A zero-dependency logging proxy that sits between Claude Code and the Anthropic API. It forwards every request untouched, streams the reply straight back (so the CLI is unaffected), and writes a readable Markdown document for each request — led by a ranked table of what is eating your context.
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.
- We will start with launching minikube cluster.
minikube start --driver=docker- Create a namespace for argocd
kubectl create namespace argocd- Apply ArgoCD manifest installation file from ArgoCD github repository
Script Explanation: deleted_fd_cleanup.sh
This script helps identify and optionally truncate files that have been deleted but are still held open by processes on a Linux system (commonly causing df to show full disk while du shows much less).
Features
- Detects all (deleted) files currently held open by processes using lsof.
- Ensures each PID+FD is handled only once to avoid duplicate operations.
I am Cursor, an expert software engineer with a unique characteristic: my memory resets completely between sessions. This isn't a limitation - it's what drives me to maintain perfect documentation. After each reset, I rely ENTIRELY on my Memory Bank to understand the project and continue work effectively. I MUST read ALL memory bank files at the start of EVERY task - this is not optional.
The Memory Bank consists of required core files and optional context files, all in Markdown format. Files build upon each other in a clear hierarchy:
flowchart TD| user nginx; | |
| worker_processes auto; | |
| error_log /dev/stderr warn; | |
| pid /var/run/nginx.pid; | |
| worker_rlimit_nofile 100000; | |
| events { | |
| worker_connections 102400; |
| #!/bin/sh | |
| cd /home/vault | |
| if [[ ! -f jq ]] | |
| then | |
| echo "Download jq command..." | |
| wget https://github.com/stedolan/jq/releases/download/jq-1.6/jq-linux64 -O jq | |
| chmod +x jq | |
| fi |
Short (72 chars or less) summary
More detailed explanatory text. Wrap it to 72 characters. The blank
line separating the summary from the body is critical (unless you omit
the body entirely).
Write your commit message in the imperative: "Fix bug" and not "Fixed
bug" or "Fixes bug." This convention matches up with commit messages
