GitHub engagement report
@github - 2.7M followers on X
Measured over 53 original posts from a 30-day window, last computed on October 25, 2026.
Engagement
A typical post picks up 319 interactions against 2.7M followers, an engagement rate of 0.012%. Posts are seen about 69K times each, and 0.465% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 18:00 UTC, and Wednesday is the busiest day of the week. Of the 53 posts sampled, 55% carry an image or video, 6% are part of a thread and 85% link out. The account's strongest tracked post pulled 8.9K interactions, about 28x its own typical post. Recurring topics include #githubuniverse, #badger26, #nationalcoffeeday.
Measured over 53 original posts from a 30-day window, last computed on October 25, 2026. Recurring tags: #githubuniverse, #badger26, #nationalcoffeeday.
Where this sits in the catalog
At 0.012%, GitHub sits above the 10th percentile of the 204,424 accounts in this comparison. That places it in the bottom 25% band, which runs below 0.024%.
Show the percentile table
| Percentile | Engagement rate |
|---|---|
| 10th percentile | 0.004% |
| 25th percentile | 0.024% |
| 50th percentile | 0.143% |
| 75th percentile | 0.677% |
| 90th percentile | 2.55% |
| 99th percentile | 82.4% |
This ruler is the whole measured catalog, not a size-matched group: it shows where the raw rate falls across every account we can measure, all of which are large. For a like-for-like comparison, read the size-band percentile above instead. See how the bands are built
Posting timing
This account posts most often around 18:00 UTC, and Wednesday is its busiest day of the week. The bars below are the catalog-wide pattern, with this account's own busiest slot marked. They do not show how this account performs at each hour: we keep one aggregate per account, not one per hour, so that measurement does not exist in our data.
Show engagement by hour posted, utc as a table
| Hour (UTC) | Vs author median | Posts |
|---|---|---|
| 00:00 UTC | -1% | 89K |
| 01:00 UTC | -2% | 90K |
| 02:00 UTC | -3% | 88K |
| 03:00 UTC | -4% | 94K |
| 04:00 UTC | -5% | 76K |
| 05:00 UTC | -4% | 75K |
| 06:00 UTC | -5% | 86K |
| 07:00 UTC | -5% | 93K |
| 08:00 UTC | -4% | 108K |
| 09:00 UTC | -4% | 124K |
| 10:00 UTC | -3% | 129K |
| 11:00 UTC | -3% | 141K |
| 12:00 UTC | -3% | 154K |
| 13:00 UTC | -3% | 167K |
| 14:00 UTC | -4% | 173K |
| 15:00 UTC | -2% | 176K |
| 16:00 UTC | -3% | 171K |
| 17:00 UTC | -3% | 159K |
| 18:00 UTC | -2% | 149K |
| 19:00 UTC | -2% | 141K |
| 20:00 UTC | -1% | 131K |
| 21:00 UTC | 0% | 116K |
| 22:00 UTC | -2% | 100K |
| 23:00 UTC | -1% | 90K |
Show engagement by day of week as a table
| Day | Vs author median | Posts |
|---|---|---|
| Sunday | +5% | 393K |
| Monday | +1% | 483K |
| Tuesday | -2% | 520K |
| Wednesday | -3% | 472K |
| Thursday | -2% | 430K |
| Friday | -3% | 447K |
| Saturday | +2% | 393K |
Formats this account uses
Its own posting mix on the left, and what each of those formats does across every account we track on the right. Only formats where the effect clears our publish test appear here, so an empty row is a format we could not measure rather than one that does nothing.
| Format | This account | Catalog effect | 95% interval | Accounts behind it |
|---|---|---|---|---|
| Image or video | 55% of posts | +111% | +108% to +115% | 34K |
| Outbound link | 85% of posts | -41% | -42% to -40% | 32K |
| Typical length | - | no effect | -2% to -1% | 42K |
- 55% of this account's sampled posts carry an image or video. Across the catalog, posts with an image or video run 111% above the same accounts' other posts.
- 85% of its posts carry a link off X. Across the catalog, posts with an outbound link run 41% below the same accounts' other posts, so a large share of this account's output sits in the weakest bucket we measure.
- Its average post runs 260 characters, which falls in the 180 - 280 characters band. Across the catalog, posts of 180 to 280 characters match the same accounts' other posts almost exactly.
These are catalog-wide differences applied to this account's own posting mix, not a measurement of how each format performs for this account specifically. We keep one median per account, not one per format per account, so the second thing is not something this data can tell you.
Best tweets
- Aug 6, 202628x their median
Build a plugin once and use it across compatible agent clients. Introducing Agent Plugins, an open standard developed with @awsdevelopers, @cursor_ai, @github, @code, and @vercel that packages Agent Skills and supports MCP server configurations in a shared format. https://t.co/JOQe4sc40N
- Sep 21, 202616x their median
Just one engineer and a team of agents ported the GitHub Copilot agent runtime to Rust, shipping 800,000 lines of production code while retaining code quality. 🚀 How it worked 👇 https://t.co/wJ5qWMuGvV
- Sep 13, 202616x their median
Today is for the programmers 🍻 https://t.co/FDQRmhuwuE
- Oct 22, 202615x their median
Spent a bunch of tokens over the last few weeks building a fully procedural New York simulation. https://t.co/YSrGNoIYsK It's only 784KB gzipped and the code is on github, so you can do whatever you want with it ✌️ https://t.co/tj5wXVxhDR
- Jul 28, 202611x their median
Maintainers: You don’t need to be a security engineer to improve your project’s security. 🔐 Enable these 6 free GitHub settings in under 30 minutes. 🧵
- Sep 1, 202611x their median
Sometimes it's easier to show than tell. We're sure this update will help with that. 👀 GitHub CLI now has a repeatable --attach flag that uploads a local image or video. Reference it inline in an issue, pull request, or comment body. Available now to all users on GitHub across all plans. 🎉 https://t.co/2oRtlSHdPT
- Sep 23, 20269.6x their median
GitHub 🤝 @Muse A new way to connect your GitHub account to review PRs, catch up on issues and notifications, and leave comments without switching tabs. https://t.co/iSg1FRs4Rt
- Aug 25, 20268.6x their median
🐧 Linux turns 35 today. That seemed like a pretty good excuse to round up 35 of the best free and open source games you can play on Linux. Some classics. Some hidden gems. Some surprisingly ambitious projects. 🎮👇 https://t.co/ESmg08Llbh
- Oct 21, 20267.2x their median
How do you _guarantee_ your agent's code is correct? You prove it. Introducing Proof Driven Development Kit (PDD Kit) from @MSFTResearch. PDD Kit helps turn your plan into a formal spec, then proves the agent's code meets that spec for every input. No vibe verification. PDD Kit is integrated with @GitHubNext's Chopin, so you can plan as a team. PDD Kit takes an app's login flow from intent to a verified pull request: It discusses your code, infers your intent as it goes, and proposes a formal spec in Verus, a proof language for Rust. Once you approve the spec, the Verus verifier automatically proves the code meets it. Where proof isn't possible, it falls back to empirical verification with tests and computer-use agents (CUAs). It works on Rust today. No new language, no change in how you produce the underlying code, making formal methods more accessible. The goal is a verified software factory, where engineers review specifications instead of code. Come see it in action at GitHub Universe, Oct 28–29. Swing by the Speakeasy and ask for GitHub Next!
- Aug 20, 20267.0x their median
On August 17, GitHub experienced a significant outage that disrupted developers and organizations around the world. If you were trying to ship software that day, we let you down. I posted in March and April about the steps we’re taking to make GitHub more reliable. The work is still underway. Here is an update: https://t.co/9KaQy7O4CG
Ranked by total interactions across everything we have tracked for this account, which is a longer history than the 30-day window the rates above use. The multiple compares each post to this account's own median.
Recurring topics
The most frequent hashtags in the sampled posts. They describe what this account writes about; they are not a performance signal, and the catalog-wide breakdown on the hub shows how little hashtag count moves.
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Reading these numbers
A typical post picks up 319 interactions against 2.7M followers, an engagement rate of 0.012%. Posts are seen about 69K times each, and 0.465% of those impressions turn into an interaction. That is about 2.52% of the follower count, which is the gap between an audience on paper and an audience in a timeline. Posting runs at about 2.6 posts a day over the last 30 days, with activity on almost every day in the window. Most posts go out around 18:00 UTC, and Wednesday is the busiest day of the week. Of the 53 posts sampled, 55% carry an image or video, 6% are part of a thread and 85% link out. The account's strongest tracked post pulled 8.9K interactions, about 28x its own typical post. Recurring topics include #githubuniverse, #badger26, #nationalcoffeeday.
- What is GitHub's engagement rate on X?
- GitHub (@github) has an engagement rate of 0.012%, based on the median interactions across 53 original posts from the last 30 days against 2,726,645 followers. Replies, reposts and quote-posts of other people are excluded from that sample.
- Is that a good engagement rate?
- At 0.012%, GitHub sits above the 10th percentile of the 204,424 accounts in this comparison. Those comparison accounts are all large ones, because our scanning cadence is weighted towards big accounts, so this is a ranking among peers of similar scale rather than a ranking across X.
- Does @github have real engagement?
- There is not yet enough sample to rank this account against others of its size.
- When does @github post?
- Most posts go out around 18:00 UTC, and Wednesday is its busiest day, at roughly 2.57 posts per day across the measured window.