Deliver User Stories

Organization

product-on-purpose

deliver-user-stories

Generates user stories in the standard persona, action, benefit story format from product requirements or feature descriptions. Use when breaking a feature into stories for sprint planning, writing tickets, or communicating scope to engineering. For testable Given/When/Then acceptance criteria on a story, use deliver-acceptance-criteria; for boundary and failure scenarios, use deliver-edge-cases.

Overview

Publisher	product-on-purpose
Repository	`pm-skills`
Skill name	`deliver-user-stories`
Stars	717
Forks	92
Bundled files	4
License	Apache-2.0
Links	Skill source Repository Homepage

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
4 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by product-on-purpose on GitHub. Read the source before you install it.

Installation

Install the Deliver User Stories AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/product-on-purpose/pm-skills/tree/main/skills/deliver-user-stories
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/product-on-purpose/pm-skills.git /tmp/pm-skills
mkdir -p .claude/skills
cp -r /tmp/pm-skills/skills/deliver-user-stories .claude/skills/deliver-user-stories

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Deliver User Stories in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Deliver User Stories on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Deliver User Stories is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

User Stories

User stories are concise descriptions of functionality from the user's perspective. They capture who needs something, what they need, and why - without prescribing how to build it. Good user stories enable teams to break large features into estimable, deliverable increments while maintaining focus on user value.

When to Use

After PRD approval, when breaking down features for implementation
During sprint planning to create actionable work items
When writing tickets for engineering teams
When communicating requirements to stakeholders in accessible terms
When prioritizing a backlog based on user value

When NOT to Use

You need deeper, QA-ready Given/When/Then coverage for a single story or slice -> use deliver-acceptance-criteria
You need the feature-wide catalog of boundary conditions and failure scenarios -> use deliver-edge-cases
The feature itself is not yet specified -> use deliver-prd first; stories should trace back to documented requirements
You want refinement-session outcomes (estimates, scope decisions, open questions) -> use iterate-refinement-notes

Instructions

When asked to create user stories, follow these steps:

Understand the Feature Context Review the PRD or feature description. Understand the overall goal, target users, and scope boundaries. User stories should trace back to documented requirements.
Identify User Personas Determine which users interact with this feature. Each story should be written for a specific persona, not generic "users." Different personas may need different stories for the same feature.
Break Down by User Goal Decompose the feature into distinct user goals. Each story should deliver a complete, valuable capability - something the user can actually do when the story is done.
Write Story Statements Use the format: "As a [persona], I want [action] so that [benefit]." The benefit clause is critical - it explains why this matters and helps prioritize.
Define Acceptance Criteria Write specific, testable criteria using Given/When/Then format. Acceptance criteria define "done" - if all criteria pass, the story is complete.
Apply INVEST Criteria Validate each story against INVEST: Independent, Negotiable, Valuable, Estimable, Small, Testable. Revise stories that don't meet these criteria.
Add Context and Notes Include relevant design references, technical considerations, and dependencies. These help implementers understand the full picture.

Output Format

Use the template in references/TEMPLATE.md to structure the output. A complete output carries, per story: Story Header; User Story Statement; Context & Background; Acceptance Criteria; Design Notes; Technical Notes; Dependencies; Out of Scope; and Open Questions where any remain. Multi-story documents nest these sections under one heading per story, as the example shows.

Quality Checklist

Before finalizing, verify:

Each story follows "As a... I want... so that..." format
Stories are independent (can be built in any order)
Acceptance criteria use Given/When/Then format
Each criterion is testable (someone can verify pass/fail)
Stories are small enough to complete in one sprint
No implementation details in the story statement
Benefit clause explains why this matters to the user

Examples

See references/EXAMPLE.md for a completed example.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Deliver User Stories AI skill do?

Why use Deliver User Stories on TypingMind?

Because you install it once and use it with any model. Deliver User Stories is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Deliver User Stories in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/product-on-purpose/pm-skills/tree/main/skills/deliver-user-stories. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Deliver User Stories?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Deliver User Stories?

As many as you like. As long as a model supports skills, you can use Deliver User Stories with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Deliver User Stories AI skill free?

Yes. It is published on GitHub by product-on-purpose under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

User Stories

When to Use

When NOT to Use

Instructions

Output Format

Quality Checklist

Examples

Bundled files

Frequently asked questions

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