Best use case
writing-user-stories is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Use when an agent needs to write user stories for a project
Teams using writing-user-stories should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/writing-user-stories/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How writing-user-stories Compares
| Feature / Agent | writing-user-stories | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Use when an agent needs to write user stories for a project
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Writing User Stories ## Overview Help Claude and subagents write properly formatted user stories for task definition. **Core principle:** User stories are formulaic ways of expressing user requirements. They identify the perosna of the actor, what they want to do, and what benefit are they hoping to gain from their actions. ## When to Use This Skill Use this skill when: - You are asked to write a user story - You are asked to plan a feature ## User Story Format As a PERSONA I want to DESCRIPTION_OF_ACTION So that DESCRIPTION_OF_BENEFIT. ### Examples As a non-technical stakeholder, I want to understand what changed in a release without reading code diffs so that I can communicate updates to customers effectively. As a new user, I want to see examples of AI-generated code before connecting my repository so that I understand the value proposition before committing to integration. As a home cook, I want to see that recipes have been tested by professional chefs so that I can know whether they are worth trying.
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