Stringers
konlu/story-studio · konlu

Sold over 4000 in one day: how a video-channel selling Skill hit 781 stars in 11 days

What it is A Chinese Skill for Claude Code and Codex that takes a single sentence from topic selection to script writing, voiceover, illustrations, and a Jianying draft, built specifically for WeChat Channels history and biography accounts.

Why it took off The author posted a long Chinese post on X bragging about his selling revenue; the post got 100 times his follower count in views. The repo also bundles the verbatim scripts of 370 hit videos from 5 top video-channel accounts, so side-hustlers felt they could use it right away.

BHow you can follow suit Copy the pipeline, swap in a content niche where you've already had results, and distill top accounts' writing into a hook library and writing rules. Then publish a long post that shows results first and explains the tool second, and keep the buzz going with a user-results post each week.

Grade B: the playbook is clear, few people know about it, and nobody has copied it yet. But the stars mostly come from the author's own earnings proof and distribution on Chinese X. Followers who lack a proven niche can only expect one or two hundred stars like similar projects; copyright of the source material is also a risk. Circulating in small circles
Data (updated daily) · Repo created 2026-10-26 · 804 stars · 7 days +246
GitHub · stars
20040060080010-2810-3111-0311-0511-08804
Data 2026-10-28 → 2026-11-08 (12 days, 12 observations). Points before 10-28 come from deeply / archive backfill, not every day has one

On Oct 27 at 8 p.m., a Chinese X blogger with just over 5k followers posted a long article titled "Officially open-sourced! Using this skill to fully automate WeChat Channels selling, I sold over 4000 in one day." The next day, his GitHub repo, created only the day before, had gained 264 stars. This article explains what the Skill is, where the stars came from, why comparable projects with the same tech got only a fifth of its stars, and which parts to learn if you want your own open-source project to take off the same way.

One sentence to the Agent, out comes a Jianying draft

story-studio is a Chinese Skill for Claude Code, Codex, and Cursor. The usage the author demonstrates in the long post is this one sentence: "Use $story-studio, write only a spoken-narration script about the medical pioneer Lin Qiaozhi... First verify the key dates and figures of her life, then give me 3 different golden opening hooks to choose from." The Agent pulls several openings from the built-in hook library, such as the "consecutive numbers" type: "Lost her mother at 5, refused marriage at 18, practiced medicine for 60 years, personally delivered 50k+ babies..."

Once you pick an opening, it runs the rest of the pipeline: it writes the script, generates the voiceover with Doubao speech synthesis, aligns subtitles to the audio word by word locally with sherpa-onnx, splits the storyboard and generates images in one of three art styles (historical realism, thick-paint comic, black-and-white documentary), and finally exports a Jianying Pro draft through the open-source library pyJianYingDraft, with a slow push-in keyframe already applied to every image. You open Jianying to fine-tune and export.

It targets a very specific niche: spoken-narration accounts on WeChat Channels that cover history and biography, with a middle-aged and older audience and book affiliate links under the videos. In the long post the author says biography and social-science books sell for ¥49 to ¥88, with commissions of 30% to 50% (the author's own claim, which I couldn't verify).

The stars came from one long post

DateDaily new starsWhat happened
10-260Repo created, only one commit: "initial release"
10-27+35Long post published on X, Beijing time 20:05
10-28+264First day of the post's spread; Trendshift Python chart #25, its only appearance on a chart
10-29+108Author reposts follower feedback
11-01+67Author publishes a sequel, "Step-by-step spoon-feeding! Full practical guide to 4000+ in single-day WeChat Channels sales"
11-02 to 11-0615 to 50 a daylong tail

Source: Trendshift daily table; GitHub. 11-06 is 781 stars and 171 forks. It has never made GitHub's main trending page.

The first long post reached about 506k views and 2787 likes by 11-06, roughly 100 times the author's follower count. The sequel got 138k views. In Nov 1, another Chinese AI blogger, @DDJCXX, posted a roundup titled "8 Skills that let Claude Code make videos," with 107k views, which Trendshift counted as one mention of this repo. Beyond that are secondary write-ups on blogs, several navigation sites, and a YouTube explainer video. There's nothing on HN, Reddit, English-language communities, or mainstream media.

The fork rate is 22%, much higher than comparable projects. The reason isn't that people are modifying it: the README tells you to "have your Agent clone it into the skills directory," so many people forked it as soon as they installed it. I spot-checked 5 forks, and none had added a single commit beyond the original (GitHub, 11-06).

Why only a fifth of the stars, for a project with the same tech

The pipeline itself is nothing new. Doubao TTS, local alignment, image generation, and pyJianYingDraft for draft output: InsightCut, LingtiStudio, otopilot, and image-story-video-wizard all do this, with stars between 120 and 400 (GitHub, 11-06). The bigger general-purpose project MoneyPrinterTurbo has 140k stars, Pixelle-Video has nearly 30k, and CapCut's official product has an AI assistant and "AI text-to-video."

It adds two things.

First, the corpus. The repo includes the verbatim scripts from 5 top WeChat Channels accounts: 80 posts from 人间人物志, 80 from 闲读人间往事, 64 from 红颜旧事志, 37 from 通史观人物, 35 from 策山读书, plus 57 more history-narrative posts with hook annotations, and 12 style reference images. Readers aren't installing an "AI video tool" so much as a way to copy accounts that already work.

Second, a money story. Similar READMEs describe features. This one's long-form post opens its first section with "Results speak for themselves": view counts and sales screenshots before any tool talk. That's how it got out of the developer circle and into the side-hustle crowd, with 500k views far beyond what the tech community alone would have produced.

The author's X bio reads "Former big-tech growth lead | Million-GMV matrix player | Video sales steadily 2000+ per day | Xianyu/Xiaohongshu 3C category monthly profit 5w+ (paid teaching, full accompaniment)." In the long post he says the Skill "costs not a cent... and there's no high-priced paid group to fleece people," yet 10-29 he added a tip QR code and contact info to the repo. The repo itself doesn't earn money; what it brings is attention and trust, and the author's business lies outside it (inferred).

Did readers make it work?

Unknown. User reports are scattered: one says a video gained 200 followers, another says they got one working. A grounded comment in the long post's replies, from @YuanCongo6: "My method for history-figure accounts is almost identical to the blogger's... average views per video are only a few hundred on WeChat Channels and a few dozen on Douyin." So the tool can cut production time per video, but this niche is crowded, and the author himself writes: "It's not that I gave you a skill... that you can post randomly and it goes viral."

One more thing to watch: the corpus is verbatim transcripts from someone's WeChat Channels videos. The author changed the license to CC BY-NC-SA 4.0 (no commercial use) in Nov 3, but GitHub no longer detects a license type, and the earlier third-party check said MIT, so the records don't agree.

No one has produced a fork-level redesign of it. The similar projects all came earlier, so this isn't copying it.

If it were you

Bottom line: the pipeline can be copied. The stars came from "a ready-made corpus for one vertical" combined with "proof you made money in that vertical." Followers may not have the second, so it's worth trying, but first check whether you have results of your own.

Who it's for: people who have actually gotten numbers in a content niche (views, followers, or sales all count), who can build a pipeline with Claude Code or Codex, and who can publish long posts on Chinese X, Jike, or Xiaohongshu.

Who it's not for: people who can only build a pipeline with no niche results (you'd end up one of the 100 to 200-star clones); people who want a general "AI video generator" (MoneyPrinterTurbo and CapCut have that covered); and people who want another "history figure stories" project (the corpus and narrative are already taken).

How to do it: change the niche, keep the pipeline. Candidates: TCM wellness, personal finance education, legal awareness, English-language history accounts, or output formats like Xiaohongshu image-text posts or Douyin talking-head videos. Organize 5 top accounts' content in that niche into writing rules and a hook library (don't dump other people's full verbatim scripts; copyright is this project's biggest risk), add your own proven style or templates, and package it as a Skill you can install in one line.

How to get users: follow its sequence. Publish one long post; in section one, show your own results screenshot; section two covers the pain point; section three gives a copy-paste prompt; put the repo link at the top. Over the following week, repost user success reports or publish a follow-up every two or three days, and each one pulls stars back up a bit. Also find bloggers making "Claude Code video Skill" roundups and try to get included.

When to move: the "Agent Skill for content" wave started in October, and roundup posts are still coming out. Shipping before year-end is best. Once official tools like CapCut or Jimeng make "topic to finished video" a standard feature, the tool alone won't carry the story (inferred).

Signs you've misread it: ① a week after your long post you have fewer than 200 stars, meaning the hook isn't strong enough or nobody wants that niche; ② over the next month or two a batch of "[niche] Skill + make-money long post" repos appear, mostly stuck at a few hundred stars, meaning the formula is oversaturated; ③ story-studio gets taken down after a copyright complaint over its corpus, meaning "packaging other people's hits" doesn't work and you need your own corpus.

GitHub repo ↗

Research notes: competitor table, acquisition evidence, full research report
Competitors
NameWhereLaunchedScaleHow it differs from this one
MoneyPrinterTurboOpen source2024-03140k starsGeneral topic-to-MP4 video, no niche corpus, no CapCut draft output
OpenMontageOpen source2026-0377.6k starsGeneral agentic video production system, mostly English, not aimed at the Chinese sales niche
Pixelle-VideoOpen source2025-1129.8k starsGeneral fully automated short-video engine with no vertical viral-writing DNA
ArcReelOpen source2026-026,172 starNovel/script to storyboard, video, and CapCut drafts, leaning toward short dramas and comics
huashu-art-motionOpen source2026-106,389 starContemporaneous Claude Code video Skill that uses code for art animation, not talking-head or image-text
image-story-video-wizardOpen source2026-09408 starClosest match: a Codex image-text story-video skill that generates audio before images, but without a niche corpus or the author's monetization narrative
jianying-editor-skill (isYangs and others)Open source2026-03386 starOnly handles CapCut editing and drafts, not topic selection or copywriting
InsightCut / LingtiStudio / otopilot / VibefilmingOpen source2026120 to 200 starsNearly identical technical flow (script to storyboard, voiceover, drafts), with no content assets or distribution, and one-fifth of its stars
CapCut AI assistant / AI text-to-videoBig-company features2026-04 (AI assistant)All CapCut usersOfficial natural-language editing, with no vertical-niche writing DNA or viral benchmark library
Where users come from
  • Verified the author's own X long post: posted at x.com/Tanghulu188/status/2115052176968159627,10-27, ❤2787 🔁361 👁505,893; the author had about 5,116 followers; GitHub gained +264 stars the next day
  • Verified the author's follow-up and user reports: 11-01 "Step-by-step guide! Single-day WeChat Channels sales monetization 4000+" 👁137,965, corresponding to +11-01 and +67 stars; 10-29 and 11-04 quoted fan feedback about follower gains
  • Verified Chinese AI creator roundup posts: @DDJCXX 11-01 "8 Skills that make Claude Code produce videos" 👁107,200 (Trendshift counts this as a mention in this database); @wanerfu, @iBigQiang, @ModengSir reposted and tested them
  • Verified secondary write-ups, directory sites, YouTube commentary: doc.gpt88.cc write-up, gitrank.cc, trendar, proskills.md listing, YouTube nWri25-ECcM; traffic contribution not quantified
  • Verified author monetization: funnel to paid coaching: X bio says "paid teaching, full accompaniment"; 10-29 submission added a tip and contact info; the long post says the back office guides people into a WeChat Work group or community

Why konlu/story-studio (Story Studio) took off

Channel: GitHub. Research date 2026-11-06. Data sources are noted after each item; "unverified" means no third-party evidence was found.

Bottom line

It rode on the author "Xia Mu GROW" (@Tanghulu188) posting a make-money long post on Chinese X, titled "Officially open-sourced! Using this skill to fully automate WeChat Channels sales, I sold 4000 in one day" with about 506k views. The stars came from that post and a follow-up 5 days later, not from the tech community spreading it on its own. The real differentiator isn't the CapCut draft technology. It's that the author packaged an already-proven niche, "WeChat Channels elderly history/figure stories + book sales," into the project: verbatim scripts from 5 top Channels accounts totaling 370+ viral posts, plus style reference images. Readers came for the "pipeline that makes money," not for the tool itself.

1. Data: how the stars grew

Date (UTC)Daily new starsNew forks that daywhat happened
10-2600Repo created, first commit "initial release"
10-27+35+34Long post published on X at 12:05 UTC (20:05 Beijing time)
10-28+264+52First day of the post's spread; Trendshift Python chart #25 (its only appearance)
10-29+108+26Residual momentum; the author reposted user feedback
10-30 to 10-31+46 / +25Decline
11-01+67+13Author's follow-up "Step-by-step guide! Single-day WeChat Channels sales monetization 4000+ complete practical guide"; same day, @DDJCXX's "8 Skills that let Claude Code make videos" roundup post
11-02 to 11-06+50 / +38 / +26 / +15 / +26long tail

Sources: Trendshift repo page trendshift.io/repositories/322347 (daily table); our github repo_day table (10-28 226 stars, 11-06 755 stars); GitHub API live values 11-06 781 stars / 171 forks.

  • Never made GitHub's main trending page (data card trending_days_any=0; the repo was also less than 60 days old, so it couldn't have qualified anyway).
  • Fork ratio is 22%, because the README and long post both tell users to "git clone into the skills directory," or have their agent clone it. Of 5 forks sampled at random, every ahead_by was 0, meaning verbatim copies with no one modifying them (GitHub compare API). So high forks show people installed it, not that anyone is building on it.

2. Where users come from (growth tactics)

ChannelEvidenceConfirmed?
The author's own X long post (main channel)x.com/Tanghulu188/status/2115052176968159627, posted 2026-10-27, ❤2787 🔁361 💬137 👁505,893 (live from the x database, 11-06). The author has only about 5,116 followers (from the long-post page), so this post's views are about 100 times his follower count. The spread came from the "sold 4000 in one day" hook.Yes
Author's follow-upx.com/Tanghulu188/status/2116859493967393176, posted 11-01, ❤784 👁137,965, corresponding to a 11-01-star recovery (+67)Yes
The author kept driving momentum with user success reports10-29 quoted a fan who "would follow to the death" (👁5,428); 11-04 quoted @Alon9nz "one video gained 200+ followers" (👁3,187); 11-04 posted a Channels product-selection thread (👁21,912)Yes
Chinese AI bloggers make roundups@DDJCXX (硅基废话)11-01 posted "8 Skills that let Claude Code make videos", ❤2034 👁107,200, and Trendshift counted it as a mention of this repo; @wanerfu 11-02 👁4,475; @iBigQiang 10-28 posted a hands-on demo video 👁622; @ModengSir 11-02 reposted the follow-up 👁422Yes (DDJCXX's post body is truncated; this database didn't see the full text where the repo appears, so go by Trendshift's attribution)
Secondary write-ups and directory sitesdoc.gpt88.cc's summary article (the author's income figures are noted as "not independently verified"); listed on gitrank.cc, trendar.org, proskills.md; YouTube commentary video "Making history short videos, AI sets up the CapCut drafts for you" (nWri25-ECcM, views not found); changqiqi.online/story-studio/ has a landing page (10-27 launched, apparently a showcase page made by the author or fans)Yes (the pages open; traffic contribution not verified)
Ads, HN, Reddit, medianone foundNo evidence

Where the money comes back (the author's own account): the author's X bio reads "former big-tech growth lead | million-GMV matrix operator | video sales steadily 2000+/day | Xianyu/Xiaohongshu 3C categories 5w+ monthly profit (paid coaching, full support throughout)". The long post ends with "I'm Xia Mu, follow me, let's learn money-making information arbitrage together"; the 10-29 commit added a tip jar and contact info (commit "docs: add sponsor funding, contact info"). The open-source skill is a lead magnet for his money-making IP: readers follow first, then get pulled into his paid coaching and community. The long post also spells out the monetization path: "the backend guides you into WeCom/community... average order value jumps from tens of yuan to hundreds or thousands." He earns from follower growth and courses, not from GitHub.

3. Competitors

NameWhereLaunchedScaleHow it differs
harry0703/MoneyPrinterTurboOpen source2024-03140k starsGeneral "topic → finished video" pipeline, outputs MP4, uses a material library for footage; no vertical corpus, does not generate JianYing drafts
calesthio/OpenMontageOpen source2026-0377.6k starsGeneral agentic video production system (12-stage pipeline), mostly English, not aimed at Chinese monetization niches
ATH-MaaS/Pixelle-VideoOpen source2025-1129.8k starsFully automated AI short-video engine, the largest comparable on Trendshift; general-purpose output, no hit-niche corpus
linyqh/NarratoAIOpen source2024-0811.7k starsAdds commentary to existing videos and re-edits them; different input
ArcReel/ArcReelOpen source2026-026,172 starTurns novels/scripts into storyboards, videos and JianYing drafts, leaning toward short dramas and comic-style series
alchaincyf/huashu-art-motionOpen-source Skill2026-106,389 starAlso a Claude Code video skill at the same time, but it uses code for artistic animation, not talking-head or image-text content
GuanYixuan/pyJianYingDraftOpen-source library2024-074,828 starThe underlying draft library this one depends on; just a tool
zenstory-ai/video-recap-skillsOpen-source Skill2026-05606 starFilm/TV commentary skill, also exports JianYing drafts
aaronyi97/image-story-video-wizardOpen-source Skill2026-09408 starThe closest one: a Codex-based image-text story video that generates audio first and then images, but with no niche corpus and no author monetization story
A batch of "JianYing skills" such as isYangs/jianying-editor-skillOpen-source SkillFrom ¥2026-03386 / 48 / 25 starOnly handles editing and drafts, not topic selection or copywriting
SkyNotSilent/insightcut, ruilisi/LingtiStudio, wj-sidiss/otopilot, VibefilmingOpen source2026Around 120 to 200 starsSame type: script or topic to storyboard, images, voiceover and JianYing draft, nearly identical tech, with one-fifth of its stars
JianYing AI assistant (official agent packaged as a Skill)Big-company features2026-04All CapCut usersThe official natural-language editing tool, plus the earlier "AI text-to-video" feature; no vertical-niche writing DNA (Geek Park, i.ifeng.com/c/8sge9A7XGBa)

Source: GitHub API (11-06 star count); Trendshift "similar projects".

4. What's the differentiation, and is it why it took off?

  • Nothing technically new: the core stack is Doubao TTS, local alignment with Coli (sherpa-onnx), image generation, and pyJianYingDraft for drafts with push/pull keyframes, the same as InsightCut and image-story-video-wizard. Those peers are close in tech and only reached 100 to 400 stars.
  • The real difference is content assets plus niche positioning: under modules/characterstory-writing/corpus/ in the repo are verbatim transcripts from 5 WeChat Channels accounts: 人间人物志 80 episodes, 闲读人间往事 80, 红颜旧事志 64, 通史观人物 37, 策山读书 35; history-writing/corpus has another 57 episodes, annotated with hooks. There are also 12 style reference images (via GitHub tree API). What it sells is "copy the middle-aged history accounts that already work", not "AI makes videos".
  • Then the author demos how he makes money: peer projects describe features, while he says "I sold 4000 in one day", which is why it spread into side-hustle and money-making circles. 500k views reach well beyond the tech crowd.
  • Bottom line: it works partly because of differentiation and partly because of the author's distribution. The author's own money-making story brings people in, and the niche corpus makes readers feel they can use it right away.

5. How many people can see it

  • "Spreading in small circles." It spread widely in Chinese X's AI and money-making circles (long post 506k views, sequel 138k, DDJCXX roundup 107k), and there are re-compiled blogs and directory sites. But no mainstream media coverage, no GitHub trending, and almost nobody in the English community mentions it. Searching x for story-studio returns high-liked English posts about other products.
  • The author publicly shows WeChat Channels sales income (hundreds to thousands of orders per episode, commission 30% to 50%, "sold 4000+ in one day"), all self-reported in screenshots; doc.gpt88.cc says these cannot be verified. The repo itself charges nothing.
  • The "WeChat Channels history/figure story sales" play is already crowded. A commenter under the long post, @YuanCongo6, said: "The way I run my history-figure account is almost identical to the blogger's... average views per video are only a few hundred on WeChat Channels, and only a few dozen on Douyin."

6. Copycats

No derivative copycat projects found. Searching GitHub for "WeChat Channels skill", "figure story skill", "history JianYing" turns up no same-design projects; the existing forks (including the renamed nongcunlige/LGC-story-studio) all have ahead_by of 0, meaning verbatim copies. Projects similar in nature mostly predate it, so none are clearly copying it.

7. What others can learn

  1. Using an open-source skill as a lead magnet for a money-making IP: first pull people in with the "I earned X a day with it" long post, then use GitHub stars as social proof, then attach paid coaching in the profile and a tip jar and contact info in the README.
  2. Differentiate on the corpus, not the pipeline: distill the top content from a proven vertical niche into writing DNA and a hook library, and plug it into a general pipeline. Anyone can copy the pipeline; the corpus plus proof that "this niche makes money" is what makes people bookmark it.
  3. Installation is a one-sentence instruction for the agent to clone it itself: the barrier to fork and clone is low, so conversion is high.
  4. Keep heat going with a series of user reports: the author posted feedback and sequels 10-29, 11-01, 11-04 in a row, each time pulling stars back up a little.

8. Still unclear

  • The author's claimed affiliate earnings are unverified (self-reported, no proof). The corpus scrapes verbatim transcripts from other people's WeChat Channels accounts, which carries copyright risk. The author 11-03 switched the license to CC BY-NC-SA 4.0, banning commercial use (commit chore(license)), but GitHub now detects it as NOASSERTION, while a third-party blog checked back when it was MIT, so the license is inconsistent before and after.
  • Real usage: 171 forks, but there's no way to tell how many people actually got it running and produced a video. User reports are sparse (@Alon9nz gained followers 200, @dxlg898 got one clip working).
  • How many stars the YouTube commentary videos and directory sites brought in has not been quantified.
  • The full text of the @DDJCXX roundup post was not read; whether this repo is on the list follows Trendshift's attribution.

This article was written by AI from public data and the data we collect daily. Numbers are sourced, and inferences are labeled.