| name | explain-diff-html |
|---|---|
| description | Use when the user asks for a rich explanation of a code change, diff, branch, or PR. Produces HTML output. |
Please make me a rich, interactive explanation of the specified code change.
It should have these sections:
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.
| /Applications/Electrum.app/Contents/MacOS/run_electrum --testnet |
| env TARGET=pandoc yay -S --asdeps --needed $(yay -Si $TARGET | sed -n '/^Depends/,/^Conf/p' | head -n -1 | sed 's/^.*\s://g' | sed 's/:.*$//g' | sed 's/^\s*//g' | tr '\n' ' ') |
| #!/usr/bin/env python3 | |
| import itertools | |
| whats = [ | |
| '自經區', '自貿區', | |
| '摩天輪', '愛情摩天輪', '愛情產業鏈', | |
| '發大財', '愛河的水甘甘', '選總統', | |
| '迪士尼', |
Today (April 16th 2019 at noon) the first major clues to discover key #1 was set to be released in a few cities. A QR code with the words 'orbital' were found at these locations and looked like this: (https://imgur.com/a/6rNmz7T). If you read the QR code with your phone you will be directed to this url: https://satoshistreasure.xyz/k1
At this URL you are prompted to input a passphrase to decrypt the first shard. An obvious first guess was to try the word 'orbital' from the QR code. Not suprisingly this worked! This reveals a congratulations page and presents the first key shard:
ST-0001-a36e904f9431ff6b18079881a20af2b3403b86b4a6bace5f3a6a47e945b95cce937c415bedaad6c86bb86b59f0b1d137442537a8.
Now, we were supposed to wait until April 17th to get clues from the other cities for keys #2 and #3 but that wouldn't stop me from digging around with all the new information we had. All that time "playing" notpron (http://notpron.org/notpron/) years ago was going to help me here.
The first thing I noticed was
| #!/bin/bash | |
| JAILS=`fail2ban-client status | grep "Jail list" | sed -E 's/^[^:]+:[ \t]+//' | sed 's/,//g'` | |
| for JAIL in $JAILS | |
| do | |
| fail2ban-client status $JAIL | |
| done |
| #!/usr/bin/env expect | |
| # Login into PTT via SSH. | |
| # Combine crontab with this script so you don't forget to login PTT everyday. | |
| # Usage: /bin/bash -c ${FILE_PATH_OF_THIS_SCRIPT} | |
| # Example in crontab: | |
| # ptt auto login, every day at 12:00 PM | |
| # 0 12 * * * /bin/bash -c ${ABSOLUTE_FILE_PATH_OF_THIS_SCRIPT} |
| #!/usr/bin/sudo sh | |
| ## ruby_revealer.sh -- decrypt obfuscated GHE .rb files. 2.0.0 to 2.3.1+. | |
| ## From `strings ruby_concealer.so`: | |
| ## | |
| ## > This obfuscation is intended to discourage GitHub Enterprise customers | |
| ## > from making modifications to the VM. | |
| ## | |
| ## Well, good, as long as its not intended to discourage *me* from doing this! |