| claude --model claude-opus-4-8 --permission-mode dontAsk |
| #!usr/bin/env python3 | |
| def readFile(file): | |
| data = [] | |
| with open(file, "rb") as f: | |
| tmp = f.read() | |
| for i in range(0,len(tmp), 2): | |
| data.append(tmp[i+1] + 1) | |
| data = bytes(data).decode("latin-1") |
Act as an expert YouTube strategist and creative copywriter for musicians. I will provide you with the lyrics of a song, potentially including timestamp data. Your task is to analyze the mood, theme, and imagery of the lyrics to generate a complete, SEO-optimized YouTube content package.
Please output the following sections formatted clearly with markdown:
0:00 - Intro, `1:15 - [Lyr
| <?xml version="1.0" encoding="UTF-8"?> | |
| <!-- This file contains the mappings for a Microsoft Xbox One Controller to actions within XBMC --> | |
| <!-- The drivers for Linux and Windows do not always match. Mappings for Win32 will be presented --> | |
| <!-- first, with Linux alts second. --> | |
| <!-- The <global> section is a fall through - they will only be used if the button is not --> | |
| <!-- used in the current window's section. Note that there is only handling --> | |
| <!-- for a single action per button at this stage. --> | |
| <!-- The format of a mapping is: --> | |
| <!-- <device name="name"> --> |
Some notes and tools on fingerprinting minified JavaScript libraries, AST fingerprinting, source code similarity, etc.
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.
If your laptop’s CPU is running very hot and you’ve tried to undervolt it, you’ve probably discovered there’s no easy way to do so—especially on laptops whose BIOS doesn’t expose those controls. I ran into the same issue with my Ryzen 7 5800H, despite numerous attempts, I couldn’t undervolt because the firmware simply wouldn’t allow it. While it may seem drastic, disabling Turbo Boost is one workaround—and you might be surprised how little real-world performance you lose by turning it off.