| 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:
| // Before attempting, use https://gifmaker.me/exploder/ to cut .gif into each frame. | |
| var favicon_images = [ | |
| 'http://website.com/img/tmp-0.gif', | |
| 'http://website.com/img/tmp-1.gif', | |
| 'http://website.com/img/tmp-2.gif', | |
| 'http://website.com/img/tmp-3.gif', | |
| 'http://website.com/img/tmp-4.gif', | |
| 'http://website.com/img/tmp-5.gif', | |
| 'http://website.com/img/tmp-6.gif' |
| """ | |
| The most atomic way to train and run inference for a GPT in pure, dependency-free Python. | |
| This file is the complete algorithm. | |
| Everything else is just efficiency. | |
| @karpathy | |
| """ | |
| import os # os.path.exists | |
| import math # math.log, math.exp |
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.
| /* | |
| * Copyright 2026 Kyriakos Georgiopoulos | |
| * | |
| * Licensed under the Apache License, Version 2.0 (the "License"); | |
| * you may not use this file except in compliance with the License. | |
| * You may obtain a copy of the License at | |
| * | |
| * http://www.apache.org/licenses/LICENSE-2.0 | |
| * | |
| * Unless required by applicable law or agreed to in writing, software |
| """Converts JSON objects into nix (hackishly).""" | |
| import sys | |
| import json | |
| INDENT = " " * 2 | |
| def strip_comments(t): |
| id | name | hash | type | |
|---|---|---|---|---|
| recommend_mobile_notice | RECOMMEND_MOBILE_NOTICE | 1486371970 | user | |
| friend_suggestions_new_user | FRIEND_SUGGESTIONS_NEW_USER | 363329543 | user | |
| friend_suggestions_old_user | FRIEND_SUGGESTIONS_OLD_USER | 2977431864 | user | |
| download_mobile_apps_notice_early | DOWNLOAD_MOBILE_APPS_NOTICE_EARLY | 4114369261 | user | |
| download_mobile_apps_notice_medium | DOWNLOAD_MOBILE_APPS_NOTICE_MEDIUM | 856100386 | user | |
| download_mobile_apps_notice_late | DOWNLOAD_MOBILE_APPS_NOTICE_LATE | 943913767 | user | |
| invite_new_invite | INVITE_NEW_INVITE | 2363164837 | user | |
| survey_video_chat | SURVEY_VIDEO_CHAT | 3678716185 | user | |
| search_experiment_dm | DM | 1770646087 | user |
The standard for building software with AI agents.
This is the compact, operational version of The Proof of Done Manifesto. It is designed to be pasted into AGENTS.md, CLAUDE.md, or the context of a coding agent.
It does not replace tests, review, CI, or product validation. It defines what an agent must show before it may claim that software work is done.