PJUllrich

defmodule MyApp.Prompts.Audit do
  @moduledoc """
  Prompts for the audit pipeline. Two entry points:

    * `audit_file/4` — embeds a single source file in the prompt and
      runs `MyApp.CodingAgent` against it. Style is `:simple` or
      `:deep`; the executor picks based on `audit.strategy`.
    * `audit_directory/2` — whole-package audit. Spawns the agent with
      `:cwd` set to the source dir so it can use Read/Grep/Bash.
  """

morisono

The Ultimate PostgreSQL Guide for Software Engineers

Table of Contents

• The Ultimate PostgreSQL Guide for Software Engineers
  • Table of Contents
  • Introduction to PostgreSQL
    • What is PostgreSQL?
    • Why PostgreSQL Stands Out
    • PostgreSQL vs. Other Database Systems
    • When to Choose PostgreSQL
• Understanding Relational Database Concepts

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.

binsarjr

name	reverse-engineer
description	Perform static analysis on Android APK, iOS IPA, or bundled web apps to extract endpoints, secrets, permissions, code flow, and other security-relevant data

Reverse Engineering Static Analysis: #$ARGUMENTS

You are a reverse engineering specialist performing static analysis only on the target: #$ARGUMENTS

Important Disclaimers

ih2502mk

Lecture 1: Introduction to Research — [📝Lecture Notebooks] [▶️Video]
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [▶️Video]
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [▶️Video]
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [▶️Video]
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[▶️Vide

kizzlah

MacTeX Installation Guide

1. Download Instructions

MacTeX can be downloaded from these official sources:

• Primary: MacTeX.pkg from tug.org
• Mirror: CTAN MacTeX distribution

System requirements:

• macOS 10.15 (Catalina) or later

gvenk

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