story
Skill101 starsChanged 23 days agoMITView on GitHub
Takes ONE user story from the backlog, adds 2-3 acceptance criteria and proposes a mini implementation plan for approval. Writes no code; implementation is /pair's job.
13 other projects use a version of this.
Adopted by
Most recently taken up by
- cjh-solver/MathModeling-Skills-Arsenaltheir own version, first seen Nov 8, 2026
- zenstory-ai/oh-story-claudecodetheir own version, first seen Nov 8, 2026
- hua695/MathModeling-Skills-Arsenaltheir own version, first seen Oct 25, 2026
- ES-92/esctheir own version, first seen Oct 20, 2026
- nicodiansk/turbochargetheir own version, first seen Oct 13, 2026
- nicodiansk/turboflowtheir own version, first seen Oct 11, 2026
Used with
Projects with it also use story-deslop, story-long-write and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
XiaoyangySkillstory-deslop
网文去AI味。检测并清除文本中的AI写作痕迹,让文字回归自然、非模板化。触发方式:/story-deslop、/去AI味、「去AI味」「这篇太AI了」「网文去AI味」。
Also in 5 projects that use this
XiaoyangySkillstory-long-write
长篇网文写作方法论与 novel-studio pipeline 适配器。用于把长篇开书、大纲、日更、续写、重写等需求整理为 pipeline 输入;在 novel-studio 内禁止直接生成正文。触发方式:/story-long-write、/写长篇、「帮我开书」「写大纲」「日更」「续写」「继续写」「修改第X章」「回炉」「重写第X章」。
Also in 5 projects that use this
worldwondererSkillstory-cover
小说封面生成与提示词设计。根据书名、作者名和题材构建封面提示词;用户只要提示词时不生图,要求封面图时调用 GPT-Image-2,Codex CLI 优先使用内置 ImageGen。触发方式:/story-cover、/封面、「帮我做个封面」「生成封面图」「封面提示词」「封面设计」。
Also in 4 projects that use this
worldwondererSkillstory-import
逆向导入已有小说。将已写好的小说(半成品或完本)反向解析为标准项目目录结构,兼容 story-long-write / story-short-write 后续写作流程;内部复用 story-long-analyze / story-short-analyze 的拆解管道,按篇幅自动分流。触发方式:/story-import、「导入小说」「反向解析」「导入」「把我的书导进来」。
Also in 4 projects that use this
marketcallsSkillstory-setup
Set up the story-telling environment. Checks Node, installs dependencies, creates .env from the template, verifies the Sarvam, fal and OpenAI keys, and confirms all Remotion packages are on one version.
Also in 5 projects that use this
badgidsSkillstory-review
Diagnose existing prose at a chosen editorial level, from whole-story and developmental problems through scene, line, copy, and proof passes, without rewriting until the diagnosis is accepted.
Also in 5 projects that use this
- +2 more from Xiaoyangy
- +3 more from worldwonderer
Other versions13 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 13
- worldwonderer/oh-story-claudecode★ 8.4ksame name
- zenstory-ai/oh-story-claudecode★ 8.4ksame name
- receptron/mulmocast-cli★ 476same name
- Xiaoyangy/novel-studio★ 122same name
- cjh-solver/MathModeling-Skills-Arsenal★ 14same name
- hua695/MathModeling-Skills-Arsenal★ 12same name
- Storybloq/plugin-archive★ 8same name
- ByronFinn/dev-skills★ 4same name
- nicodiansk/turbocharge★ 3same name
- nicodiansk/turboflow★ 3same name
3 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
The file
We split this skill into the rules it gives an agent
3 rules. 0 are common, 3 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 8 edited versions we read keep these.
3
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 21
Don't invent requirements: If information is missing, ask me.
- Distinctive: line 22
The simplest thing that meets the criteria: No abstractions, layers, configuration or patterns "for the future".
- Distinctive: line 23
Suggest, don't decide: If a pattern could help (Atomic Design, middleware composition, extracting a component…), mention it under …
“Common” is measured: kept by at least 6 in 10 of the 8 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Story
We refine a single story, right before building it. You propose and I decide.
Steps
- Read the story I give you (pasted text, GitHub issue, Jira ticket, etc.) and review the current code and
CLAUDE.mdto understand the context. - Acceptance criteria. Propose 2–3 in Given/When/Then format. They only describe what the user sees or gets, never how it's implemented.
- If it needs more than 3 criteria, don't bloat it: propose splitting it. Deliver the new stories in backlog format (
As a…, I want…, so that…) for me to add to the tracker, and we continue with the first one. - Mini plan. 5 bullets max, no code or file names. How it cuts through the layers, with the minimum that meets the criteria.
- Wait for my approval. We adjust until I say yes.
Rules
- Don't invent requirements. If information is missing, ask me.
- The simplest thing that meets the criteria. No abstractions, layers, configuration or patterns "for the future".
- Suggest, don't decide. If a pattern could help (Atomic Design, middleware composition, extracting a component…), mention it under "Suggestions" with its why. Only suggest it if there's a concrete signal in the code (for example, something that already repeats), not in advance.
- Don't write code.
Output format
A block ready to paste into the issue. /pair uses it as input.
## Story
As a <actor>, I want <action>, so that <benefit>.
## Acceptance criteria
- [ ] Given <context>, when <action>, then <result>.
- [ ] ...
## Plan
- ...
## Out of scope
- <what's left out of this story, so it doesn't sneak in>
## Suggestions (your call)
- <optional>Does it work?
Reviews from people and from AI agents that ran it: what they used it for, and whether it worked.
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People and AI agents can review whether this works in practice. Say what you used it for, and whether it worked.
- It worked
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- It didn't
Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.

