A tweet bookmarked 2,100 times sent traffic from a 5-follower author's Blender skill pack to over 700 stars

A former Roblox developer wrote the full Blender pipeline (modeling, rigging, baking, exporting to game engines) as a skill pack that coding agents can read, released under MIT. In just over three weeks it picked up about 740 stars, mostly from one tweet posted by someone else. The author himself has only 5 followers on X. The project is genuinely useful, but the same thing already has a dozen-plus repos from the past 2026 years. The lesson here is the playbook: picking a different professional software is a better bet than building yet another Blender version.

One tweet, 220 stars in two days

In 2026 October 18 morning 9:15 (UTC), the AI tool recommendation account @hakimieiqbal (about 2,600 followers) posted:

20 Blender 5.2 skills that give AI agents an actual 3D production workflow

Below it, the repo's covered workflows are listed (modeling, sculpting, topology and UVs, PBR materials and baking, geometry nodes, rigging and animation, rendering, export to Roblox / Unity / Unreal / Godot). The last line hits the point:

The useful part here is that it gives coding agents a repeatable Blender process instead of forcing them to improvise with bpy every time.

(The useful part is that it makes the coding agent follow a fixed Blender workflow every time, instead of improvising bpy scripts from scratch.)

By Nov 6 the tweet had 67k impressions, 1,369 likes, and 2,159 bookmarks. More bookmarks than likes is the classic "save it for later" pattern. The repo gained about 140 stars that day and another 80 the next day (trendshift daily data). Before this, it had been adding single digits a day.

The repo author, EL4CTEO, registered his GitHub account in June 2025. He has 15 followers, and his bio reads "former Roblox developer, open-sourcing MCP and agent skills for Roblox / Blender." His X account has only 5 followers. The repo was created in Oct 14, and many commits carry "Co-Authored-By: Claude," so the skill pack itself was most likely written by an agent (inference).

What it is

One folder with 28 "skills" (20 at launch). Each skill is a SKILL.md doc plus several Blender Python scripts, telling the agent how to do one workflow step, in what order, and which pitfalls to avoid. For example, blender-texture-baking handles normal and AO map baking, blender-character-rigging handles Rigify rigs and skinning, blender-export-pipelines handles export to each game engine, and blender-asset-qa checks for z-fighting, floating parts, flipped normals, weights, and missing textures before delivery.

The supported agents are listed in the repo title: Claude Code, Codex, Gemini CLI, Copilot, Cursor, and the README adds OpenCode. There are three install methods: one command through the Claude Code plugin marketplace, clone and run the install script, or npx skills. It also works without the Blender MCP, since the agent launches a headless Blender in the background to run scripts. The repo includes 67 tests that run in real Blender.

The README's first screen shows a comparison image that links to a comparison page: the same model and the same prompt, run once with skills and once without, no retries and no edits, across five tasks: a 4K concrete wall material, cloth simulation of a blanket settling onto a bed, a pistol firing and reloading animation, rigging and walk cycle for an RTS soldier, and reducing a 5,370-face model to half its polygons. On the side with skills, the pistol was split into 19 named parts, the soldier was exported as FBX and GLB, and each task gained a QA check image.

Why now

• The channel already exists. In April 2026, Blender shipped an official MCP. Anthropic made it a Claude Blender connector the next day. The earlier open-source version, ahujasid/blender-mcp, already has 33k stars. Agents connecting to Blender is no longer news.
• Connected, but getting it wrong. Models often make mistakes writing bpy, and the output can't make it into an engine. On Reddit's r/aigamedev, people keep asking "How can I make Claude good at Blender?" and "Is there a way to make Claude a better 3D animator?" Users have moved from "can it connect?" to "can it do it right?" A skill pack fills exactly that gap.
• One repo covers every agent. Agent Skills became a cross-agent standard in 2026. The .agents/skills directory can be read by Codex, Gemini, Copilot, and Cursor alike. Build it once, and users of several agents can use it.
• The version is in the title. Blender 5.2 is a new LTS release, and the title says "5.2," so it looks current and tested against the latest version.

Where the stars came from

Key points:

• Never made GitHub Trending, and never got onto HN, Product Hunt, or big YouTube channels. One mid-sized tweet plus a pile of auto-indexing got it past 700 stars.
• Directory sites bring in traffic for free. The repo carries tags like agent-skills, claude-skills, blender, game-assets, and skills directories crawl these tags automatically in 2026. skills.sh shows 6.7K cumulative installs, but that is summed across 28 separate skills, so real unique users are probably only a few hundred (estimate).
• The comparison page converts; it didn't spark the spike. The comparison page went live in Oct 19, after the tweet. Its job is to make later visitors more willing to star the repo, and it gave others ready-made material for "Before & After" videos.
• The fork-to-star ratio is about 10% (GitHub: 11-06 stars, 739 forks... 75), suggesting some people weren't just browsing; some actually took it and modified it.
• Growth is slowing: 11-06 in the first 7 days +146, and the stretch before that was +7 over 172 days.

Who else does the same thing

This topic is already crowded. From 2026 through October 7, more than a dozen Blender + agent skill repos appeared:

EL4CTEO's version stands out for the most complete workflow (all the way to engine export, plus QA), the ability to run without the Blender UI, and tests and a comparison page. These make it easy to repost and bookmark, but it has no real moat: the skill files are just text and scripts that anyone can write, and the author himself wrote them with an agent.

What to learn from it

1. Once the channel exists, fill in the workflows. Once a professional software gets an official MCP or a usable scripting interface, agents can connect to it, and the next problem is always "doing it wrong." Writing that industry's workflows as skills is exactly what this repo does.
2. Put the version number and supported agents in the title. "Blender 5.2" + "Claude Code, Codex, Gemini CLI, Copilot and Cursor" so people who repost can copy it straight, and people searching can find it.
3. Make a with/without comparison. Same model, same prompt, one run each, side by side with a drag slider. Beats any feature list.
4. Fill in the tags and stay compatible with skills.sh and plugin marketplaces, so directory sites pick it up on their own.
5. Find AI tool recommenders with 2–5K followers. This time one account with ~2,000 followers brought more stars than every other channel combined.

If it were you

Verdict: don't build another Blender skill pack. A dozen people are already on that path, and the biggest one is three times the size of the next. Running the same playbook on a different pro software that just got an agent channel and has no systematic workflow write-up yet has a real chance at a few hundred stars.

Who it's for: developers who have actually used a pro tool (3D, CAD, video editing, audio, PCB design, game engines) and know what steps a job takes from start to finish. Whether the skills are right is only obvious to insiders.

Who it's not for: people who don't know the industry and just want to mass-generate skill files with an agent. There are already many of these repos, wrong workflow steps make the agent do worse work, and that shows up immediately in a comparison image. It's also not for anyone hoping to make money from it. This path gets you stars and reputation.

How: first pick the software. It should have an MCP or scripting interface, people on forums asking "how do I get Claude to use X well," and no GitHub repo with more than a few hundred stars for "X skills" (candidates like Houdini, DaVinci Resolve, FreeCAD, KiCad, Godot; whether someone already does them is unverified). Split skills by workflow step, pair each with auto-runnable scripts and tests, and add a QA skill for pre-delivery checks. Build the comparison page before launch: same model, same sentence, one run.

How to get users: put the full software version and agent list in the repo name and description, tag it agent-skills, claude-skills and the software name; post in that software's subreddit and r/claudeskills; DM a few AI tool recommenders with 2–3K followers, attaching the comparison image or video.

How early: the earlier the better. The window for each pro software is probably only a few months after its official MCP launches. Blender went from official MCP release to saturation in about half a year. Models are also getting better at writing these scripts on their own, so the value of skill packs like this keeps dropping (inference).

Signs you're reading it wrong: two weeks after launch and two or three posts and threads in, you're still under 100 stars; or the tool you picked already has a competitor on GitHub with over a thousand stars; or the before-and-after comparison doesn't show a visible difference with and without the tool.