mattmc3

Firefox 157 - Nova UI

Firefox introduced a UI overhaul in v157 called Nova. While some of the changes are welcome, for users of vertical tabs you may agree with me that that part is absolutely terrible looking. This gist gives you a simple userChrome.css to restore tabs to the pre-Nova look while still retaining the rest of the Nova UI enhancements. This script fixes the look of both vertical and horizontal tabs by removing the excessive outlining and roundedness. You can keep the good parts of the new Nova look, but fix the parts that are broken.

Steps to fix

arianvp

Native Secure Enclave backed ssh keys on MacOS

It turns out that MacOS Tahoe can generate and use secure-enclave backed SSH keys! This replaces projects like https://github.com/maxgoedjen/secretive

There is a shared library /usr/lib/ssh-keychain.dylib that traditionally has been used to add smartcard support to ssh by implementing PKCS11Provider interface. However since recently it also implements SecurityKeyProivder which supports loading keys directly from the secure enclave! SecurityKeyProvider is what is normally used to talk to FIDO2 devices (e.g. libfido2 can be used to talk to your Yubikey). However you can now use it to talk to your Secure Enclave instead!

orepras

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name: bahasa-indonesia-plain description: > Tulis dan edit teks antarmuka, panduan, dokumentasi, atau konten apa pun dalam Bahasa Indonesia yang lugas, inklusif, dan ramah semua orang, menggunakan prinsip bahasa polos (plain language), EYD, desain trauma-informed, aksesibilitas kognitif, dan framework RASA (Ritmis, Akurat, Sarat Makna, Alami) sebagai lensa evaluasi kualitas tulisan. Gunakan skill ini saat menulis UI copy, microcopy, laporan, panduan pengguna, komunikasi layanan publik, atau teks apa pun yang harus dipahami siapa saja sejak pertama kali membacanya.

flamerix-ai

Claude Code burns ~15–20% of your tokens on a 3-word status line. Here's how to turn it off

by Flamerix AI · MIT License

Platforms: Linux and Windows 11 tested by us; macOS reported by others. Tested on Claude Code 2.1.257–2.1.317. The binary is not modified (BUN_OPTIONS=--preload). An update can silently undo it, so see Verify.

TL;DR

Every ~30 seconds, Claude Code re-sends each background agent's full transcript to the model to

ageis

[user]
    email = kevingallagher@gmail.com
    name = Kevin M. Gallagher
    signingkey = 0x3B324F4FF73BECF8
[core]
    editor = vim
    excludesfile = /etc/gitignore
    autocrlf = true
    compression = 9
    fscache = true

orepras

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name: english-plain description: > Write and edit English text that is plain, inclusive, and easy for everyone to read, using plain language principles, trauma-informed design, cognitive accessibility, and the RASA framework (Rhythmic, Accurate, Substantive, Authentic) to judge quality. Use for UI copy, microcopy, error messages, guides, reports, documentation, public-service content, or any text that should be understood on the first read, including by non-native readers. user-invokable: true

aamiaa

Caution

As of August 26th 2026, Discord has started suspending quest access of people caught automating quest completion.

Some users have received the following system message:

There isn't much I can do to make the script undetected, so use it at your own risk, as you WILL get flagged by doing so.

Complete Recent Discord Quest

toncotales

The 50/15/5 Rule Budget Plan CLI

A lightweight Python command-line tool that calculates your monthly budget allocations using the Fidelity 50/15/5/30 rule.

Budget Breakdown

• Essential Expenses (50%): Housing, utilities, groceries, transportation, and bills
• Retirement Savings (15%): Long-term retirement investments and pension funds
• Short-Term Savings (5%): Emergency fund and near-term financial goals
• Discretionary (30%): Lifestyle, dining out, entertainment, and personal wants

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.