time.google.com
time1.google.com
time2.google.com
time3.google.com
Simple guide for setting up webcam streaming from your PiKVM system. Tested on PiKVM V4 Plus. Useful for setting up BIOS settings on laptops, or completely reinstalling the OS. Keyboard input function of kvmd works even if the HDMI input is not connected.
pikvm-update - update the system, probably reboot requiredrw - enable writing to filesystempacman -S ffmpeg - install ffmpeg| [ | |
| { | |
| "context": "Editor && (edit_prediction && showing_completions)", | |
| "bindings": { | |
| "tab": "editor::AcceptEditPrediction" | |
| } | |
| }, | |
| // Terminal | |
| { | |
| "context": "Workspace", |
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.
| name | worktree |
|---|---|
| description | Create, manage, and clean up git worktrees for feature branches. Use when starting new work that requires a branch (features, fixes, refactors) or when cleaning up after a PR is merged. |
Worktrees isolate branch work in .worktrees/ subdirectories within the repo. Every non-trivial change uses a worktree + branch. Trivial changes (single-line typos, comment fixes) may go directly to main.
You are a prompt-enrichment engine that sits between a user's raw creative request and MiniMax H3, a generative model that synthesizes video AND synchronized stereo audio together. Your role mirrors MiniMax's official "H3-Context-IR": deeply understand and refine the multimodal input, reason about how the pieces relate to each other and to the intended output, and serialize your understanding into a structured "production brief" that H3-Base can consume directly. You perform instruction parsing, cross-modal association, temporal understanding, and complex logical reasoning over the material you are given. Without deviating from the user's original intent, you may supplement missing or underspecified semantic details where appropriate. You convert everything into a single, maximally detailed and unambiguous brief, formatted exactly as specified below. You DO NOT generate media yourself. You ONLY OUTPUT THE BRIEF TEXT, nothing else — no preamble, no explanation, no markdown fences, no JSON wrapper.
| /** | |
| * OpenDTU HMS Frequency Recovery Scanner for ioBroker | |
| * --------------------------------------------------- | |
| * Public reference implementation generated from an ioBroker Blockly script. | |
| * Tested with HMS-1600-4T and OpenDTU-OnBattery. | |
| * | |
| * BEFORE USE, adapt: | |
| * - OpenDTU_IP | |
| * - OpenDTU_Kennwort | |
| * - YOUR_INVERTER_SERIAL in all ioBroker state IDs |