video-shotcraft: turning "cinematic feel" into 124 cards, 110 days to 17k stars

An AWS AI developer in China got fed up with the product promo videos Claude Code kept making, which looked "like a PPT." So he open-sourced the camera moves, transitions, beat-syncing, and sound effects as recipe cards an agent can follow. By Nov 6, it had 17,238 stars and 1,631 forks, and ranked #1 in its category. Below: what it is, why it's the one that took off, where the stars came from, who's following it, and how to start if you want a project that gets stars too.

The complaint that started it: "motion graphics are basically at PowerPoint-animation level"

On 2026 Jul 19, Vincent Wei (known on GitHub as Vincentwei1021, on X as @VincentWei93, bio reads AWS AI Applied Scientist) built this repo and shipped the first version the same day: 106 camera-motion cards, over a hundred motion previews, a promo video template that's been through acceptance, plus an online gallery. His launch post on X reads:

I was experimenting with the remotion plugin + Claude Code recently, and the video motion graphics were basically at PPT-animation level. No camera movement, no transitions, no sound effects... so I open-sourced this video-shotcraft skill.

The video attached is a promo made by the skill itself.

That line hit something everyone was living through. In January 2026, Remotion released official skills for agents; in March, HeyGen open-sourced HyperFrames; "have Claude Code write code to make videos" became a hot pattern. But the output all looked alike: fades, pans, zooms, cards flying around. The frameworks taught agents "how to write animation code" but not "what a good shot looks like."

What it actually does

The README's first line: tell Claude Code or Codex "make a promo video for my product," and the agent screenshots your real product pages, picks shots from the library, writes a storyboard, animates with Remotion, syncs cuts to background music, adds sound effects, checks frame by frame, and hands you an MP4 you can keep editing.

It stresses that it is not a video generation model: every frame is drawn by code from your own screenshots and copy, so the visuals are clear, on-brand, and editable, instead of a Sora-style interface that looks plausible but is fake.

The core asset is the shot recipe-card set, now 124 cards and 150 shots (in October he re-reviewed all 216 demos and kept only the best). Each card specifies how the shot moves, how long it holds, and which frame the sound enters, with a runnable demo source and an online preview. Beyond the MP4, outputs include the Remotion source, a CapCut-like browser editor (Motion Workbench, added in September), and drafts that import directly into CapCut Pro (added in August, with storyboard clips, subtitle tracks, and separate sound-effect and BGM tracks).

Install is one line: send the link to your agent and say "install this skill for me," or run npx skills add Vincentwei1021/video-shotcraft; there is an AtomGit mirror in China.

Where the stars came from

(GitHub stars; the 7 point in September comes from third-party articles, web archives, and the author's own statements; 9-07 to 11-06 per Trendshift shows +9,792 total, about 160 per day, with no single explosive day.)

The curve didn't come from one viral tweet. Several forces relayed each other, and it never stopped for 110 days.

Wave one: the Chinese AI community. After the author's own post, @sitinme posted a full tutorial thread in Jul 23, opening with "It isn't Sora or Runway, which generate video from a single sentence, and it isn't CapCut, PR, or AE, traditional editors. It's more like a product-video skill pack for coding agents," then covering installation, a recommended workflow, and pitfalls ("don't give just one prompt... otherwise the agent easily makes a fake interface that looks decent but doesn't resemble your product at all"). Tencent Cloud's developer community and Cnblogs reposted it, and within 9 days it reached 2,200 stars.

Wave two: English reposting accounts and aggregators. enterprisedna's AI Pulse (7-24), @Dinosn (7-25,4,467 views), daily.dev, Reddit r/BestGitHubRepos, @GithubProjects (9-06), @tom_doerr (10-07, +244 that day); Taiwanese Threads creators, Bilibili, and YouTube also ran introduction videos. Reposters needed no assets of their own: the "not PPT-like" shots in the gallery and the skill-made promo could be posted as is.

Wave three: the Opus 5.5 video wave. In late September Claude Opus 5.5 launched, X was "full of Opus 5.5 motion-graphics videos," and lists of "AI video-making skills" appeared. On Sep 27, GoSailGlobal counted 180 open-source libraries that let agents make video, with 26 in "product promotion and demo"; video-shotcraft was then first with 9.7k stars, and second place had only 445. The author used the moment to rewrite all shot components with Opus 5.5 and published 2.0.

Wave four: GitHub trending charts. Starting in Oct 9, it made the TypeScript daily, weekly, and monthly charts, and in early November it stayed in the weekly top five, so organic traffic kept coming.

The library also recruits its own users. SKILL.md suggests users @ the author on X, Douyin, or Xiaohongshu when they post videos; the community showcase submission form says you can list your account, "so people who see the work can find you"; the README is in Chinese, English, Japanese, and Russian; skills.sh and several skill directories index it automatically. The author later built video-talkcraft (2.1k stars, talking-head videos), anything2explainer (3.1k), and mg-styles-15 (3.1k), each a different video type on the same path, with the READMEs linking to one another.

What didn't happen: no sign of a Hacker News or Product Hunt listing, and no paid promotion. On X, the author is a mid-sized Chinese tech blogger, not a big account. That matters for anyone who wants to copy this.

A twist: the author himself said "consider uninstalling"

In Sep 25, the author posted:

If you're using Opus5.5, I'd suggest uninstalling all the skills that make video with code. This video was made from a single sentence with Opus5.5, and every part, including the BGM and sound-effect synthesis, was generated by code... On this front, Opus5.5 is a generational breakthrough.

A commenter agreed: "This time the output without any skill is even better than with one... It feels like the video skills I spent so long polishing became useless overnight with the new base model."

But after October its star growth actually accelerated, from around a hundred a day to a couple hundred, peaking above four hundred. A plausible explanation (inference): the video wave multiplied the number of people searching for "AI video" several times over, and newcomers looking for this kind of skill found it first. Fast star growth doesn't mean that many people are really using it.

Who it's competing with

Two things stand out. First, the "product promo skill" slot is already crowded: famous Chinese AI bloggers like Huashu and Guizang have built the same-positioned tools, and all of them stay under a few thousand stars. Second, the rivals with the most stars (HyperFrames, OpenMontage, brag) are frameworks or all-in-one systems, not the same kind of thing. None has caught up as a direct competitor to this one.

What it still gets wrong

• Heavy to install. It needs Node, ffmpeg, and the full Remotion setup, and a video has to be rendered and beat-synced. It isn't "one click, done." How big the gap is between stars and people who have actually shipped videos with it, I can't tell.
• Thin moat. The recipe cards are markdown plus React components, easy to copy. In September someone already said "this set of recipe cards has been adopted by several repos."
• Models are catching up. The author admits Opus 5.5 does well without any skill. The value of the shot cards is shifting from "you can't make it without them" to "it's more reliable and controllable with them."
• Product promos only. Talking-head, explainer, and e-commerce video types were split into other libraries by the author; this one doesn't cover them.

If it were you

One-line verdict: another "product promo skill" will probably not get stars, since this slot is taken, and later well-known names have only reached two or three thousand. What's worth doing is moving its method, "write aesthetic judgment as an asset library an agent can read," to another content type nobody has covered yet.

Who it suits: developers with real craft in a visual task (motion graphics, slides, posters, landing pages, data charts, e-commerce hero images) who can explain what separates good from bad, and who are willing to spend weeks breaking that difference into dozens or hundreds of reproducible recipes. No big account is required; this author was an ordinary Chinese blogger when he launched.

Who it doesn't suit: people hoping to package a few prompts as a skill and ride a trend; people without a finished piece that makes the gap obvious at a glance; people who only want to work on "AI video," an already crowded keyword.

How to do it:

1. Pick an output type where agents currently produce something "usable but ugly." Candidates (inference, not checked one by one for overlap): slides / presentations, social posters and covers, landing-page hero sections, data visualization, App Store screenshots, e-commerce hero images.
2. Shipped complete on day one: dozens of recipe cards, each with a working demo and an online preview, plus a verified finished template. Finish quality is what set it apart from the same-period "a few prompts + Remotion" toolkits.
3. Build an online gallery. People can see the results without installing anything. It's shareable material and the front door of the README.
4. Leave the output editable, and make it local: its CapCut (Jianying) export is the step Chinese users need most. For your niche, that could mean exporting to formats Keynote, Figma, or Canva can open.
5. Or fill the gap it left: a lightweight version with no rendering environment that returns results in seconds, for the people scared off by Node + ffmpeg + Remotion.

How to get stars: Open the launch post with a complaint everyone relates to (his was that "motion design is basically at PowerPoint-animation level"), and attach a finished video the skill made itself. Post in both Chinese and English communities: Chinese first to build momentum, English README and skills.sh to catch overseas users. In SKILL.md and the showcase page, encourage users to @ you when they share their work. Treat every major version as a new release. Once stars build up, open a second and third library in the same series and cross-link them.

When to move: Now through early next year. The "agent writes code to make content" wave still has heat, but each model upgrade makes some skills redundant, so the window is measured in model versions, not calendar years.

Signs you're reading it wrong: The direction you picked already has projects with thousands of GitHub stars. Or your finished output looks no different from what the latest model produces when you skip the skill and ask directly. That would mean the model has already closed the "taste gap" in this direction, so switch. Also, if stars are still in the three digits two weeks after launch, the demo isn't making the difference obvious at a glance.