| 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:
| #!/usr/bin/env bash | |
| set -Eeuo pipefail | |
| trap cleanup SIGINT SIGTERM ERR EXIT | |
| script_dir=$(cd "$(dirname "${BASH_SOURCE[0]}")" &>/dev/null && pwd -P) | |
| usage() { | |
| cat <<EOF | |
| Usage: $(basename "${BASH_SOURCE[0]}") [-h] [-v] [-f] -p param_value arg1 [arg2...] |
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 | |
| # --slave /usr/bin/$1 $1 /usr/bin/$1-\${version} \\ | |
| function register_clang_version { | |
| local version=$1 | |
| local priority=$2 | |
| update-alternatives \ | |
| --install /usr/bin/llvm-config llvm-config /usr/bin/llvm-config-${version} ${priority} \ |
| using namespace System.Management.Automation | |
| using namespace System.Management.Automation.Language | |
| if ($host.Name -eq 'ConsoleHost') | |
| { | |
| Import-Module PSReadLine | |
| } | |
| #Import-Module PSColors | |
| #Import-Module posh-git | |
| Import-Module -Name Terminal-Icons |
Research on how other coding assistants implement context compaction to manage long conversations.
Context compaction (also called "handoff" or "summarization") is a technique to manage the context window in long coding sessions. When conversations grow too long, performance degrades and costs increase. Compaction summarizes the conversation history into a condensed form, allowing work to continue without hitting context limits.
| { | |
| "$schema": "https://raw.githubusercontent.com/code-yeongyu/oh-my-openagent/dev/assets/oh-my-opencode.schema.json", | |
| "agents": { | |
| "sisyphus": { | |
| "model": "opencode/big-pickle", | |
| "fallback_models": [ | |
| { | |
| "model": "opencode/nemotron-3-ultra-free", | |
| "variant": "max" | |
| }, |