{"$schema":"https://ejfox.com/schema/page-twin@1.json","kind":"project_index","url":"https://ejfox.com/projects","json_url":"https://ejfox.com/projects.json","generator":"ejfox.com/json-twin@1","data":[{"slug":"projects/terminal-tools","title":"Terminal Tools","html":"

Fourteen small programs for the terminal: utilities for working inside tmux, a few input and display experiments, and some games and toys. Each name links to its code.

\n

Utilities

\n

git-status-dash

\n
\n\"git-status-dash\n
git-status-dash showing multiple repositories at once
\n
\n

git-status-dash shows the status of every repository in a folder at a glance — one terminal dashboard for all your work in progress. It's written in Go, with commands for config, themes, and status.

\n

GitHub Sloth

\n
\n\"The\n
The PR rollup logic in Rust — status glyphs and age coloring
\n
\n

GitHub Sloth is a minimalist amber-on-black terminal UI for GitHub PRs, reviews, and checks, written in Rust. It's designed to complement lazygit.

\n\n
\n\"tmux-link-grab\n
tmux-link-grab in action
\n
\n

tmux-link-grab grabs and opens the links scattered across your terminal panes. No mouse, no scrollback hunting.

\n

Music CLI

\n
\n\"The\n
The command reference — track management, a radio scheduler, and setup/watcher commands
\n
\n

Music CLI manages the audio that powers music.tools.ejfox.com and the radio — list, move, upload, convert, and tag tracks straight from the shell. Reads hit Cloudflare R2 directly; writes go through wrangler.

\n

Robots

\n
\n\"Robots\n
Robots running in a vulpes-themed terminal
\n
\n

Robots is a live cockpit for every Claude Code agent on the machine, written in Rust. It needs zero instrumentation and works retroactively on sessions that are already running.

\n

Input and display

\n

PS5 Tmux

\n
\n\"PS5\n
PS5 Tmux running in a vulpes-themed terminal
\n
\n

PS5 Tmux controls tmux with a PS5 DualSense controller. Move between panes with the controller, accept changes with the X button, or hit the middle button to enter dictation mode.

\n

Talon Sketchybar

\n
\n\"Talon\n
Talon Sketchybar running in a vulpes-themed terminal
\n
\n

Talon Sketchybar pushes Talon Voice state into sketchybar — event-driven, zero polling, about 60 lines of Python. It includes a Karabiner double-shift integration.

\n

showtouch

\n
\n\"showtouch\n
showtouch displaying a keystroke as full-screen centered ASCII art
\n
\n

showtouch shows every key you press as large ASCII art on screen, so an audience can follow along during presentations and livestreams. pynput captures the keys and pyfiglet renders them.

\n

ascii_webcam

\n
\n\"ascii_webcam\n
ascii_webcam turning a live scene into terminal ASCII
\n
\n

ascii_webcam shows your webcam as ASCII art in the terminal. It supports customizable cyberpunk 3D scenes, gradient palettes, and Floyd–Steinberg dithering.

\n

Games and toys

\n

CLI Ching

\n
\n\"cli-ching\n
cli-ching — the I Ching oracle in the terminal, with throw history and the coin-toss prompt
\n
\n

CLI Ching walks you through six coin tosses, builds your I Ching hexagram, and interprets the reading. It keeps a history of past throws.

\n

CLI Conway

\n
\n\"CLI\n
CLI Conway running in a vulpes-themed terminal
\n
\n

CLI Conway runs Conway's Game of Life in the terminal. The cells are drawn in braille unicode characters.

\n

CLI Delta Dojo

\n
\n\"CLI\n
CLI Delta Dojo title screen
\n
\n

CLI Delta Dojo is a terminal reflex game for training your eye to spot differences. Two values flash up and you call them Different or Same as fast as you can, against the clock.

\n

CLI Ascii 3D

\n
\n\"CLI\n
CLI Ascii 3D running in a vulpes-themed terminal
\n
\n

CLI Ascii 3D renders 3D shapes as ASCII art in the command line.

\n

CLI AI Chat

\n
\n\"CLI\n
CLI AI Chat running in a vulpes-themed terminal
\n
\n

CLI AI Chat is an IRC-style terminal interface for LLM conversations, in the same channel-and-buffer idiom as an IRC client. Vim-style modes and keybindings handle navigation between threads.

","metadata":{"title":"Terminal Tools","date":"2026-09-30T04:00:00.000Z","category":"Tools","featured":false,"draft":false,"tech":["Rust","Go","Python","Node.js","Shell","tmux"],"state":"deployed","ai-involvement":"ai-assisted","tags":["cli","terminal","tools"],"words":546,"images":14,"imageDetails":{"total":14,"cloudinary":14,"withDimensions":0},"links":14,"codeBlocks":0,"headers":{"h2":3},"toc":[{"text":"Utilities","slug":"utilities","level":"h2","children":[{"text":"git-status-dash","slug":"git-status-dash","level":"h3","children":[]},{"text":"GitHub Sloth","slug":"github-sloth","level":"h3","children":[]},{"text":"tmux-link-grab","slug":"tmux-link-grab","level":"h3","children":[]},{"text":"Music CLI","slug":"music-cli","level":"h3","children":[]},{"text":"Robots","slug":"robots","level":"h3","children":[]}]},{"text":"Input and display","slug":"input-and-display","level":"h2","children":[{"text":"PS5 Tmux","slug":"ps5-tmux","level":"h3","children":[]},{"text":"Talon Sketchybar","slug":"talon-sketchybar","level":"h3","children":[]},{"text":"showtouch","slug":"showtouch","level":"h3","children":[]},{"text":"ascii_webcam","slug":"ascii_webcam","level":"h3","children":[]}]},{"text":"Games and toys","slug":"games-and-toys","level":"h2","children":[{"text":"CLI Ching","slug":"cli-ching","level":"h3","children":[]},{"text":"CLI Conway","slug":"cli-conway","level":"h3","children":[]},{"text":"CLI Delta Dojo","slug":"cli-delta-dojo","level":"h3","children":[]},{"text":"CLI Ascii 3D","slug":"cli-ascii-3d","level":"h3","children":[]},{"text":"CLI AI Chat","slug":"cli-ai-chat","level":"h3","children":[]}]}],"type":"post"}},{"slug":"projects/amen-slicer","title":"Amen Slicer","html":"
\n\"Amen\n
Amen Slicer — running on the Game Boy Advance
\n
\n

A breakbeat slicer / performance instrument for the Game Boy Advance — 13 amen flavors, sync-locked clock, live stutters/FX/crush, and a reactive generative visualizer. Butano/C++

\n

I am SO stoked about this one. This is basically because I am getting my music table set up again — I have a Maschine+ and an FM synthesizer, and I just need a device that makes it easy to drop in, beat sync, and chop up amen breaks in time with the other music hardware.

\n

I made one for the Game Boy (Miyoo Mini, really) to experiment with making my own Game Boy game utilities — or really, shaping the Miyoo Mini into my own dream piece of hacker music gear.

\n

Plug in the Game Boy — the headphone port is a little janky but you can get it — then sync up the 1 from the Game Boy, pick a sample, chop it around while the other instruments happen.

\n

I also made a Rust macOS amen slice breaker app that works with the 64-pad grid controller over MIDI — amen-grid.

","metadata":{"title":"Amen Slicer","date":"2026-07-28T05:00:00.000Z","category":"Hardware","featured":false,"draft":false,"url":"https://github.com/ejfox/amen-slicer","tech":["C++","Makefile","Python"],"tags":["hardware"],"words":186,"images":1,"imageDetails":{"total":1,"cloudinary":1,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/badusb-remote-desktop","title":"BadUSB Remote Desktop","html":"
\n\"BadUSB\n
BadUSB Remote Desktop — a real DuckyScript payload in a vulpes terminal
\n
\n

Flipper Zero BadUSB payloads that make a fresh, keyboard-less machine reachable on the LAN for remote desktop — macOS Screen Sharing (VNC), Windows RDP, Linux VNC

\n

For setting up new computers, especially desktops and Raspberry Pis, with no keyboard, and getting them on a network where I can manage them from my MacBook.

\n

Just plug the Flipper in with USB-C and run the BadUSB scripts until it's connected.

","metadata":{"title":"BadUSB Remote Desktop","date":"2026-06-09T05:00:00.000Z","category":"Hardware","featured":false,"draft":false,"url":"https://github.com/ejfox/badusb-remote-desktop","tech":["Shell"],"tags":["badusb","duckyscript","flipper-zero","headless","linux"],"words":80,"images":1,"imageDetails":{"total":1,"cloudinary":1,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/pixel-canvas","title":"Pixel Canvas","html":"

I spend all day looking at screens that want something from me. Pixel Canvas is a screen that doesn't — a networked 320×240 display that sits on my desk and quietly shows me my own life in the Vulpes palette.

\n

It's an ESP32-S3-BOX-3B running a little Arduino REST API, driven by a bash CLI that rotates through \"scenes\" every fifteen minutes. Each scene is a tiny self-contained script that fetches from some corner of my data and draws it with primitives over HTTP — the weather, the last film I watched with my rating, the book I'm in the middle of, my best typing speed, a random card from the gear closet, a line from my journal.

\n
A day of the display's rotation, compressed — all fourteen scenes as the device cycles them
\n
\n\"Today's\n
Today's weather as a desk-display scene
\n
\n
\n\"The\n
The last film I watched, with my rating
\n
\n

The whole thing is the opposite of a notification feed. Nothing on it is urgent, nothing is trying to pull me back in. It's ambient — you glance at it the way you glance out a window, and mostly you just let it cycle in the corner of your eye while you work.

\n

That's the part I actually care about. I've been tracking myself for years across a dozen systems, and the usual pitch for all that data is optimization: quantify yourself, find the inefficiency, grind it down. I've never been interested in that. I wanted to turn the panopticon inward and just look — not \"how do I do more,\" but \"what does a day of mine actually look like when it's reflected back and I'm not the one narrating it?\"

\n
\n\"A\n
A random gear card
\n
\n
\n\"Best\n
Best WPM, pulled from my typing stats
\n
\n
\n\"The\n
The book I'm currently reading
\n
\n
\n\"Morning\n
Morning greeting
\n
\n

How it works

\n\n
\n\"A\n
A todo scene
\n
\n
\n\"Clock\"\n
Clock
\n
\n

By now there's a scene for nearly every corner of the archive — a random old tweet, a draft note yanked out of Obsidian, this week's intelligence-summary wiki page, the day's site analytics, a line of cipher text, and when there's genuinely nothing to say, a quiet field of ambient dots.

\n
\n\"A\n
A random tweet from the archive
\n
\n
\n\"Today's\n
Today's site analytics
\n
\n
\n\"A\n
A line of cipher text
\n
\n
\n\"Ambient\n
Ambient dots
\n
\n

The scenes I like best are the ones that catch me off guard — a tweet from a version of me I'd half-forgotten, a book I keep meaning to finish. A small calm machine for remembering there's a life on this side of the screen too.

","metadata":{"title":"Pixel Canvas","date":"2026-05-27T04:00:00.000Z","category":"Hardware","featured":true,"draft":false,"tech":["ESP32-S3","Arduino","LovyanGFX","Bash","REST API"],"state":"doing","ai-involvement":"ai-assisted","tags":["hardware","device","dataviz","quantified-self"],"words":530,"images":13,"imageDetails":{"total":13,"cloudinary":13,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"How it works","slug":"how-it-works","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/scrapbook-core","title":"Scrapbook Core","html":"

I have gotten pretty good at saving interesting things that I see on the internet. Anytime I read something I think I might want to reference, show someone, or think about later, I chuck it into my bookmarks. I've done this for over 10 years now, making little notes of my favorite things while wading through the ever-expanding deluge of \"content.\" Now I want to take a step back and map the constellations that emerge.

\n
\n\"A\n
A phyllotaxis of the scrap corpus — every screenshot placed by the golden angle, the way a sunflower packs its seeds
\n
\n

All of these things — mastodon posts, pinboard bookmarks, github activity, are.na blocks — can be thought of as various scraps of paper sitting on my desk, clipped out from some source material. But first I needed to reclaim my data from the various services in which they live. Scrapbook-core is that engine: a scraper for my Pinboard bookmarks, are.na blocks, public GitHub actions, and Mastodon posts, all coordinated in an index file that handles rate limiting, sequencing, and the CLI options, landing everything in one database — the substrate everything else (the CLI, the scrollers) reads from. Every bookmark gets fetched and summarized into a standalone list of facts, tagged, embedded for similarity searching and clustering, and mined for relationships — [Person:Stewart Brand] -[:CreatedBy]-> [Publication:Whole Earth Catalog] — that I can easily turn into nodes and edges with some lightweight regex parsing.

\n
Running the scraper
\n

Even though no one will likely be using this specific tool except for me, I will be practicing a bit of self care in the form of a well-crafted tool that I can find, and most importantly, figure out how to use months or years down the line. The ability to own, possess, remix, and re-explore my own data is crucial for me to make sense of the world. It's how I access my own thoughts, understand how I think about things, and to find creative paths forward and decide what is worth focusing on. If I gave up those responsibilities to a faceless algorithm whose goals are quite different from my own, I would be giving up quite a lot. You are what you eat.

\n

The full story: My Modern Scrapbook.

\n

The scrapbook family

\n

Scrapbook CLI

\n
\n\"The\n
The scrapbook CLI in action — browse bookmarks, full-text search, and an AI summary of each scrap
\n
\n

Scrapbook CLI is a command-line interface for exploring the scrapbook — browse bookmarks, run full-text search, and read an AI summary of each scrap without leaving the terminal. The interface is built from blessed widgets, including a mini-map.

\n

Scrapscroller

\n
\n\"scrapscroller\n
scrapscroller running: the SCRAP_ZONE feed with source/tag sidebar and stats
\n
\n

Scrapscroller turns the scraps into a scrolling feed, with a source and tag sidebar and running stats.

\n

Arena Cards

\n
\n\"Arena\n
Arena Cards — a real are.na channel laid out as draggable spatial cards
\n
\n

Arena Cards turns an are.na channel into draggable cards for spatial thinking. It was originally made for a YouTube video exploring the are.na API and taking control of your own data.

\n

Retroscope

\n
\n\"Retroscope\n
Retroscope running — config verification: Cloudinary initialized, all checks green, health server up
\n
\n

Retroscope uses an AI to generate text descriptions of every screenshot stored in Cloudinary.

\n

Photos

\n
\n\"A\n
A frame from the photo blog
\n
\n

Photos is the photo blog and the custom media-organizing and publishing app behind it. It's Nuxt and Cloudinary, fed by bash scripts and Apple Automator, for getting photographs from camera to web.

","metadata":{"title":"Scrapbook Core","date":"2026-05-05T05:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/scrapbook-core","tech":["JavaScript"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":581,"images":7,"imageDetails":{"total":7,"cloudinary":7,"withDimensions":0},"links":7,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"The scrapbook family","slug":"the-scrapbook-family","level":"h2","children":[{"text":"Scrapbook CLI","slug":"scrapbook-cli","level":"h3","children":[]},{"text":"Scrapscroller","slug":"scrapscroller","level":"h3","children":[]},{"text":"Arena Cards","slug":"arena-cards","level":"h3","children":[]},{"text":"Retroscope","slug":"retroscope","level":"h3","children":[]},{"text":"Photos","slug":"photos","level":"h3","children":[]}]}],"type":"post"}},{"slug":"projects/gem-viz","title":"Global Energy Ownership Tracker","html":"

Global Energy Monitor's Ownership Tracker is a giant network: thousands of owners — governments, corporations, private equity firms, and the intermediaries between them — connected to tens of thousands of energy-related assets around the world. It's a rich dataset that had been genuinely hard to explore, so we built a set of tools to open it up. You can trace the full ownership chain behind a single project (down to the stakes held by the likes of BlackRock and EDF), see the whole energy-asset portfolio connected to one owner, and screen owners by what they actually own — coal-based steel plants, proposed mines in BRICS countries, captive gas plants for data centers.

\n

It's built for the digging: investigating a corporation's clean-energy claims, following investment patterns, or tracing who ultimately owns a piece of the world's energy infrastructure. The ownership chain is where a lot of the truth is.

\n

My favorite part was working with Stephen and Nadieh, finding new visual ways to explore ownership patterns this intricate. It started as an ownership chart — Stephen prototyped the forms in Observable, I turned them into Svelte components, and Nadieh brought really cool interactions and visual forms on top. That's how you get things like the ownership \"flowers\" that open an owner's whole portfolio at once, instead of another org chart.

\n

Built with Stephen Osserman and Anna Mowat at Global Energy Monitor, Third Bear Solutions on the data pipeline, and Nadieh Bremer on vis design.

\n
\n\"The\n
The live tool — the whole Global Energy Monitor database, 50,223 assets across 194 countries
\n
\n
\n\"Owners\n
Owners of the Sines power station, traced live: the coal plant up through EDP to China Three Gorges (22.2%), BlackRock (8.4%), and the Vanguard Group — pie-nodes colored by headquarters country
\n
\n
\n\"The\n
The screener — pick an asset class (coal plants, captive gas plants for data centers, proposed mines in BRICS countries) and find exactly who owns it
\n
\n
\n\"Ownership\n
Ownership network for the Sines power station
\n
\n
\n\"Every\n
Every energy asset in the Global Energy Monitor database, mapped
\n
\n
\n\"Tracing\n
Tracing a power station up to Bank of America
\n
\n
\n\"An\n
An asset's corporate ownership graph
\n
\n
\n\"Drilling\n
Drilling into the owners of a binational pipeline
\n
","metadata":{"title":"Global Energy Ownership Tracker","date":"2026-05-01T04:00:00.000Z","category":"Dataviz","featured":true,"tech":["D3.js","Network Analysis","Data Visualization"],"state":"deployed","ai-involvement":"ai-assisted","context":"client","url":"https://globalenergymonitor.org/projects/global-energy-ownership-tracker","tags":["dataviz","network","energy","climate"],"words":354,"images":8,"imageDetails":{"total":8,"cloudinary":6,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/motorcycle-viz","title":"Motorcycle Meta-Visualizations","html":"

I started filming my rides in case something went wrong. A helmet cam is insurance — if an accident or something crazy happened, at least there'd be a tape. But over a few years the reason quietly changed on me. I'd flip it on for the beautiful stuff instead: a good stretch of road, the light, whatever cool thing was happening. One time I caught a train and a helicopter lining up over the Hudson River exactly as I rode past.

\n

By the end of those first few years I had gigabytes and gigabytes of it, and I got curious what all of it looked like at once — what years of riding might add up to. So I ran the whole corpus through a battery of meta-visualization techniques, pulling images out of the footage that no single frame holds.

\n
Scrolling the helmet-cam corpus explorer — 294 rides, the frame contact sheet, and GPS route maps
\n
\n\"Every\n
Every frame from 3.5 years of riding — 294 clips, 78 rides — averaged into a single image
\n
\n

Frame averaging (after Jason Salavon) stacks thousands of frames into one — the constants of riding (road below, sky above, the fairing) resolve into a soft ghost while everything transient blurs away. Run it per year and you can watch the ghost shift as the routes and seasons change:

\n
\n\"The\n
The average of every 2024 frame
\n
\n

Slit-scan takes a single column from every frame and lays them side by side, turning a whole ride into a striated band of color and light — both horizontally and vertically.

\n
\n\"Slit-scan:\n
Slit-scan: one column per frame, a whole ride compressed into a band
\n
\n
\n\"Vertical\n
Vertical slit-scan variant
\n
\n
\n\"Dusk\n
Dusk gradient — the color of the light, averaged across the golden-hour rides
\n
\n

Cinema redux shrinks every frame to a tile and tiles them into a single mosaic — the entire footage archive as one dense image, a barcode of where I've been.

\n
\n\"Cinema\n
Cinema redux — every frame as a tile, the whole archive in one mosaic
\n
\n
\n\"Cinema\n
Cinema redux, frame variant — a denser grid
\n
\n
\n\"A\n
A contact-grid of frames pulled from the rides
\n
\n
\n\"Dusk\n
Dusk anthology — a tall contact sheet of golden-hour frames
\n
\n

So what did it all add up to? Honestly, not much you could point at. The specific moments I'd gone looking for — the train and the helicopter, the good light — washed out in the averaging. What was left was just the general shape and colors of the Hudson Valley and its roads. Unremarkable, but with a kind of haunting beauty to it. A consistency.

\n

The real blessing turned out to be in what isn't there. Across all of it — every gig of footage, every year — no accident, nothing terrible ever happened. The insurance I started rolling never had to pay out. That's the thing the average quietly confirms.

\n

Mapping the rides

\n
\n\"A\n
A 56-mile Hudson Valley loop mapped from a Garmin file
\n
\n

Moto GPX dumps a folder of GPX tracks into map-ready GeoJSON split by day, hour, or stage, and can merge photos and videos in via exiftool. It also generates elevation and speed profiles, with the day's peak and top-speed moment marked.

","metadata":{"title":"Motorcycle Meta-Visualizations","date":"2026-05-01T04:00:00.000Z","featured":true,"category":"Art","url":"https://github.com/ejfox/motorcycle-viz","tech":["FFmpeg","Python","Generative Art","Data Visualization"],"state":"doing","ai-involvement":"ai-assisted","tags":["motorcycle","dataviz","generative","art","video"],"words":525,"images":11,"imageDetails":{"total":11,"cloudinary":11,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"Mapping the rides","slug":"mapping-the-rides","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/subway-builder","title":"Subway Builder","html":"

The mission, as I see it: hyperstitioning public transit into every American city. Subway Builder is a game created by Colin Miller, a member of Room 302 Studio, in 2025 — a sort of Ender's Game for transit, using realistic simulations to let train-people SHOW their elected leaders what is and is not possible.

\n

The game itself: a transit simulation (an Electron build) — design train types with realistic acceleration, capacity, and cost parameters, lay networks over real-world geography, and analyze the demand you create. It launched on Steam in July 2026. My corner of it: code contributions, Steam release infrastructure, and spin-offs like subway-builder-mods and a Pico-8 demake.

\n

It's also a success story for Room 302 Studio — Colin grew from a studio member to having the studio support his effort, and I wanna do that for more people and their dream apps and games.

\n
\n\"Subway\n
Subway Builder construction mode — laying track in an isometric city
\n
\n
\n\"A\n
A subway network laid over real geography
\n
\n
\n\"Train-type\n
Train-type editor with full simulation parameters
\n
\n
\n\"A\n
A 3D transit map — blue rail lines and teal stations across a metropolitan area
\n
\n
\n\"A\n
A Manhattan line running in simulation — stations and real-time train arrivals
\n
\n
\n\"Elevated\n
Elevated parallel tracks from Vernon Ave to Bleecker St — $538M of imaginary money
\n
\n
\n\"Generating\n
Generating train service across the NYC network
\n
\n
\n\"The\n
The construction panel — track and station options with live cost estimates
\n
\n
\n\"Achievements:\n
Achievements: 2 of 9 unlocked — Track Builder and First Station
\n
\n
\n\"The\n
The transit-operations event log — the simulation keeps receipts
\n
\n

Metro Savefile Doctor

\n
\n\"Metro\n
Metro Savefile Doctor — current game analysis
\n
\n

Metro Savefile Doctor is a TUI (and cross-platform Tauri desktop app) for editing Subway Builder save files, in both JSON and .metro binary formats, with auto-backup. It edits money, game time, train count, and ticket price through an interactive terminal interface with a crackintro aesthetic.

","metadata":{"title":"Subway Builder","date":"2026-05-01T04:00:00.000Z","category":"Games","featured":true,"url":"https://github.com/ejfox/subway-builder-mods","tech":["JavaScript","Simulation","Transit","Game Modding"],"state":"evolved","ai-involvement":"ai-assisted","tags":["games","simulation","transit","dataviz"],"words":306,"images":11,"imageDetails":{"total":11,"cloudinary":11,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"Metro Savefile Doctor","slug":"metro-savefile-doctor","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/tv-station","title":"TV Station","html":"

On-demand broke the one good thing about cable: everybody watching the same thing at the same second — no pausing, nobody skipping ahead, no algorithm picking for you. So I built my own channel. Everyone who tunes in to tv.tools.ejfox.com lands on the exact same frame, because the playhead is computed deterministically from a fixed epoch and the running sum of every video's duration. No database, no per-client state to keep in sync — just a single-file Deno app on smallweb. There's a live \"N other viewers\" counter too, so you can feel whether it's just you or a whole room.

\n

The room I built it for is a little Discord community — people learning things together. Everyone can tune in and out and comment on what's happening at the same time, even though underneath it's just a playlist looping.

\n
The station mid-loop — everyone watching the same frame of the 224-hour broadcast
\n

What's actually playing is my own YouTube \"Watch Later\" list — 507 saved links, enriched down to the 475 that are still alive, about 224 hours of runtime looping around. So tuning in is really watching over my shoulder through the backlog I never got around to. It's a whole cable channel, and it's also just... my saved videos.

\n
\n\"The\n
The TV station landing — tuned to the channel
\n
\n
\n\"tv.tools.ejfox.com\n
tv.tools.ejfox.com live
\n
\n

I also wrote up a Pi 5 kiosk recipe so it runs full-screen on the wall TV — an actual television, tuned to my channel.

\n

The whole thing is open source, and the point is that it's yours, not mine. It's one ~140-line Deno file plus a small Python recipe that eats a Watch Later export, an Obsidian or Notion vault, or a plain CSV and builds the playlist for you. Point it at your own backlog, drop it on smallweb behind any reverse proxy, and you've got your own public-access channel in an afternoon.

","metadata":{"title":"TV Station","date":"2026-05-01T04:00:00.000Z","category":"Art","featured":false,"url":"https://tv.tools.ejfox.com","tech":["TypeScript","Deno","Smallweb"],"state":"deployed","ai-involvement":"ai-assisted","tags":["web","experiment"],"words":318,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/github-sloth","title":"GitHub Sloth","html":"\n

A minimalist amber-on-black terminal UI for GitHub PRs, reviews, and checks, written in Rust. It is designed to be complementary to lazygit.

\n

I wanted my own top-level minimalist view of all of my open work — most of my work collaborations happen through GitHub. It's part of a process of redesigning all of my tools and daily interfaces to the world with an eye towards exactly what I need and what serves me.

\n

I've been having a lot of fun lately writing minimalist TUIs I can run in tmux panes — my workspace lately is often just a full-screen terminal with different tmux panes and windows, and I really like it when the interface is just text. It lets me think about the functionality and core offerings rather than diving into padding and spacing and layout the way I do in CSS and front-end.

\n
\n\"The\n
The PR rollup logic in Rust — status glyphs and age coloring
\n
\n
\n\"The\n
The TUI rendering — ratatui layout and styled spans for the PR list
\n
","metadata":{"title":"GitHub Sloth","date":"2026-05-01T00:00:00.000Z","category":"Tools","featured":false,"draft":false,"url":"https://github.com/ejfox/github-sloth","tech":["Rust"],"state":"deployed","ai-involvement":"ai-assisted","tags":["cli","terminal","git"],"words":180,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/clipgoblin","title":"clipgoblin","html":"
\n\"Clipgoblin\n
Clipgoblin running in a vulpes-themed terminal
\n
\n

clipgoblin came out of a real editing problem. I was buried in a corpus of long recorded talks and lectures — hours of it — that I needed to actually navigate for a research project, and scrubbing Final Cut timelines to find the one moment someone said the thing was breaking me. So I built a tool that reads the transcript and drops a marker at every concept-relevant moment straight into the Final Cut timeline. Now I move through hours of footage by hitting Ctrl+' instead of scrubbing.

\n
\n\"The\n
The CLI — generating concept-tagged FCPXML markers from a words.json transcript
\n
\n

Under the hood it shells out to Whisper for word-level transcription, then generates concept-tagged FCPXML markers from the resulting words.json — so each marker lands on the exact word, not a rough guess.

\n
\n\"Resolving\n
Resolving and shelling out to whisper for word-level transcription
\n
\n

Related video tools

\n

Sentry Search

\n
\n\"sentrysearch\n
sentrysearch CLI help output listing the index, search, img, highlights, shell, and stats commands
\n
\n

Sentry Search is semantic search over video footage: type a query and get back the matching trimmed clip, instead of scrubbing hours of timeline. Its CLI covers indexing, search, image search, highlights, and stats.

\n

Transcript Video

\n
\n\"Synced\n
Synced transcript with concept color-tagging — a word appears in Archivo Black timed to speech, with tagged terms highlighted and a QR provenance code
\n
\n

Transcript Video generates 1080p synced transcript videos from audio, with word-level timing and concept color-tagging. It includes audio-reactive visualizations: a spectrogram, oscilloscopes, and a Lissajous phase scope.

","metadata":{"title":"clipgoblin","date":"2026-04-29T05:00:00.000Z","category":"Tools","featured":false,"tech":["Swift"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":256,"images":5,"imageDetails":{"total":5,"cloudinary":5,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"Related video tools","slug":"related-video-tools","level":"h2","children":[{"text":"Sentry Search","slug":"sentry-search","level":"h3","children":[]},{"text":"Transcript Video","slug":"transcript-video","level":"h3","children":[]}]}],"type":"post"}},{"slug":"projects/cyberdeck-saver","title":"cyberdeck-saver","html":"

Most cyberpunk desktops are set dressing — fake terminals scrolling gibberish for the vibe. This one is real. cyberdeck-saver is a native macOS screensaver, written in Swift and Metal, that turns your idle screen into an actual command center: a 5×5 grid of 25 terminal panels, each typing itself out with live data and post-processed through a CRT shader chain in the vulpes palette.

\n

The rule behind it is one line from the README — no fake data; every byte on screen comes from a real API or a system call. So the panels are wired to things that are actually happening: aircraft crossing the airspace over the Hudson Valley on live ADS-B, earthquakes above magnitude 2.5 in the last day, the planetary K-index off NOAA's space-weather feed, the ISS's current distance from wherever you're sitting. Next to those runs your own telemetry — Apple Health, system thermals, GitHub commits, chess ratings, what's playing on Last.fm — and your scrapbook's extracted knowledge, down to the claim-triples and the entities trending across your last fifty saves.

\n
\n\"The\n
The data streams — each terminal panel fetches and parses its own feed; here, haversine math for scrapbook distances
\n
\n

Every panel is config-driven, the grid auto-scales to however many you switch on, and they share a single process-wide cache so twenty-five live feeds never hammer a source.

\n
\n\"The\n
The Metal fragment shader behind the screensaver's CRT look
\n
","metadata":{"title":"cyberdeck-saver","date":"2026-04-20T04:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/cyberdeck-saver","tech":["Swift","Metal","macOS","OSINT"],"state":"deployed","ai-involvement":"ai-assisted","tags":["macos","osint","design"],"words":231,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/tempo","title":"Tempo","html":"

A brutalist Pomodoro timer for iPhone and Apple Watch — edge-trace progress around the screen and adaptive themes

\n

I wanted a Pomodoro that showed a unit chart and had a great visual look — something to include in YouTube videos and show my friends, like a designer watch. Elegant, Swiss-feeling, smooth advancing, with some social features like rings.

\n

Next, I'd love to automatically ping a robot or my VPS when a Pomo session ends, or track it in my Grafana with a quantified-self vibe, or ping my Hue lights to do a little dance.

\n

I've used Tempo a fair bit, and some folks from The Vestibule have been beta testing it for me on TestFlight too.

\n
\n\"Tempo\n
Tempo on iPhone
\n
\n
\n\"Tempo\n
Tempo session view
\n
","metadata":{"title":"Tempo","date":"2026-04-01T04:00:00.000Z","category":"Apps","featured":false,"draft":false,"tech":["Swift","SwiftUI","iOS","watchOS"],"state":"deployed","ai-involvement":"ai-assisted","tags":["ios","app","design"],"words":122,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/vulpes-devices","title":"Vulpes Devices","html":"

The hardware arm of the Vulpes look — one palette, one glyph, generated out to seven device targets: Flipper Zero, OnionOS handhelds, the TD-H3 radio, Meshtastic nodes, a PortaPack, plus iPhone and iMac wallpapers. It takes the cyberpunk-neon Vulpes scheme from my editor and pushes it down onto the little screens, so my devices boot and theme in the same visual language as everything else I make.

\n
\n\"One\n
One look, many targets — the Vulpes glyph and palette generated across Flipper, OnionOS, TD-H3, Meshtastic, PortaPack, and the desktop
\n
\n

Everything derives from a single shared palette file — the same #e60067 magenta and #6eedf7 teal that run through the rest of the Vulpes system — so a new device target is mostly a matter of teaching the generator that platform's theme format. The scheme itself is open: it grew out of vulpes.nvim, and vulpes-theme-lab is a live builder for spinning up your own variant.

\n
\n\"The\n
The Flipper Zero boot animation, generated straight from the palette — the fox, on a 128×64 monochrome screen
\n
","metadata":{"title":"Vulpes Devices","date":"2026-03-15T04:00:00.000Z","category":"Hardware","featured":false,"tech":["Flipper Zero","OnionOS","Theming","JavaScript"],"state":"deployed","ai-involvement":"ai-assisted","tags":["vulpes","flipper","hardware","device","design"],"words":170,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/connectology","title":"Connectology","html":"

Connectology is for me — a custom front-end replacement for Gephi or a raw D3 force layout: build graphs of nodes and links, then analyze the resulting structure with force-directed layout and graph metrics. The v2 rebuild adds AI-powered node generation and multiple import formats (Obsidian, Mermaid, CSV).

\n

Here's the kind of thing it's for. The other day I had a pretty cool idea — I figured I'd put 60 minutes on the clock and give it a shot. I wanted the robot to read all of the articles and bookmarks I've made in the past 10 years — there's over 3,000 of them — and make a huge knowledge graph of the connections between all of the entities in everything I've ever read. I built a little scraper that extracts relationships from the text of an article, and made a huge database of nodes and edges: who influences who, who is associated with who, what movements and philosophies and schools of thought different people come from. That's not always explicitly stated in the text you're reading — it's part of critical thinking, keeping in your mind what a source's worldview is — and this is an attempt at capturing that in data. Then I wanted to actually see them, so I pulled the table into Connectology. It didn't yet have a CSV import, so I had to build one real quick, and then there it was: 600 nodes of my mental model as a big network on the screen. You can imagine sending the robot a couple degrees of that network to inform its responses. But I just wanted to see a cool graph, I'm going to be honest, and I did it in an hour.

\n

That session is on YouTube: Turning My Bookmarks Into A Knowledge Graph.

\n
The force layout re-distributing a funding network — scatter, settle, repeat
\n
\n\"The\n
The editor: force controls, WebGL rendering, and a network of nodes mid-layout
\n
\n
\n\"Your\n
Your networks — the home shelf with live previews of each graph
\n
","metadata":{"title":"Connectology","date":"2026-03-01T00:00:00.000Z","category":"Dataviz","featured":false,"url":"https://connectology.room302.studio/","tech":["Nuxt 3","Vue 3","D3","graphology","SQLite","Clerk"],"state":"deployed","ai-involvement":"ai-assisted","context":"collaborative","tags":["dataviz","network","web"],"about":"[[project-notes/connectology]]","words":334,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/coachartie-memory","title":"Coach Artie — Memory Analysis","html":"\n

What does an AI agent actually remember? Coach Artie has been accumulating memory for as long as he's been running, so I embedded all of it, clustered it, and drew the map.

\n

I expected noise. What came back was sorted — clean clusters, things filed where they belonged, distinctions I never asked him to make.

\n

Reading it was the strange part. The clusters kept surfacing episodes I'd completely forgotten about, sitting right there where he'd put them. He really was listening the whole time, and thinking about what was said.

\n
\n\"Cognitive\n
Cognitive topology — Coach Artie's memories embedded and laid out as a map
\n
\n
\n\"Hierarchical\n
Hierarchical clustering of the memory space, as a dendrogram
\n
\n
\n\"t-SNE\n
t-SNE small multiples across the memory clusters
\n
\n

Beyond the static map, the analysis tracks how the memory changes — which clusters grow, when memories form, and how the topology shifts over time.

\n
\n\"Temporal\n
Temporal cluster evolution — how the memory grows and shifts
\n
\n
\n\"Cognitive\n
Cognitive activity calendar — daily memory-formation patterns
\n
\n
\n\"Qualitative\n
Qualitative cluster heatmap
\n
","metadata":{"title":"Coach Artie — Memory Analysis","date":"2026-02-01T05:00:00.000Z","category":"Dataviz","featured":false,"tech":["Python","t-SNE","HDBSCAN","Embeddings","Data Visualization"],"state":"doing","ai-involvement":"ai-collaborative","context":"collaborative","tags":["dataviz","data","ai","embeddings"],"words":178,"images":6,"imageDetails":{"total":6,"cloudinary":6,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/vulpes-browser","title":"Vulpes Browser","html":"

Minimalist web browser. Zig + Swift + Metal — rendered entirely on the GPU, with particle effects, link glow, and a two-pass bloom.

\n

I really wanted to experiment with creating a browser but making every choice myself, centered around how I use and consume the internet — from first principles, aided by a super-intelligent robot. What would a new browser made today, with speed and performance as a central tenet, look like?

\n

Zig, Swift, Metal: barebones, non-web, performant, and they interest me.

\n
\n\"The\n
The vulpes browser rendering ejfox.com
\n
\n
\n\"The\n
The Metal render pipeline — solid, glyph, particle, glow, and a two-pass bloom
\n
\n
\n\"The\n
The GPU image atlas — texture packing, zero-copy Metal textures, and an LRU cache for fast image rendering
\n
","metadata":{"title":"Vulpes Browser","date":"2026-01-20T05:00:00.000Z","category":"Tools","featured":false,"draft":false,"url":"https://github.com/ejfox/vulpes-browser","tech":["Swift"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":118,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/vulpes-nvim","title":"vulpes.nvim","html":"

A cyberpunk neon colorscheme for Neovim — signature vulpes pink, teal comments, dark and light variants, and monthly color rotations. Ships with matching themes for the rest of the terminal: wezterm, kitty, ghostty, alacritty, tmux, lazygit, bat, and fzf. It's the seed of the whole Vulpes look.

\n
\n\"The\n
The vulpes colorscheme rendering its own palette file in Neovim
\n
\n
\n\"The\n
The vulpes palette across a full terminal — waveforms, logs, and the fox mark
\n
\n
\n\"vulpes.nvim\n
vulpes.nvim editing its own source in Neovim
\n
","metadata":{"title":"vulpes.nvim","date":"2026-01-18T05:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/vulpes.nvim","tech":["Lua"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":78,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/vulpes-system","title":"Vulpes","html":"

I believe that if I spend so much time looking at and thinking about my computer, I want to have full control over the fonts and colors I look at — to make it cinematic, aesthetic, \"me,\" and different. And it's so dope that when I go to coffee shops (true story), people stop me and say \"that setup looks sick, can I give you my card in case I need a dev?\"

\n

Vulpes is what that belief turns into when you follow it all the way down. One palette — #e60067 magenta, #6eedf7 teal, near-black — and one fox glyph, pushed through every surface I touch: the editor, the terminal, the browser, the screensaver, and the little screens on the hardware in my bag. Each piece is a working tool. Together they're one look.

\n
\n\"The\n
The vulpes palette across a full terminal — waveforms, logs, and the fox mark
\n
\n

The editor

\n

It started with vulpes.nvim: a cyberpunk neon colorscheme for Neovim — signature vulpes pink, teal comments, dark and light variants, and monthly color rotations. It ships matching themes for the rest of the terminal: wezterm, kitty, ghostty, alacritty, tmux, lazygit, bat, and fzf.

\n
\n\"The\n
The vulpes colorscheme rendering its own palette file in Neovim
\n
\n

Vulpes Theme Lab is the live builder for it: tweak a base hue and a ±7° offset and watch nvim, lazygit, htop, and tmux recolor in real time.

\n
\n\"The\n
The theme lab — palette controls on the left, live nvim / lazygit / htop / tmux previews recoloring as you tune
\n
\n

The devices

\n

Vulpes Devices carries the same palette file out to seven hardware targets — Flipper Zero, OnionOS handhelds, the TD-H3 radio, Meshtastic nodes, a PortaPack, plus iPhone and iMac wallpapers — so everything boots in the same visual language.

\n
\n\"One\n
One look, many targets — the Vulpes glyph and palette generated across Flipper, OnionOS, TD-H3, Meshtastic, PortaPack, and the desktop
\n
\n
\n\"The\n
The Flipper Zero boot animation, generated straight from the palette — the fox, on a 128×64 monochrome screen
\n
\n

The screen when I walk away

\n

cyberdeck-saver is a native macOS screensaver in Swift and Metal: a 5×5 grid of terminal panels typing out live data — ADS-B aircraft over the Hudson Valley, earthquakes, space weather, my own telemetry — through a CRT shader chain in the vulpes palette. No fake data; every byte comes from a real API or a system call.

\n
\n\"The\n
The Metal fragment shader behind the screensaver's CRT look
\n
\n

The rest of the kit

\n\n
\n\"The\n
The vulpes browser rendering ejfox.com
\n
","metadata":{"title":"Vulpes","date":"2026-01-18T05:00:00.000Z","category":"Art","featured":true,"url":"https://github.com/ejfox/vulpes.nvim","tech":["Lua","Swift","Metal","Rust","Zig","Tauri","Flipper Zero"],"state":"doing","ai-involvement":"ai-assisted","tags":["vulpes","design","aesthetic","tools","hardware"],"words":489,"images":7,"imageDetails":{"total":7,"cloudinary":7,"withDimensions":0},"links":5,"codeBlocks":0,"headers":{"h2":4},"toc":[{"text":"The editor","slug":"the-editor","level":"h2","children":[]},{"text":"The devices","slug":"the-devices","level":"h2","children":[]},{"text":"The screen when I walk away","slug":"the-screen-when-i-walk-away","level":"h2","children":[]},{"text":"The rest of the kit","slug":"the-rest-of-the-kit","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/vulpino","title":"Vulpino","html":"

Any JSON endpoint into a home-screen iOS widget, no code, in about a minute

\n

I have data scattered across a dozen endpoints — analytics, servers, side projects, my own life. Vulpino is the fox that eats all of it and puts one clean number on my home screen. You paste a URL, it fetches the JSON and shows you the whole tree, you tap the values you care about, you pick a template, and you're done. Five taps: URL, data, template, customize, deploy. The whole thing is native SwiftUI and it works at all three widget sizes.

\n

The part I care most about is what it doesn't let you do. There's no font picker, no color wheel, no padding slider. You get seven typographic templates — Mono Stat for a single hero number, Dual Stat to compare two, Stat Stack for a little dashboard, plus Headline, List, Grid, and Timestamp — and every one of them is already designed. That's the whole idea behind the vulpes family: the constraint is the product. Vulpino says no to customization theater, and the widgets look good because I made the decisions instead of pushing them onto you at 11pm when you just want to see your visitor count.

\n

It's real infrastructure too. API keys and auth headers live in the Keychain, not in some plist. Data is cached offline so the widget still shows the last good value with a stale indicator when the network's down, and tapping a widget deep-links straight into whatever URL you set or back into the app to edit it. Built with a lot of AI pairing — I was the one saying no to features, the model helped me build the ones that survived.

\n
\n\"The\n
The widget editor — a SwiftUI step flow from URL to data to template to customize
\n
\n
\n\"The\n
The typographic design system behind the widgets — opinionated, minimal, restrained
\n
\n

Running on device: the widget list, pasting a live JSON endpoint, and the tree Vulpino builds from the response so you can tap the values you want.

\n
\n\"The\n
The app's home — your widgets live here; a new one is sixty seconds away
\n
\n
\n\"Paste\n
Paste any endpoint and Vulpino validates it live before it fetches
\n
\n
\n\"Vulpino\n
Vulpino fetches the JSON and lays the whole response out as a tree — tap the values you care about
\n
","metadata":{"title":"Vulpino","date":"2026-01-10T05:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/vulpino","tech":["Swift"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":387,"images":5,"imageDetails":{"total":5,"cloudinary":5,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/paperclip","title":"paperclip","html":"

No chat. Just vibes.

\n

paperclip is a friends-only presence app: you broadcast your vibe with a single emoji and that's the whole thing. There's no feed to scroll, no chat thread, no likes or follower counts or read receipts — none of the machinery that turns \"how are my friends doing\" into a job. You pick an emoji, your friends see it, and when theirs changes you can get a quiet notification. That's it. I wanted the ambient warmth of knowing what your people are feeling without any of the pressure to perform or respond.

\n

It's built native on both platforms — SwiftUI on iOS, Jetpack Compose on Android — over a shared Supabase backend that syncs in real time, so an emoji you set on your iPhone shows up on your friend's Android in seconds. It's monochrome on purpose: the only color on the screen is the emoji itself, which is exactly where I want your eye to go. Friends join by invite code, there's no public anything, and I built the boring-but-real parts too — push notifications with mute and quiet hours, block/report and account deletion for the App Store, a Cloudflare Worker proxy, even a Discord bot that mirrors your friends' emoji board into a server and Siri Shortcuts so you can set your vibe by voice.

\n

I built it with AI help (Claude), which is how one person ships two native apps and a backend at all — but the shape of it, the ruthless subtraction, the decision that the anti-social-network should feel like a piece of paper and not a dashboard, that's mine. Deliberately styled to lean Apple, not startup. Just pushing it steadily forward like a boss.

\n
\n\"paperclip\n
paperclip — one-emoji friends-only presence
\n
\n
\n\"A\n
A friend's contact card — pinned emoji, notifications, and a scrolling emoji history
\n
","metadata":{"title":"paperclip","date":"2025-11-01T05:00:00.000Z","category":"Apps","featured":false,"tech":["Swift","SwiftUI","Kotlin","Jetpack Compose","Supabase"],"state":"deployed","ai-involvement":"ai-assisted","tags":["ios","android","app","social"],"words":301,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/newswell","title":"Newswell Studio","html":"

A browser-based newspaper layout tool, built to take small newsrooms off InDesign. It has three parts: a WordPress plugin that stores issues, layouts and ads; a Nuxt web editor for laying out pages; and a Slack bot for checking issue status without leaving chat.

\n

In the editor, pages are built from drag-and-drop frames on a six-column newspaper grid. Articles come straight in from WordPress, ads are placed from inventory, and text flow is simulated so you can see what fits before you print. GPT-4 suggests headlines and trims articles to fit their frames. Finished pages export to print-ready PDF from the browser, with a preflight check first. Times of San Diego is the test site.

\n
\n\"Newswell\n
Newswell Studio — drag-drop frame layout on the six-column grid
\n
\n
\n\"Article\n
Article trimming and page export
\n
","metadata":{"title":"Newswell Studio","date":"2025-10-01T00:00:00.000Z","category":"Tools","featured":false,"draft":false,"tech":["Nuxt 4","Vue","WordPress","PHP","GPT-4"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools","journalism","dataviz"],"words":130,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/paramilitary-leaks","title":"Paramilitary Leaks","html":"

I was perusing Mastodon, as one does, and noticed a post from journalist Micah Lee saying he was exploring a 200GB dump from American paramilitary groups — a leak made possible through the incredible bravery of John Williams, who infiltrated these groups and exfiltrated the data. I hadn't heard of the dump before, and immediately sent Micah an email offering to help with any dataviz.

\n
\n\"The\n
The leak explorer — search + a dense visual index of the document set
\n
\n

The pipeline chops and screws the data from Telegram HTML exports into SQLite, then Parquet hosted on Cloudflare R2 — a columnar format that's super-fast in the browser. On top of that sits a Nuxt + regl-scatterplot frontend with full-text search, filters, and a dense visual index of the corpus. We took a 200GB leak and turned it into something a reporter can explore in the browser.

\n
Full-text search across the corpus
\n

Explore it at para-leaks.ejfox.com, read the full write-up — Processing Telegram Leaks for Fast Web Visualization — or watch the walkthrough: Visualizing 200GB Of Leaked Telegram Chats.

","metadata":{"title":"Paramilitary Leaks","date":"2025-09-01T04:00:00.000Z","category":"Journalism","featured":true,"tech":["Nuxt","Vue","Search","Data Visualization"],"state":"deployed","ai-involvement":"ai-assisted","context":"collaborative","tags":["journalism","data","osint","tools"],"words":178,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":6,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/openrouter-census","title":"OpenRouter Census","html":"

A full census of every model on OpenRouter, dumped into immutable JSONL/Parquet snapshots and rendered as an Observable Plot dashboard

\n

OpenRouter is the marketplace where you can hit basically any language model through one API, and the roster changes constantly — models appear, prices drift, a provider quietly bumps a context window. I wanted a way to take a dated snapshot of the whole thing and actually look at it, so I built a scraper that pulls all 316 models across 54 providers in about a second and hands me analysis-ready data I can chart.

\n

The interesting part is what falls out once you have every model in one table. Median context length is 128K tokens but the average is 171K, dragged up by outliers like OpenAI's million-plus-token windows. 70% of the catalog is still text-only; the other 30% takes images. And the capability spread is uneven in ways the marketing never tells you — max_tokens is table stakes at 99.7%, but tool calling only shows up on about half the models, structured outputs on 45%, and reasoning tokens on 29%. That's the kind of thing you want to know before you pick a model to build on.

\n

I care about provenance more than a leaderboard, so every run writes a dated artifacts/ directory: raw unmodified API payloads next to the normalized tables, JSON Schemas, SHA-256 checksums, fetch metadata, and a CITATION.cff — so a snapshot is something you can actually cite and reproduce, not a screenshot that rots. There's an interactive TUI for browsing and filtering, and the dashboard is seven Observable Plot charts over the processed data.

\n
\n\"OpenRouter\n
OpenRouter Model Census — the dashboard: pricing distribution + the context-price paradox
\n
\n
\n\"The\n
The companion interactive CLI
\n
","metadata":{"title":"OpenRouter Census","date":"2025-08-21T05:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/openrouter-census","tech":["JavaScript"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":285,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/smallbot-mcp","title":"Smallbot MCP","html":"

Smallweb is a unique tool to create a filesystem based system for rapidly-deployed deno apps, and it pairs really well with a robot companion.

\n

Nowadays when I have an idea for a website I just want it to exist, without spending three hours setting up a build pipeline and configuring DNS. Smallbot is an incredible tool to defeat that particular form of procrastination—a robot that takes \"make me a site about northeastern trees\" and actually builds the thing.

\n

I made a video with the creator of Smallweb about how easy it is to get set up, and I love how much the project embodies indieweb philosophies

\n

This is a tool built on the MCP (Model Context Protocol) so it can talk to Claude and other AI assistants and give them the tools and documentation to make little Smallweb sites easily, on-the-fly.

\n
\n\"Smallbot\n
Smallbot — a helpful assistant for creating Smallweb applications
\n
\n
\n\"Smallbot\n
Smallbot generating a Smallweb app
\n
\n

smallweb-starter

\n
\n\"The\n
The starter running locally — a live HTTP request returning JSON, with rate-limiting and cache-control headers from the Hono middleware
\n
\n

smallweb-starter is a lightweight application starter for Smallweb, in TypeScript on Deno. It ships Hono middleware for rate-limiting and cache-control headers.

","metadata":{"title":"Smallbot MCP","date":"2025-08-02T04:00:00.000Z","category":"Tools","featured":false,"modified":"2025-08-13T17:17:13.000Z","url":"https://github.com/ejfox/smallbot-mcp","tech":["MCP","AI","Web Generation","Node.js"],"state":"deployed","ai-involvement":"ai-enhanced","tags":["ai","web"],"words":198,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":5,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"smallweb-starter","slug":"smallweb-starter","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/towntuner","title":"towntuner","html":"

A single-purpose podcast app for exactly one podcast: Harmontown, all ~360 episodes

\n

For the past five or six years I've listened to Harmontown almost every single night. I went through it a few times on Spotify, then made my way through the archives on YouTube. And each night I kept getting annoyed: every podcast app I used was full of other podcasts I didn't care about, getting in the way of me listening to Harmontown. This was a problem that needed to be solved.

\n

A few weeks later I had a vibe-coded iOS app that Apple somehow approved for TestFlight. It's a little piece of software made with love, mostly just for myself, but I figured if anyone else would find it useful it would be the Harmontown people — so I posted it to r/Harmontown on New Year's Day.

\n
\n\"towntuner\n
towntuner — a Harmontown-only podcast player
\n
\n

What it does

\n\n

It builds on the amazing work of HarmonSearch, whose transcripts power both the transcript view and search.

\n
\n\"towntuner\n
towntuner on iPhone — the episode browser with prestige progression
\n
\n

Join the TestFlight beta — iOS only, sorry.

","metadata":{"title":"towntuner","date":"2025-08-01T04:00:00.000Z","category":"Apps","featured":false,"draft":false,"url":"https://github.com/ejfox/towntuner","tech":["Swift","SwiftUI","iOS"],"state":"deployed","ai-involvement":"ai-collaborative","tags":["ios","app","audio"],"words":222,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":3,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"What it does","slug":"what-it-does","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/websdr-vcv","title":"WebSDR VCV","html":"

A VCV Rack / Cardinal plugin — a C++ Eurorack module — that streams real radio from KiwiSDR servers into a modular synth

\n

I was kind of just doing recordings of WebSDR and integrating them into my music. But I love the organic, generative method of modular synthesis, and incorporating some real-life data — as my broken brain is prone to do — sparked a lot of joy for me. So: what if we controlled a synth from a live frequency turned into CV data? Unlocking hidden ambient music in the structures of unseen information floating all around us.

\n
\n\"The\n
The WebSDR module patched into a modular synth rack
\n
\n
\n\"The\n
The Eurorack module in C++ — presets and KiwiSDR resampling
\n
","metadata":{"title":"WebSDR VCV","date":"2025-08-01T00:00:00.000Z","category":"Hardware","featured":false,"url":"https://github.com/ejfox/websdr-vcv","tech":["C++","VCV Rack","Cardinal"],"state":"deployed","ai-involvement":"ai-assisted","tags":["audio","radio","hardware"],"words":118,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/noaa-sat-cli","title":"NOAA Satellite CLI","html":"
\n\"NOAA\n
NOAA Sat CLI running in a vulpes-themed terminal
\n
\n

The whole planet, from a satellite, on your hard drive, in one command

\n

I wanted the freshest picture of Earth without opening a browser, so I built a CLI that pulls straight from NOAA's GOES-18 and GOES-19 geostationary satellites — the two live birds parked over the Pacific and the Atlantic — and drops the image into a local archive. You can grab the latest GEOCOLOR frame, or reach for the max: a full disk of Earth at 21696x21696, 470 megapixels. It handles GOES' Julian-day timestamps (that YYYYJJJHHMM format that isn't a normal date), MD5-hashes every capture so it never stores the same frame twice, and keeps a little JSON database tracking what it's pulled and when. Point cron at it and you've got an hourly archive of the sky building itself.

\n

It's not just NOAA either. It'll pull NASA's EPIC camera — the one on DSCOVR, sitting a million and a half kilometers out at the L1 Lagrange point looking back at the whole sunlit face of Earth — plus MODIS and VIIRS regional imagery for the US, Europe, Asia, Africa, Australia. There's a quick grab one-liner for when you just want the shot, and a full ASCII terminal menu when you want to pick the satellite, channel, and resolution yourself. No emoji, all cyan-and-magenta status lines, the whole 90s-terminal thing on purpose.

\n
\n\"EARTH\n
EARTH OBSERVATION CLI — grab latest, mass capture, archive, and NASA deep-space views
\n
\n
\n\"The\n
The TUI behind the menu — satellite, channel, and resolution prompts
\n
","metadata":{"title":"NOAA Satellite CLI","date":"2025-06-09T05:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/noaa-sat-cli","tech":["TypeScript"],"state":"deployed","ai-involvement":"ai-assisted","tags":["tools"],"words":256,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/flipper-zero-tools","title":"Flipper Zero Tools","html":"

Two small apps for the same tiny, useless-but-perfect screen: flipper-space-calculators and flipper-generative-art.

\n

Space Calculators

\n

A set of minimalist space- and physics calculators for the Flipper Zero — relativistic time dilation, space-travel figuring, and friends, all on the 128×64 screen for back-of-the-napkin astrophysics in your pocket.

\n

I think I like it because it's so useless but still utilitarian — cyberpunk and gestural. It's a tool for a time/space-traveler who doesn't exist — or maybe does — the kind of thing he'd find handy.

\n

It's also an experiment in pushing what small Flipper apps can do, and imagining utilities that would make sense within its capabilities — using the limits as a method of inspiration. This is what came from that.

\n
\n\"The\n
The orbital-mechanics constants and transfer math, in C on the Flipper Zero
\n
\n
\n\"The\n
The transfer solver — delta-v, flight time, and a celestial-body database keyed by semi-major axis
\n
\n

Generative Art

\n

I often just leave the Flipper on my desk below my monitor, and my feeling was: why not have it show me little evolving art pieces instead of just the time? What would that look and feel like? Is generative art even possible within the constraints of the Flipper's screen and processor? What does 1-bit generative art feel like? How can it evolve over the course of a day?

\n

This is the answer: a Flipper Zero app that generates animated patterns in real time on the device's 128×64 monochrome screen. It runs ten gradient families — horizontal, vertical, radial, diagonal, sine waves, interference, checkerboard, noise, spiral — and converts each to crisp 1-bit graphics with Floyd–Steinberg dithering, evolving the parameters every second at ~30fps.

\n
\n\"More\n
More real-time generative patterns
\n
\n
\n\"Dithered\n
Dithered radial patterns generated on the Flipper Zero
\n
\n
\n\"Checkerboard\n
Checkerboard and noise fields
\n
\n
\n\"Interference\n
Interference and sine-wave fields, 1-bit dithered
\n
\n
\n\"Diagonal\n
Diagonal gradients and spirals
\n
\n

Making something genuinely generative look good in 1-bit on a tiny embedded display is the whole challenge — the dithering is what turns smooth math gradients into something the Flipper's screen can actually render without looking like mud.

","metadata":{"title":"Flipper Zero Tools","date":"2025-01-15T05:00:00.000Z","category":"Hardware","featured":true,"url":"https://github.com/ejfox/flipper-space-calculators","tech":["Flipper Zero","C","Embedded","Floyd–Steinberg Dithering"],"state":"deployed","ai-involvement":"ai-assisted","tags":["flipper","hardware","device","science","generative","art"],"words":338,"images":7,"imageDetails":{"total":7,"cloudinary":7,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{"h2":2},"toc":[{"text":"Space Calculators","slug":"space-calculators","level":"h2","children":[]},{"text":"Generative Art","slug":"generative-art","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/showtouch","title":"showtouch","html":"

For presentations and livestreaming: show every key you press as large ASCII art on screen, so an audience can follow along

\n

This was a fun \"can robots make TUIs?\" experiment. Answer: they can, and it's fun. The idea was to have it open in a tmux pane while I work — especially vim stuff, where people wanna know your shortcuts. The question got answered, and that was the point.

\n
\n\"How\n
How it works — pynput captures keys, pyfiglet renders them as centered ASCII art
\n
\n
\n\"showtouch\n
showtouch displaying a keystroke as full-screen centered ASCII art
\n
","metadata":{"title":"showtouch","date":"2024-10-01T04:00:00.000Z","category":"Tools","featured":false,"url":"https://github.com/ejfox/showtouch","tech":["Python","ASCII Art","Terminal"],"state":"prototype","ai-involvement":"ai-assisted","tags":["cli","terminal","programming"],"words":92,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/creative-interfaces","title":"Hand-Tracking & Generative Art","html":"

These are my attempts to make computers that respond to the way humans actually move and gesture.

\n

The other day I had this idea to try and control a modular synth using computer vision. I loaded YOLOv4 into a python script and had it detect objects in an episode of Atlanta I had lying around, sending the X and Y positions of every object as control voltage to the oscillators. It makes this weird, haunting, sort of robotic sound — but I kind of really like it. Then I had a fun idea to run it through the webcam, and I couldn't figure out why it wasn't working — I kept seeing the chair as an object. Then I figured it out: the chair is the instrument. Why did I make a chair an instrument? I don't know. I ended up running dance videos from Sherrie Silver, the This Is America choreographer, through it instead — not just the X and Y positions but the distances between the objects — and it comes up with some really cool, interesting generative effects. I don't really know how I use this right now, or what it's for exactly. That's kind of how I know it's art.

\n

That session: Using Computer Vision As A MIDI Controller.

\n

The other end of the spectrum: no camera, no screen at all. I've been using Talon to control my computer, so I tried to do the dishes and code at the same time — talking to Claude while my hands were in the sink, having it answer everything out loud. There are some sharp edges — a couple times it didn't pick up everything I said — but the fact that you can detach from looking at a screen and still engage in the mechanical task of writing code and making things with a computer is completely radical. It's unlike anything I've ever experienced in my life.

\n

That one's on video too: Coding While I Do The Dishes.

\n

See also Flipper Zero Tools and Terminal Tools.

\n

Hand-tracking & gesture

\n

Hand MIDI Controller

\n
\n\"Hand\n
Hand MIDI Controller — MediaPipe hand landmarks mapped to MIDI CC
\n
\n

Hand MIDI Controller is a real-time hand-tracking MIDI controller built on MediaPipe and OpenCV, turning hand movements into MIDI control signals for music production, VJing, and performance. It includes TouchDesigner integration.

\n

Handtrack WebSockets

\n

Handtrack WebSockets does real-time 3D hand tracking with MediaPipe, OpenCV, and FastAPI, streaming hand position and rotation over WebSockets. It includes a cyberpunk visualization layer that renders the tracked hand.

\n

OpenCV MIDI Controller

\n
\n\"OpenCV\n
OpenCV MIDI Controller — OpenCV object tracking driving MIDI CC
\n
\n

OpenCV MIDI Controller is an experiment in sending MIDI signals based on OpenCV object detection.

\n

Speech Echoes

\n
\n\"Live\n
Live speech rendered as decaying typographic echoes
\n
\n

Speech Echoes is a Vue app that captures live speech and renders it as decaying typographic \"echoes,\" with a font and weight captured per utterance. It's built with p5, MediaPipe, and d3-force.

\n

Glasses HUD

\n
\n\"The\n
The two lenses you compose a HUD across
\n
\n

Glasses HUD is a tool for quickly prototyping AR lens visualizations and HUDs. Drag data widgets onto the left and right lenses to compose a heads-up display from live bio, motion, location, environment, and device signals.

","metadata":{"title":"Hand-Tracking & Generative Art","date":"2024-07-01T04:00:00.000Z","category":"Art","featured":false,"modified":"2025-08-13T15:46:54.000Z","tech":["Computer Vision","MIDI","WebGL","Hand Tracking","Generative Art","Interactive Media"],"state":"deployed","ai-involvement":"ai-assisted","tags":["creativity","interfaces"],"words":540,"images":4,"imageDetails":{"total":4,"cloudinary":4,"withDimensions":0},"links":8,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"Hand-tracking & gesture","slug":"hand-tracking--gesture","level":"h2","children":[{"text":"Hand MIDI Controller","slug":"hand-midi-controller","level":"h3","children":[]},{"text":"Handtrack WebSockets","slug":"handtrack-websockets","level":"h3","children":[]},{"text":"OpenCV MIDI Controller","slug":"opencv-midi-controller","level":"h3","children":[]},{"text":"Speech Echoes","slug":"speech-echoes","level":"h3","children":[]},{"text":"Glasses HUD","slug":"glasses-hud","level":"h3","children":[]}]}],"type":"post"}},{"slug":"projects/obsidian-analysis","title":"Obsidian Analysis","html":"

I embedded my entire Obsidian vault — around 2,000 notes, chunked — using local Nomic embeddings running in LM Studio, so my private notes never leave my machine, and then I laid the whole thing out as a semantic map. Every note is a point, and points that sit close together are notes that are actually about the same thing. You search it in plain natural language, and you can recolor the map by semantics, recency, note size, or link density to see the vault from a different angle each time.

\n
\n\"~2,000\n
~2,000 notes embedded into a single semantic map — search and filter by SEMANTIC / TEMPORAL / SIZE / LINKS
\n
\n

The other half of this is the parameter grid. UMAP has a lot of knobs and the layout you get depends entirely on how you set them, so instead of guessing I ran 64 combinations of n_neighbors and min_dist at once and put them side by side. It turns \"which settings are right\" into something you can just look at — the same vault laid out 64 different ways, all on one screen.

\n
\n\"A\n
A 64-combination UMAP parameter grid — the same vault laid out 64 different ways
\n
\n

More semantic maps

\n

Criterion Embeddings

\n
\n\"Criterion\n
Criterion film embeddings explored as a 2D map
\n
\n

Criterion Embeddings computes vector embeddings for every Criterion Collection film and projects them into an explorable 2D map. You search by theme (\"films about existentialism\") instead of by keyword.

\n

r/dataisbeautiful, Embedded

\n
\n\"r/dataisbeautiful\n
r/dataisbeautiful embedded — 1,000 posts clustered into 50 thematic bubbles, sized by count
\n
\n

The top 1,000 posts from r/dataisbeautiful, each embedded with OpenAI and clustered into 50 themes, laid out as a map. The biggest clusters: US politics dataviz, COVID and mortality, Google search trends, climate, creative visualizations, and personal-finance charts.

\n

code-network-gen

\n
\n\"Real\n
Real output — every script in this site's content pipeline as a call-constellation (pink hub = file scope, teal = functions, edges = calls)
\n
\n

code-network-gen generates a node/edge graph from a JavaScript codebase by walking the AST with acorn and babel. It shows software architecture as an explorable network instead of a file tree — above, the scripts behind this site's own content pipeline.

","metadata":{"title":"Obsidian Analysis","date":"2024-06-01T04:00:00.000Z","category":"Dataviz","featured":false,"url":"https://github.com/ejfox/obsidian-analysis","tech":["Python","Embeddings","UMAP","LM Studio"],"state":"deployed","ai-involvement":"ai-collaborative","tags":["data","visualization","ai"],"words":362,"images":5,"imageDetails":{"total":5,"cloudinary":4,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{"h2":1},"toc":[{"text":"More semantic maps","slug":"more-semantic-maps","level":"h2","children":[{"text":"Criterion Embeddings","slug":"criterion-embeddings","level":"h3","children":[]},{"text":"r/dataisbeautiful, Embedded","slug":"rdataisbeautiful-embedded","level":"h3","children":[]},{"text":"code-network-gen","slug":"code-network-gen","level":"h3","children":[]}]}],"type":"post"}},{"slug":"projects/photography-tools","title":"EXIF Printer","html":"

I love being able to reference the technical details when editing photography—aperture, shutter speed, ISO, all the little choices that go into making a photograph. But most photo prints completely ignore this data, treating it like metadata to be hidden away in EXIF tags that nobody ever sees. So I made a little app to add the EXIF data to the margins of prints you might get from CVS, Walgreens, or Wal-Mart (don't use them for photo prints, I learned the hard way).

\n
\n\"EXIF\n
EXIF Photo Printer application displaying five family photos with options to regenerate layouts or save prints at 4x6 size.
\n
\n
\n\"The\n
The EXIF Photo Printer marketing site
\n
\n

exif-printer: Creates printable photos with camera settings displayed in the borders.

","metadata":{"title":"EXIF Printer","date":"2024-04-01T04:00:00.000Z","category":"Tools","featured":false,"modified":"2025-08-13T15:20:07.000Z","tech":["Photography","EXIF","Print Design","Web Design","Camera Metadata"],"state":"deployed","ai-involvement":"ai-assisted","tags":["photography","tools"],"words":119,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/motorcycle-pico8","title":"Motorcycle.p8","html":"

This was my first experiment in coding a PICO-8 game, so I wanted it to tie into something that sparks joy for me — motorcycle rides — and try to capture its essence in a minimalist video game sketch. That's the exact transmutation that I think makes PICO-8 magical. I hand-coded the whole thing, referencing the docs — this was pre-robot, June 2023. My brother made the sprites and the music (a tracker engine that escalates through five patterns as speed climbs, then collapses on a crash).

\n

I love how it feels once you get to a high speed and the road is coming at you fast — it does, in fact, remind me of the feeling of riding a motorcycle. Which I think is, like, an artistic achievement of some kind.

\n
\n\"The\n
The motorcycle.p8 source in the Pico-8 editor — perlin road sway and the speed-driven music-pattern engine
\n
","metadata":{"title":"Motorcycle.p8","date":"2023-07-02T00:00:00.000Z","category":"Games","featured":false,"tech":["Pico-8","Lua"],"state":"deployed","ai-involvement":"human-only","context":"collaborative","tags":["games","art","motorcycle"],"words":148,"images":1,"imageDetails":{"total":1,"cloudinary":1,"withDimensions":0},"links":0,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/coach-artie","title":"Coach Artie","html":"

Coach Artie is the AI assistant that lives in the Room 302 Studio Discord. He came online in March 2023 and has been answering the studio's questions, remembering its people and running its errands ever since.

\n
\n\"Coach\n
Coach Artie interface
\n
\n

Version one: a studio assistant

\n

The first Coach Artie was a Discord bot with memory. Alongside each message, he gets the history of his past conversations with that person, the memories he's formed about them, and a random mix of other memories. That mix is what made him feel like a member of the studio rather than a search box. As I wrote in my 2024 year in review, he \"developed into an AI assistant that helps all members of the studio.\" I purposely left out the ability to DM him, to encourage public conversation.

\n

Version two: one brain, many doors

\n

Coach Artie 2 is a 2025 rebuild as a TypeScript monorepo. One capabilities service sits behind many doors: Discord, Slack, SMS, IRC, email and a web \"brain\" UI for looking inside his head. A Redis queue feeds the language model through OpenRouter, and his memory and state live in SQLite. Capabilities are grouped by what they do: research, memory, the web, development, media, productivity, finance and more.

\n

What he remembers

\n

What does an assistant actually remember after years of conversations? Coach Artie: Memory Analysis embeds all of his memories, clusters them and draws the map.

\n

The showcase site

\n
\n\"Meet\n
Meet Coach Artie — the showcase landing
\n
\n

The Coach Artie showcase is a one-page editorial site in big serif display type on black, walking through what the agent does: adapts to its environment, remembers what matters, stays cost-conscious, writes its own release notes. It lays out 28 capabilities like a magazine feature.

","metadata":{"title":"Coach Artie","date":"2023-03-21T04:00:00.000Z","category":"Tools","featured":false,"modified":"2025-08-26T19:52:50.000Z","url":"https://github.com/room302studio/coachartie2","tech":["Node.js","TypeScript","Discord.js","OpenRouter","Redis","SQLite"],"state":"evolved","ai-involvement":"ai-enhanced","context":"collaborative","tags":["programming","ai","product","nodejs"],"about":"[[project-notes/coach-artie]]","words":294,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":4,"codeBlocks":0,"headers":{"h2":4},"toc":[{"text":"Version one: a studio assistant","slug":"version-one-a-studio-assistant","level":"h2","children":[]},{"text":"Version two: one brain, many doors","slug":"version-two-one-brain-many-doors","level":"h2","children":[]},{"text":"What he remembers","slug":"what-he-remembers","level":"h2","children":[]},{"text":"The showcase site","slug":"the-showcase-site","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/margin-maps","title":"The Margin","html":"

Data storytelling for The Margin, an independent outlet covering the people and places most affected by environmental injustice. I'm credited for data storytelling on its first two features, which pair the reporting with satellite-based map scrollytelling.

\n

We Glow in the Dark

\n

Leanna First-Arai's story on the Memphis Defense Depot, a Superfund site where the Army stored and disposed of munitions and chemical weapons for some 50 years, and the community around it demanding reparations. Made with The Margin and Earth Genome.

\n
\n\"Memphis\n
Memphis — a historical city map registered over present-day satellite imagery
\n
\n

Read the story →

\n

Opening the Gateway

\n

Rico Moore's feature on Seattle City Light's three dams on the Skagit River, and the Upper Skagit Tribe's fight over salmon and treaty rights during the dams' federal relicensing.

\n
\n\"Skagit\n
Skagit River — a satellite-based feature on hydroelectric dams
\n
\n

Read the story →

","metadata":{"title":"The Margin","date":"2022-09-21T04:00:00.000Z","category":"Journalism","featured":false,"draft":false,"client":"The Margin","tech":["Mapping","Satellite Imagery","Scrollytelling","Data Visualization"],"state":"deployed","ai-involvement":"human-only","context":"client","tags":["maps","dataviz","journalism","interactive"],"words":143,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":4,"codeBlocks":0,"headers":{"h2":2},"toc":[{"text":"We Glow in the Dark","slug":"we-glow-in-the-dark","level":"h2","children":[]},{"text":"Opening the Gateway","slug":"opening-the-gateway","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/long-lead","title":"Long Lead","html":"

Production and technical work for Long Lead, a story studio that builds each long-form feature from scratch — no CMS, no templates.

\n

The Depths She'll Reach

\n

Xan Rice's profile of world-record freediver Alenka Artnik, told as an immersive scroll that mirrors the descent. It won two Webbys for Best Sports Website.

\n
\n\"The\n
The Depths She'll Reach — a freediver descending, with captioned audio
\n
\n

Read the story →

\n

Querdenken: COVID Misinformation or Freedom Movement?

\n

Darren Loucaides' investigation into Germany's Querdenken movement and the 2020 storming of the Reichstag. I'm credited for production and technical support. The data graphics trace the audience growth of the Querdenken_711 and Qlobal Change Telegram channels (data: Telemetrio) and map the Telegram universe around Querdenken_711 (network data: Jordan Wildon / Logically).

\n
\n\"The\n
The Rise of Qlobal Change & Querdenken_711 — audience growth beside the Telegram network map
\n
\n

Read the story →

","metadata":{"title":"Long Lead","date":"2021-11-18T05:00:00.000Z","category":"Journalism","featured":false,"draft":false,"client":"Long Lead","tech":["Scrollytelling","Data Visualization","Network Analysis"],"state":"deployed","ai-involvement":"human-only","context":"client","tags":["data","dataviz","journalism","investigations"],"words":144,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":3,"codeBlocks":0,"headers":{"h2":2},"toc":[{"text":"The Depths She'll Reach","slug":"the-depths-shell-reach","level":"h2","children":[]},{"text":"Querdenken: COVID Misinformation or Freedom Movement?","slug":"querdenken-covid-misinformation-or-freedom-movement","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/ccrb-clusters","title":"Clusters of NYPD Misconduct","html":"
\n\"Force-directed\n
Force-directed network graph of NYPD civilian complaint clusters showing officers connected by shared misconduct patterns
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\n
Scrolling the published Gothamist investigation — the officer-cluster network as readers met it
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\n\"The\n
The network visualization in the published piece
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In 2021, WNYC/Gothamist got the NYPD's full civilian-complaint dataset through a FOIL request and handed it to me — every complaint and every officer since 2000, including officers named only as witnesses and complaints the CCRB never substantiated. Noisier than the data ProPublica had published a year earlier, but for mapping a network that noise is the signal: being named on a complaint alongside another officer, even an unfounded one, means the two of them interacted in a way the public noticed.

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Complaints are often the first and only warning that an officer is on a course of escalating violence. Derek Chauvin had at least 22 complaints across 19 years before he killed George Floyd; the officer who choked Eric Garner had 7. Nothing disrupted either pattern.

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So I built the network — 29,915 officer nodes, 159,671 relationships, in Neo4j (with a lot of Cypher help from David Allen at Neo4j) and laid out in Gephi (love-hate relationship, but unrivaled for networks). Two officers get a link — a CO_OCCURANCE — when they appear on the same complaint, weighted by how many they share: three complaints together, weight 3. I filtered out everything the CCRB marked exonerated or unfounded first, and only labeled an officer by name if they'd had a complaint substantiated — a caution I was told lawyers would appreciate. Everyone else stays an anonymous ID.

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One sign it was working: when I ran community detection, the clusters mirrored real NYPD precincts — officers appear on complaints with the officers they actually work beside.

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Then the big nodes surfaced — Martinez, Radoncic, Grieco — officers co-appearing on complaint after complaint. When Gothamist reporter George Joseph took those names to the street and interviewed victims, the graph held up: the central nodes were acting as catalysts in real life. One man described a big node, Adnan Radoncic, sparking a group assault — \"As soon as he grabbed me, all the officers was hands on. It's like they just followed his lead.\" Math and reality matched up.

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I documented every query and every decision so anyone could rebuild this for their own police department: the full methodology write-up →

","metadata":{"title":"Clusters of NYPD Misconduct","date":"2021-06-15T04:00:00.000Z","category":"Journalism","modified":"2025-08-26T19:52:56.000Z","url":"https://gothamist.com/news/mapping-clusters-nypd-officers-repeatedly-accused-misconduct","tech":["Neo4j","SQLite","Gephi","Network Analysis","Cypher"],"featured":true,"state":"deployed","ai-involvement":"human-only","context":"client","tags":["data","nypd","journalism","database"],"words":394,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/covidcast","title":"COVIDcast","html":"

During the early COVID-19 pandemic, I worked with Carnegie Mellon University's Delphi research group on COVIDcast, prototyping data visualizations and interactions to help the public understand hospitalization, transmission and movement trends across the country.

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COVIDcast launched in April 2020 with a then-unusual idea: no single signal could be trusted on its own, so it mapped many rough ones side by side. These included doctor and telemedicine visits, symptom searches on Google, flu-test statistics, and symptom surveys run through Facebook and Google. Where several signals agreed, you could believe them.

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Scrolling the COVIDcast dashboard as it runs today — indicator tiles, the county-level map, and the signals table
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\n\"COVIDcast\n
COVIDcast dashboard: weekly case, hospitalization, and death rates above an interactive county-level map
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I kept playing with the data afterwards. Using Delphi's open Epidata API, I made time-lapses of doctor visits by county, where each circle is a county sized by the share of outpatient visits due to COVID-like symptoms. One was paired with a data sonification of the same numbers for all of New York State.

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\n\"A\n
A county-level circle map of the United States, one circle per county
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","metadata":{"title":"COVIDcast","date":"2020-04-24T04:00:00.000Z","category":"Journalism","featured":false,"modified":"2025-08-26T19:53:05.000Z","url":"https://campustechnology.com/articles/2020/04/24/carnegie-mellon-maps-offer-more-data-for-covid-19-forecasting.aspx","tech":["Data Visualization","JavaScript","COVID-19 Data","Public Health"],"state":"deployed","ai-involvement":"human-only","context":"client","tags":["covid","dataviz","javascript","health"],"words":186,"images":3,"imageDetails":{"total":3,"cloudinary":3,"withDimensions":0},"links":1,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/twitter-artbot","title":"Twitter Artbot","html":"

My first generative art bot — @417am1975, running since 2017. It picks a random art script, renders a piece with node-canvas, and tweets it, on the hour, on its own.

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This was my first generative art bot, and boy did he make some dope shit. It came from node-canvas tick-generations.

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I like it as an artifact of how I was using the robots to make art before AI, and how that changes my perspective on things as a computer-aided artist.

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\n\"Twitter\n
Twitter Artbot — generative piece 1
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\n\"Twitter\n
Twitter Artbot — generative piece 2
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\n\"Twitter\n
Twitter Artbot — generative piece 3
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\n\"Twitter\n
Twitter Artbot — generative piece 4
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\n
\n\"Twitter\n
Twitter Artbot — generative piece 5
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\n\"Twitter\n
Twitter Artbot — generative piece 6
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\n
\n\"Twitter\n
Twitter Artbot — generative piece 7
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\n\"Twitter\n
Twitter Artbot — generative piece 8
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\n\"Twitter\n
Twitter Artbot — generative piece 9
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There's a ton still up at @417am1975.

","metadata":{"title":"Twitter Artbot","date":"2017-06-11T05:00:00.000Z","category":"Art","featured":false,"draft":false,"url":"https://twitter.com/417am1975","tech":["CoffeeScript","HTML","JavaScript"],"tags":["art","bot","generative"],"words":141,"images":9,"imageDetails":{"total":9,"cloudinary":9,"withDimensions":0},"links":2,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/nbcnews-specials","title":"NBC News Specials","html":"

From 2016 to 2019 I was a senior interactive graphics specialist at NBC News, on the Foundry team. We built bespoke longform features, the specials, in collaboration with reporters across the newsroom. Every one was designed from scratch around its story, mixing video, data visualization and scrolling narrative.

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Scrolling Journey of a Bullet — the bullet-path diagram, documentary stills, and longform text as readers met it
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Journey of a Bullet (2017)

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The overlapping stories of six gunshot survivors, from Iraq to the streets of Chicago, coping after their injuries. Read it →

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\n\"The\n
The introduction to the Journey of a Bullet story
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Post Bail (2017)

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America's justice system runs on exchanging money for freedom, so can data fix it? Jon Schuppe's investigation includes an interactive version of a risk-assessment algorithm, so readers can see how a score gets made. Read it →

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Does America Need Another Prison? (2018)

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Letcher County, Kentucky, was sustained by a coal industry that now hardly exists, and a federal prison might replace it. Read it →

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\n\"A\n
A map comparing the location of prisons and coal mines in the southeastern United States
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How Trump Won (2016)

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How a populist message proved everyone wrong, county by county. Read it →

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\n\"A\n
A table and map showing the counties that swung hardest toward Donald Trump
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And more

\n","metadata":{"title":"NBC News Specials","date":"2016-12-14T20:01:50.000Z","client":"NBC News","category":"Journalism","featured":false,"modified":"2025-08-13T16:01:12.000Z","url":"https://nbcnews.com/specials","state":"deployed","ai-involvement":"human-only","tech":["JavaScript","D3","Longform Design"],"context":"client","tags":["dataviz","journalism","webdesign","elections"],"words":255,"images":4,"imageDetails":{"total":4,"cloudinary":4,"withDimensions":0},"links":7,"codeBlocks":0,"headers":{"h2":5},"toc":[{"text":"Journey of a Bullet (2017)","slug":"journey-of-a-bullet-2017","level":"h2","children":[]},{"text":"Post Bail (2017)","slug":"post-bail-2017","level":"h2","children":[]},{"text":"Does America Need Another Prison? (2018)","slug":"does-america-need-another-prison-2018","level":"h2","children":[]},{"text":"How Trump Won (2016)","slug":"how-trump-won-2016","level":"h2","children":[]},{"text":"And more","slug":"and-more","level":"h2","children":[]}],"type":"post"}},{"slug":"projects/nbc-big-board","title":"NBC News Big Board","html":"

It started as a prototype I made in January — a touchscreen way to explore county-level election results — that I demoed to Adam, then to Steve, then to Marc, until it got the budget and became the real thing: the \"Big Board\" Steve Kornacki wields on air, live, in front of ten to nineteen million people.

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Building something that gets performed live is the most stressful thing I've ever done — no room for error, and you hand it off to someone else on a screen you don't control. In the weeks before an election, Adam (Kornacki's producer) was texting and calling me at all hours as he did hits on Maddow and Morning Joe, and I got used to adding new scorecard filters at a moment's notice.

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The workflow on election night, from my couch: edit some JSON, VPN into the NBC network, SSH into the server, git pull from master, pm2 restart all, text the producer that it's updated — then watch my change go out on air a few minutes later through Hulu. Doing that live in an emergency and seeing it on television minutes later is a pretty cool feeling.

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Broadcast runs on radio frequencies, mostly silent when things go well, and you can hear things breaking all over — \"the 3A wall went to black,\" \"the rink graphics aren't loading.\" You keep your ears perked for your own name. You hope to god you don't hear it.

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By the end it worked. A coworker told me Chuck Todd's producer said it was the first election night Chuck wasn't frustrated with the app. Steve looked amazing with it — panning, zooming, pulling up the scoreboard and the historical drawers we'd added, using motions and ways of storytelling I'd worked out months earlier, playing on TV exactly how I'd wanted them to.

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The whole story — the 1AM bacon pancakes, the Montana freeze, what I learned about leading a team — is here: Election Night 2018 →

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\n\"The\n
The Big Board UI: 2016 Pennsylvania presidential results beside an interactive county map
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2016 NBC News County-Level Election Maps

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\n\"Planning\n
Planning board — printed election-graphic studies and notes pinned to the wall
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\n\"Broadcast\n
Broadcast setup — the Big Board on a control-room monitor beside a waveform scope
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\n\"Printed\n
Printed design studies for the on-air election graphics, spread across a desk
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NewscastStudio wrote up a later update.

","metadata":{"title":"NBC News Big Board","date":"2016-11-08T05:00:00.000Z","client":"NBC News","category":"Journalism","modified":"2025-08-13T16:24:29.000Z","tech":["D3.js","JavaScript","Touch Interface","Election Data"],"featured":true,"state":"deployed","ai-involvement":"human-only","context":"client","tags":["d3","dataviz","javascript","elections"],"words":394,"images":4,"imageDetails":{"total":4,"cloudinary":4,"withDimensions":0},"links":3,"codeBlocks":0,"headers":{},"toc":[],"type":"post"}},{"slug":"projects/dataproofer","title":"Dataproofer","html":"

Along with Gerald Rich and the Vocativ data team, I received a Knight Prototype Fund grant to create Dataproofer — an open source tool to check data for reliability, missing data, and outliers. Built as an Electron desktop app for journalists.

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Scrolling dataproofer.org — the pitch, downloads for every platform, and the Knight Foundation / Vocativ credits
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\n\"The\n
The Dataproofer site — a spellchecker, for your data
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\n
❯ dataproofer Criterion\\ Channel\\ videos\\ v1.2.0-20190621\\ -\\ v1.2.0-20190621.csv\n \ntotal rows 5035\nrows sampled 1259\n \nMissing or duplicate column headers: passed\nNumeric cells: info\nString cells: info\nEmpty Cells: warn\nSpecial Letters & Characters: warn\nDuplicate Rows: passed\nPotentially missing rows: passed\nWords at their character limit: failed\nInteger at its SQL upper limit: passed\nSummed integer at its upper limit: passed\nSmall integer at its SQL upper limit: passed\nBig integer at its SQL upper limit: passed\nOutliers from the mean: info\nOutliers from the median: info\nInvalid coordinates: passed\nVoid coordinates: passed\n \n75%\n9 tests passed out of 12\n \n### PROOFED ###
","metadata":{"title":"Dataproofer","date":"2015-11-03T05:00:00.000Z","category":"Journalism","modified":"2025-08-26T19:53:33.000Z","url":"https://github.com/dataproofer/Dataproofer","tech":["JavaScript","Electron","Data Quality","CSV"],"featured":false,"state":"deployed","ai-involvement":"human-only","context":"collaborative","tags":["data","javascript","tool","journalism"],"words":171,"images":2,"imageDetails":{"total":2,"cloudinary":2,"withDimensions":0},"links":2,"codeBlocks":1,"headers":{},"toc":[],"type":"post"}}],"_links":{"self":"https://ejfox.com/projects.json","html":"https://ejfox.com/projects"}}