A designer turned the process they use for client logos into a Skill: 41 days, 6,000 stars

Kaan Kızıltuğ, a Turkish brand designer, has just one repo on GitHub: an Agent Skill that makes Claude Code, Codex, and Gemini CLI follow a designer's rules when making logos. It never reached Hacker News and never spent a cent on promotion, yet it climbed to 6,054 stars in 41 days. Below: why it took off, where the stars came from, how much room the logo niche still has, and which field you should pick for your next one.

A self-deprecating Reddit post

In Sep 2026 26, Kaan created the repo and published v1.0.0. The same day he posted on r/ClaudeAI with the title "I built a logo design skill for Claude Code, trying to get less AI slop." The post didn't oversell. It led with a caveat:

I don't think it produces amazing results, but it doesn't produce AI-generated slop (let's say 50% of time).

"It's not stunning, but maybe half the time it won't produce AI-looking garbage."

Three days later the repo had 647 stars, and by day four it passed 1,000. In Sep 30 he shared "4 days, 1,000 stars" on LinkedIn, but that post got only 19 reactions, so the stars clearly didn't come from his own circle. By Nov 6 the repo had 6,054 stars and 479 forks (GitHub, 11-06).

He explained his motivation in an Oct 2 blog post. He needed a logo and wanted to see whether an AI agent could help, so he looked for a skill that works like a designer and didn't find one. Image generators give you a picture of a logo that you can't scale or edit. Asking a model to "write an SVG logo" always returns the same few things: a circle, a letter, a gradient. His conclusion: "The model is good enough. What's missing is the process." So he wrote down the process he uses for client logos.

What it actually does

Once installed in an agent, if you say "make me a logo," it doesn't draw right away. It goes through five steps:

1. Ask for the brief: the name, the audience, three to five brand adjectives, and what you don't want.
2. Check what the category looks like: browse the 1,400 real brand SVGs it ships with to find conventions in the same industry, and list the clichés: shields and upward arrows for fintech, beans and steam for coffee, padlocks for security. Those defaults are off-limits.
3. Write 8–12 one-sentence concepts and keep only the strongest, most distinctive 3. "If a concept takes a paragraph to explain, it isn't a logo concept."
4. Test before showing you: draw everything in black, shrink it to 16, 32, and 64 pixels to check legibility, then test in one-color, reversed, and mirrored-rotated versions, and place it next to real logos for a "shelf test." An audit script catches corners that are "just off from 45°" and details that blur at small sizes.
5. Stop and wait for your pick: three grayscale options with one recommendation, then it halts. Only after you choose a direction does it do color, lockups, mockups, favicons, and the brand guide.

The output is clean vector SVG, and wordmarks are hand-drawn paths rather than default fonts, so you can drag them into Figma or Illustrator and keep editing. The tools are Python scripts with no third-party libraries. It's MIT-licensed and free. In late October a GitHub Sponsors button was added to the top of the README, but there's no paid version.

The first screen of the README is one large image: 28 fictional brands (specialty coffee, a pickleball app, a password manager, a boxing gym, a sourdough bakery, and so on), each shown going from brief to finished palette. In the blog he doesn't hide the failures: from one batch of ten, four were rejected. Two looked too much like earlier ones, one looked like a loading spinner, and one looked like a play button.

Where the stars came from

The growth curve came in waves, not one spike:

Star counts come from GitHub's daily records; X view counts are as read by 11-06.

A few main threads:

• Reddit kickoff. After the first r/ClaudeAI post, r/BestGitHubRepos and r/ClaudeWorkflows picked it up too. Later, Reddit threads about "using Claude to make a logo" often had it linked alongside.
• AI newsletter relay. It hit 1,000 stars in its first four days, timing lines up with three AI news digests picking it up, and the AlphaSignal link carries a utm_source tag.
• X tool-list accounts did the heavy lifting. Chinese, English, Turkish, Korean, Thai and Spanish "AI tips" accounts kept folding it into "N repos that turn Claude into X"-style lists. Every star spike has a post pulling tens to hundreds of thousands of views behind it.
• Skill directories auto-indexed it: skills.sh shows npx skills add installed 1.9K times; Skill Leaderboard ranks it #106 overall and #19 in design; dozens of other directories and mirrors too.

A more concrete signal than stars is downloads: the zip uploaded to Claude.ai, attached to the release, has been downloaded about 11k times across both versions (GitHub, 11-06). Fork rate is 7.9%, a bit lower than new repos of similar size (my estimate). That fits skill repos: lots of bookmarks, few people who actually modify them.

Worth noting: the author says a full run, on Opus at high effort, takes about an hour. That's a high bar, and from the outside you can't tell how many people use it long-term.

Why this one and not the earlier ones

It wasn't the first logo skill. From April to September, GitHub already had several (pranavred/claude-code-logodesign-skill, wcgordon1/logo-skills, etc.), and r/ClaudeAI had people posting skills that teach Claude to design logos in plain SVG. Each topped out at single digits to a hundred or two stars. The difference comes down to three things:

• The content is written by a real designer. A blacklist of clichés, optical corrections (jargon like overshoot and bone effect), checkpoints. These aren't prompt tricks. They're rules from seven years of client work, and people in the trade recognize them at a glance.
• A memorable number and a wall of results people can repost. "1,400+ logo reference library" shows up in almost every repost, and a wall of finished work across 28 brands got lifted straight into tool-list posts as the header image. Whether a skill gets shared on X depends heavily on the screenshot.
• It landed in the two months Agent Skills became a common format. In 2026 9–October, a folder with a SKILL.md worked across Claude Code, Codex, Gemini CLI and Cursor. "Give your agent skills" was hot, and list posts were traffic machines. One codebase covers every agent, so accounts in every language and ecosystem could push it.

On top of that, the author kept maintaining it: in October they shipped v1.4.x, added CI and added evals, so each new round of reposts kept feeding the long tail of stars.

Who's competing, and how much room is left

The "general logo design skill" slot is already taken. Another one of the same kind will struggle to get the reposts it got. What's still open is two ends: upstream and downstream of the logo (animation, brand systems, packaging rollout), which people are already working on; and other professional design work that AI makes look amateur (app icons, posters, packaging, slide decks, infographics, font pairing). I haven't seen anyone make a name for themselves using this approach of real workflow + reference library + automated tests (this is 11-06's observation, not an exhaustive survey).

If it were you

Verdict: A. Copying the logo idea isn't worth it. Carrying this approach over to another kind of professional design work you really know is. The two bets are whether your expertise is really deep enough, and whether the "skill list post" wave can keep going for a few more months.

Who it suits: people who have actually worked in a design or professional field (icons, packaging, typesetting, data visualization, presentations), who have a set of rules they really use on client work, and who can write some Python. Kaan could pull this off partly because he's a designer and the rules were already there.

Who it doesn't suit: people with no industry experience who plan to have AI "summarize a design principles document" for them. Insiders see through that immediately, and list accounts won't repost a skill with mediocre output. Also anyone hoping it earns money directly: this path gets you stars, reputation and client leads, not revenue.

How to do it:

• Pick a task where "AI currently does it amateurishly, and good output is directly usable." App icons and infographics are the easiest (the deliverable is also SVG, so it can be tested automatically).
• Build on the same skeleton: a SKILL.md with a real workflow and a cliché blacklist with acceptance criteria. Pair it with a searchable library of real reference work, and come up with a memorable number. Add a zero-dependency test script. Place a "stop and wait for the user to choose" checkpoint at the key moment.
• Before launch, run 20–30 fictional cases yourself and assemble them into a wall of finished work at the top of the README. That image is your ad.
• One codebase that works with the Claude Code plugin marketplace, the Claude.ai zip (with a slimmed-down version), and directories for Codex / Gemini CLI / Cursor.

How to get users: launch on r/ClaudeAI with a title that names a pain everyone recognizes (something like "less AI slop"), keep the tone modest, and state clearly what it still gets wrong. Over the next few days, watch for AI digests and skill directories picking it up. The wall-of-work image needs to be reposttable on its own so regional list accounts can use it directly. If you read Chinese, the Chinese X list accounts are the starting point for a second wave of growth for this repo.

Deadline: ship before year end. In November this repo's weekly star gains fell from 1,119 to 814, which suggests list posts have less appetite for "yet another skill". The later you go, the more you'll have to rely on real substance rather than the hype cycle.

Signs you misjudged it: ① two weeks after you ship your skill, stars stall at a few hundred with no list account or digest pickup. That means the wave has passed, or the field you picked isn't "photogenic" enough. ② In your chosen area, Anthropic or Figma has already shipped an official equivalent skill or feature. ③ The reverse: late followers like fatihaydost/brand-identity-skill passed a thousand or two stars in November. That suggests the space isn't crowded yet, and you can be bolder about building in the area adjacent to logos.

A closing thought for anyone doing open source: models keep getting better at making things, so what's worth money is the unwritten rules of a trade. Whoever writes their trade's rules down as a workflow an agent can execute, and pairs it with a wall of work that people can repost, is the one who catches this round of skill traffic.