are sure that this method is applicable to your card!!!
I'm not responsible for your doings! You are flashing the firmware of your ethernet card, in the worst case you endup with a soft- or even hardbricked card! Also this might void your warrenty.
Having said this, if you are uncertain if this will work for your card be sure to dump the ROM with a RPI, RPI Pico or 3.3v moded SPI-Flash Programmer:
| name | pragmatic-testing |
|---|---|
| description | Decides whether to write a test, what it asserts, which test double it uses, and how many tests a change needs. Load before adding, changing, reviewing, or deleting any test or test double, when auditing existing tests for low value, and when proving that a test prune lost no protection. |
Tests exist so we can change the product and still ship it. A test that fails on every refactor and never catches a real bug makes change harder.
| # using curl -s https://gist.githubusercontent.com/mark99i/c2611df4a12ce1d048cd08fbc52f0002/raw/b8953281aece44d965ee244a3c42d7a28fe639dc/ubuntu-install-hyperv-addons.sh | bash | |
| echo 'hv_vmbus' >> /etc/initramfs-tools/modules | |
| echo 'hv_storvsc' >> /etc/initramfs-tools/modules | |
| echo 'hv_blkvsc' >> /etc/initramfs-tools/modules | |
| echo 'hv_netvsc' >> /etc/initramfs-tools/modules | |
| apt update | |
| apt -y install linux-virtual linux-cloud-tools-virtual linux-tools-virtual | |
| update-initramfs -u |
| # Fetch remote updates, rebase the stack onto the latest base, and push changed layers. | |
| # Works best when stack branches use the `stack/` prefix, e.g. `stack/my-feature`. | |
| customCommands: | |
| - key: '#' | |
| description: 'gh stack' | |
| commandMenu: | |
| - key: 'h' | |
| description: 'Handle stack state' | |
| commandMenu: |
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.
