Over the past few years I’ve been running a gaming YouTube channel, Chambers Plays Games, and like most small creators I’ve found that making the content is only half the battle. The other half is the relentless work of promoting it… writing tweets, scheduling posts, engaging with other channels, and keeping track of which accounts in your following list are actually worth keeping around. I was doing all of this manually, which was both time-consuming and inconsistent. So, as I’ve done more than once before with problems that annoy me enough, I decided to write a tool to solve it.
That tool is PromoForge.
This isn’t my first attempt at Twitter automation. Back in early 2018, as part of a #30DayDev challenge, I built and open-sourced the Microcosm retweet bot, a Python and Tweepy script that retweeted content from a configurable set of hashtags on a schedule. It did one thing and did it reasonably well, and I wrote about it on this blog at the time. The repository is now archived. PromoForge is in some ways the natural successor to that project, built on the same instinct to automate the repetitive parts of being online, just considerably more ambitious about what “automated” actually means.
What started as a fairly simple idea (fetching my YouTube videos and generating tweets for them) has grown into something considerably more ambitious over the last ten days. This post covers what’s been built, some of the more interesting challenges I ran into along the way, and where I plan to take it next.
What Is PromoForge?
At its core, PromoForge is a promotion and audience-growth platform built specifically for gaming content creators. It has two entry points: a command-line tool for headless operation, and a full web UI that you run locally and access through your browser. The web interface is where most of the action happens and it covers three broad areas of work: content scheduling, audience growth, and channel maintenance.
The scheduling side of things works by connecting to the YouTube Data API, fetching your public videos, and then generating algorithm-optimised tweets for each one. It detects which game is being played from the video title using a combination of exact matching and fuzzy search, selects appropriate hashtags from a curated set, and composes a tweet from a template library. You can export everything as a CSV or push directly to Buffer or X’s own scheduling API. The whole flow from “fetch my videos” to “tweets are scheduled” can be done in a couple of clicks.
