Reconstructed from Danny Postma's talk How I Built My Own AgentOS on Claude's Agent SDK (So You Can Too) (2026). This document is both a product spec for a human and an implementation prompt for an AI coding agent. Build exactly this system. Do not invent features that are not specified here.
Role contracts and prompts in this file are reconstructed from the talk, not his verbatim files. Mark every reconstructed prompt in code comments and docs as such.
| #/usr/bin/env python | |
| from LaunchServices import LSSetDefaultHandlerForURLScheme | |
| from LaunchServices import LSSetDefaultRoleHandlerForContentType | |
| # 0x00000002 = kLSRolesViewer | |
| # see https://developer.apple.com/library/mac/#documentation/Carbon/Reference/LaunchServicesReference/Reference/reference.html#//apple_ref/c/tdef/LSRolesMask | |
| LSSetDefaultRoleHandlerForContentType("public.html", 0x00000002, "com.operasoftware.operanext") | |
| LSSetDefaultRoleHandlerForContentType("public.xhtml", 0x00000002, "com.operasoftware.operanext") | |
| LSSetDefaultHandlerForURLScheme("http", "com.operasoftware.operanext") | |
| LSSetDefaultHandlerForURLScheme("https", "com.operasoftware.operanext") |
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.
Audit this entire codebase for materially useful simplifications in its data structures, state representation, control flow, algorithms, and ownership.
This is an audit-only exercise. Do not edit files, run tests, implement recommendations, commit, or push. Read-only inspection commands are allowed.
You are the coordinator. Continue until the complete codebase has been reviewed and the final audit is validated.
Inspect the repository and inventory every identifiable subsystem.
| <?php | |
| // This file walks you through the most common features of PHP's SQLite3 API. | |
| // The code is runnable in its entirety and results in an `analytics.sqlite` file. | |
| // Create a new database, if the file doesn't exist and open it for reading/writing. | |
| // The extension of the file is arbitrary. | |
| $db = new SQLite3('analytics.sqlite', SQLITE3_OPEN_CREATE | SQLITE3_OPEN_READWRITE); | |
| // Errors are emitted as warnings by default, enable proper error handling. |
Hello and welcome to my Shortcuts Catalog!
This is a public resource designed to help people get started with Siri Shortcuts and the Shortcuts app.
It’s made up of the Shortcuts Library, a collection of over 125+ shortcuts grouped into folders, and the Action Directory, a documentation of 125+ of the actions in the Shortcuts app used to build shortcuts.
Enjoy!