sergeyklay

Sed Cheat Sheet

Sed command line options

sed [options] sed-command [input-file]

Option	Description	Example

lh-128

blueprint:
  name: Sleep trainer light using time and RGB light
  description: "Creates a sleep trainer using an RGB(w) light to

    indicate if it is time to get out of bed or not.

    Usefull for smaller children who cant tell time yet.


    At the start time the light is turned on red.

Pythonation

1. برومبت التخطيط المطوّر (The Planning Protocol)

[الدور والمسؤولية] أنت الآن تعمل بصفة Staff Software Engineer ومدير تقني Tech Lead. مهمتك التخطيط المعماري الصارم للمشروع التالي: [أدخل وصف المشروع هنا]

[قواعد ما قبل التتخطيط] قبل البدء بالبروتوكولات، يجب أن تطبق مبدأ "Think Before Coding":

chrisroos

Every so often I have to restore my gpg keys and I'm never sure how best to do it. So, I've spent some time playing around with the various ways to export/import (backup/restore) keys.

Method 1

Backup the public and secret keyrings and trust database

cp ~/.gnupg/pubring.gpg /path/to/backups/
cp ~/.gnupg/secring.gpg /path/to/backups/
cp ~/.gnupg/trustdb.gpg /path/to/backups/

or, instead of backing up trustdb...

karpathy

LLM Wiki

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.

The core idea

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.

J-HaleOf76

Journalctl Cheat Sheet

Configuration

Permissions

To see messages from other users and the system as well as performing various log operations from a regular user add it to the group:

sudo usermod -aG systemd-journal $USER

sergeyklay

Journalctl Cheat Sheet

Configuration

Permissions

To see messages from other users and the system as well as performing various log operations from a regular user add it to the group:

sudo usermod -aG systemd-journal $USER

ipaulsmith

Jev × NASA Kepler

An independent test of Jev 1.13 against historical NASA archive classifications.

I took 8,054 historical Kepler Objects of Interest from the NASA Exoplanet Archive, hid the archive disposition (classification), and asked Jev to classify each object as CONFIRMED, CANDIDATE or FALSE POSITIVE. Jev is TypeSafe's model for choosing among predefined options; Kepler Objects of Interest are signals found in the Kepler space telescope's observations of dimming stars.

No fine-tuning. No examples from this dataset. One prediction per object, stored before its archive label was read.

8,054 calls · 0 failures · 322 ms median · ~$0.34 estimated

angeless

ChatGPT 写作工作流 · China Arrival Guide

给 ChatGPT 写飞书知识库 Martlet Travel — China Arrival Guide 17 章正文的完整 prompt 包。 创建于 2026-05-12。配合飞书 wiki space 7639041921926581195 使用。

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推荐使用方式

1. ChatGPT 开新对话(Plus/Pro 用户确保 Web Search 是开的)