write-requirements

Write user stories, acceptance criteria, and technical requirements for a feature or change. Use when defining what needs to be built.

6 stars

Best use case

write-requirements is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Write user stories, acceptance criteria, and technical requirements for a feature or change. Use when defining what needs to be built.

Teams using write-requirements 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

$curl -o ~/.claude/skills/write-requirements/SKILL.md --create-dirs "https://raw.githubusercontent.com/yu-iskw/llmops-demo-ts/main/.claude/skills/write-requirements/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/write-requirements/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How write-requirements Compares

Feature / Agentwrite-requirementsStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Write user stories, acceptance criteria, and technical requirements for a feature or change. Use when defining what needs to be built.

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

# Write Requirements

Write detailed requirements for the following feature:

$ARGUMENTS

## Requirements Format

For each requirement, produce:

### User Story

```text
As a [user type],
I want to [action],
So that [benefit].
```

### Acceptance Criteria

- [ ] Given [context], when [action], then [result]
      (Include happy path, error cases, and edge cases)

### Technical Requirements

- Data model changes needed
- API endpoints affected
- UI components affected
- Non-functional requirements (performance, security, accessibility)

### Out of Scope

- What is explicitly NOT included in this feature

## Context

This is for the llmops-demo-ts project — a chat-based AI agent application. Consider all layers: frontend (Vue.js), backend (Express), agents (LangGraph), and common (shared types).

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