User Story Decomposition

Community

Productfculty-aipm

user-story-decomposition

Use this skill when the user asks to "write user stories", "decompose this into user stories", "break this into stories", "write acceptance criteria for this feature", "turn this PRD into stories", "create a story map", "help me write stories for sprint planning", or has a feature or PRD and wants to decompose it into shippable units for engineering. Do NOT use this skill to write a full PRD — use prd-authoring for that.

Overview

Publisher	Productfculty-aipm
Repository	`PM-Copilot-by-Product-Faculty`
Skill name	`user-story-decomposition`
Stars	80
Forks	34
Bundled files	Instructions only
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.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by Productfculty-aipm on GitHub. Read the source before you install it.

Installation

Install the User Story Decomposition 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/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/user-story-decomposition
Enable the skill in any chat where you want it available.

Store

Installed

Skills

Add skills

Import one or more skills from a public GitHub folder or a local .skill or .zip archive, or SKILL.md file.

From GitHub URLFrom .skill, .zip, or SKILL.md

GitHub repo or folder

https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/user-story-decomposition

Points to a single skill folder, or any folder that contains multiple skills. Public repos only.

CancelContinue

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/Productfculty-aipm/PM-Copilot-by-Product-Faculty.git /tmp/PM-Copilot-by-Product-Faculty
mkdir -p .claude/skills
cp -r /tmp/PM-Copilot-by-Product-Faculty/skills/user-story-decomposition .claude/skills/user-story-decomposition

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

Use it in TypingMind

Enable User Story Decomposition 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 User Story Decomposition 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 User Story Decomposition 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 Story Decomposition

You are helping the user break a feature or PRD into well-formed user stories ready for sprint planning and engineering estimation. Good stories are independently shippable, testable, and small enough to fit in a sprint.

Framework: Shape Up (small, vertically sliced bets), INVEST criteria (Independent, Negotiable, Valuable, Estimable, Small, Testable).

Step 1 — Load Context

Read memory/user-profile.md for product context and team norms. Read the PRD or feature description provided.

Step 2 — Identify the Feature Boundaries

Before decomposing, establish:

What is the full scope of the feature?
What is explicitly out of scope (from the PRD)?
What are the key user flows (from the PRD or user input)?

Step 3 — Story Map Structure

Build a story map with three levels:

Epics (user goals): The high-level things a user is trying to accomplish. These are the columns of the story map.

Stories (user tasks): Specific actions a user takes to achieve the epic. These are the rows under each epic.

Sub-tasks (engineering tasks): The technical work needed to implement each story. These are not user stories — they go into the engineering ticket.

Step 4 — Write User Stories (INVEST Format)

For each story, write in this format:

User Story: As a [specific user type from personas], When [triggering situation / context], I want to [action], So that [outcome / progress made].

Acceptance Criteria (Gherkin format):

Given [precondition], When [action], Then [expected result]
Given [precondition], When [action], Then [expected result]

Definition of Done:

[Engineering-level done criterion]
[QA-testable criterion]
[Design-signed-off criterion if applicable]

Story size estimate: [XS / S / M / L / XL — based on typical team velocity from memory if available]

Step 5 — INVEST Check

For each story, verify:

Independent: Can this story be shipped without other stories?
Negotiable: Is the scope negotiable, or is it a fixed requirement?
Valuable: Does this story deliver user value by itself, or only when combined with others?
Estimable: Does engineering have enough information to estimate it?
Small: Can it be completed in one sprint? If not, split it.
Testable: Can QA verify it with the acceptance criteria above?

Flag any story that fails INVEST and suggest how to fix it.

Step 6 — MVP vs. Full Scope

After listing all stories, identify the minimum set that delivers the core user value. Label each story:

MVP — must ship for the feature to be minimally useful
V1 — should ship in the same release but not strictly blocking
V2 — can ship in a follow-up iteration
Nice to have — valuable but deprioritized for now

Step 7 — Output

Produce:

Story map (epics as columns, stories as rows)
Full user stories with acceptance criteria for MVP stories
Brief descriptions for V1 and V2 stories (full write-up can come later)
Story size estimates
Sprint breakdown suggestion: which stories go in Sprint 1, Sprint 2, etc.

Frequently asked questions

What does the User Story Decomposition AI skill do?

Why use User Story Decomposition on TypingMind?

Because you install it once and use it with any model. User Story Decomposition 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 User Story Decomposition in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/user-story-decomposition. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use User Story Decomposition?

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 User Story Decomposition?

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

Is the User Story Decomposition AI skill free?

It is published on GitHub by Productfculty-aipm. Check the repository for licensing terms. 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 Story Decomposition

Step 1 — Load Context

Step 2 — Identify the Feature Boundaries

Step 3 — Story Map Structure

Step 4 — Write User Stories (INVEST Format)

Step 5 — INVEST Check

Step 6 — MVP vs. Full Scope

Step 7 — Output

Frequently asked questions

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