hirrolot

type term =
  | Lam of (term -> term)
  | Pi of term * (term -> term)
  | Appl of term * term
  | Ann of term * term
  | FreeVar of int
  | Star
  | Box

let unfurl lvl f = f (FreeVar lvl)

willurd

Each of these commands will run an ad hoc http static server in your current (or specified) directory, available at http://localhost:8000. Use this power wisely.

Discussion on reddit.

Python 2.x

$ python -m SimpleHTTPServer 8000

antonioCoco

// TcbElevation - Authors: @splinter_code and @decoder_it

#define SECURITY_WIN32
#include <windows.h>
#include <sspi.h>
#include <stdio.h>

#pragma comment(lib, "Secur32.lib")

void EnableTcbPrivilege(BOOL enforceCheck);

k16shikano

name	japanese-tech-writing
description	日本語の技術文書・書籍原稿の文章規範。整形（一文一行、引用ブロック、脚注、コラム記法）、段落と論証の構成（パラグラフライティング）、論証の厳密さ（ツッコミどころの除去）、読み手の負荷の管理、視点と語り、演出の抑制、LLM っぽい空句の禁止、冗長の排除を定める。日本語で技術書の章、草稿、記事、解説文を書くとき、または推敲・リライトするときに使用する。

日本語技術文書の文章規範

日本語で技術的な原稿（書籍の章、記事、解説文）を書く・推敲するときは、以下の規範に従う。

整形

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.

starhollow2008

{
  "5445": {
    "id": "5445",
    "artist": "Hanataba",
    "artist_unicode": "Hanataba",
    "title": "Night of Knights",
    "title_unicode": "Night of Knights",
    "creator": "v2b",
    "user_id": "47060",

mattpocock

agent-proxy — see the bloat in Claude Code's requests

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.

Run it

cleansely