You will need something from your Stock ROM first. Get them all and Try to modify it using the procedure.
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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.
| #!/usr/bin/env bash | |
| set -euo pipefail | |
| issue=$1 | |
| ~/.claude/local/claude \ | |
| "Start working on issue #$issue | |
| - Keep an open mind. Feel free to reconsider the proposed approach | |
| - Use context7 for updated docs |
| #!/usr/bin/env zsh | |
| printf "PT09IENyb3NzT3ZlciBUcmlhbCBSZXNldCBTY3JpcHQgPT09DQpbSU5GT10gVGhpcyBzY3JpcHQgaXMgb25seSBtZWFudCBmb3IgZWR1Y2F0aW9uYWwgcHVycG9zZXMuDQpbV0FSTklOR10gSWYgeW91IGRpZG4ndCBnZXQgdGhpcyBzY3JpcHQgZnJvbSBueGZ4MjEncyBHaXRIdWIgR2lzdCwgaXQgbWF5IGhhdmUgYmVlbiB0YW1wZXJlZCB3aXRoLiBJZiB5b3UgZGlkIGdldCB0aGlzIG9mZiBueGZ4MjEncyBHaXRIdWIgR2lzdCwgeW91IGFyZSBzYWZlLCBjYXJyeSBvbi4gQmUgY2F1dGlvdXMgd2hlbiBydW5uaW5nIG9ubGluZSBjb2RlLCBhbmQgYWx3YXlzIGNoZWNrIGlmIGl0IGRvZXMgYW55dGhpbmcgdGhhdCB5b3UgZG9uJ3QgbGlrZS4=" | base64 -D | |
| echo "\n[LOG] Started at: $(date)" | |
| # Check if Homebrew exists, install if needed | |
| if ! command -v brew >/dev/null 2>&1; then | |
| echo "[INFO] Homebrew not found. Installing Homebrew..." | |
| /bin/bash -c "$(curl -fsSL https://raw.githubusercontent.com/Homebrew/install/HEAD/install.sh)" | |
The RISC-V specification is a very long technical document (hundreds of pages) that describes many "architectural parameters" — settings like how many memory-protection regions a chip supports, or how wide its registers are. Right now, people manually read through the spec and write these parameters into a structured file (YAML) by hand. This is slow and easy to get wrong. The goal of this project is to use AI (large language models) to read the spec text automatically and pull out these parameters correctly, so the manual work becomes much faster.
Using Zed IDE for Python? Feel free to use my settings.
Just keep a few things in mind:
- Font: I use Fira Code Nerd Font. Make sure it's installed on your system before applying.
- AI config: Update the AI model provider and model to match your own setup.
- Save behavior: I don't use auto-save — I save manually with Cmd+S. I also have on-save hooks (ruff, isort, black, ty) that may modify your file/buffer unexpectedly. Adjust these if that's not what you want.
Files:
Tip
See the blog post: https://mdinata.my.id/blogs/docker-on-postmarketos/
With postmarketOS and modified kernel (see https://blog.hypriot.com/post/verify-kernel-container-compatibility/), it's possible to natively run Docker on phone. Since postmarketOS runs Alpine Linux natively, there's no need to run VMs, chroot, or whatever it is. Just native. Ain't that cool?
| import Darwin | |
| import Foundation | |
| // known good: Swift 5 | |
| // runs on macOS, probably works on iOS (but haven't tried) | |
| /// Wraps `host_statistics64`, and provides info on virtual memory | |
| /// | |
| /// - Returns: a `vm_statistics64`, or nil if the kernel reported an error | |
| /// |