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Jtbd Building

Community
menkesu
jtbd-building

Builds features based on Jobs-to-be-Done theory using Bob Moesta's frameworks. Use when designing features, identifying customer jobs, understanding push/pull forces, or uncovering hidden needs beyond stated feature requests.

Overview

Publishermenkesu
Repositoryawesome-pm-skills
Skill namejtbd-building
Stars
406
Forks
120
Bundled files
Instructions only
Links
  • 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 menkesu on GitHub. Read the source before you install it.

Installation

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

1

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.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. 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.
2

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/menkesu/awesome-pm-skills.git /tmp/awesome-pm-skills
mkdir -p .claude/skills
cp -r /tmp/awesome-pm-skills/jtbd-building .claude/skills/jtbd-building
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Jtbd Building 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 Jtbd Building 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 Jtbd Building 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.

Jobs-to-be-Done Product Design

When This Skill Activates

Claude uses this skill when:

  • Designing new features
  • Understanding customer needs
  • Moving beyond feature requests
  • Identifying real jobs to be done

Core Frameworks

1. Jobs Theory (Source: Bob Moesta, JTBD Co-Creator)

Core Principle:

"People don't buy products, they hire them to make progress in their lives."

The Job:

  • Functional: What needs to get done?
  • Emotional: How do they want to feel?
  • Social: How do they want to be perceived?

2. Forces Diagram

Four Forces:

PUSH (away from current):
- Pains with current solution
- Frustrations

PULL (toward new):
- Attraction to new solution
- Expected benefits

ANXIETY (hesitation):
- Fear of new
- "What if it doesn't work?"

HABIT (inertia):
- "Current way works okay"
- Switching cost

Action Templates

Template: JTBD Analysis

markdown
# Feature: [Name]

## The Job
**When** [situation],
**I want to** [motivation],
**So I can** [expected outcome].

### Example:
When I'm planning my week,
I want to see all my commitments in one place,
So I can feel in control and not miss anything.

## Forces Analysis

### Push (Problems with Current)
- [Current pain 1]
- [Current pain 2]

### Pull (Attraction to New)
- [Desired benefit 1]
- [Desired benefit 2]

### Anxiety (Hesitations)
- [Worry 1: "What if..."]
- [Worry 2: "What if..."]

### Habit (Inertia)
- [Current habit 1]
- [Switching cost]

## Design for the Job

### Functional
[How feature helps get job done]

### Emotional
[How feature makes them feel]

### Social
[How it affects their image]

## Address Forces
- **Reduce anxiety:** [how]
- **Overcome habit:** [how]
- **Amplify pull:** [how]

Quick Reference

🎯 JTBD Checklist

Understand Job:

  • Situation identified
  • Motivation clear
  • Desired outcome defined
  • Job story written

Forces:

  • Push forces (current pains)
  • Pull forces (desired benefits)
  • Anxiety forces (hesitations)
  • Habit forces (inertia)

Design:

  • Solves functional job
  • Addresses emotional job
  • Considers social job
  • Reduces switching anxiety

Real-World Examples

Example: Milkshake Marketing (Bob Moesta)

Wrong Question: "How do we make better milkshakes?" Right Question: "What job is the milkshake being hired for?"

Discovery:

  • Morning commuters: Long, thick shake for entertainment during boring drive
  • Parents: Quick, thin shake to feel like good parent ("I got you a treat")

Result: Different products for different jobs


Key Quotes

Bob Moesta:

"People don't want a quarter-inch drill. They want a quarter-inch hole."

Clayton Christensen:

"When we buy a product, we essentially 'hire' something to get a job done."

Frequently asked questions

What does the Jtbd Building AI skill do?

Builds features based on Jobs-to-be-Done theory using Bob Moesta's frameworks. Use when designing features, identifying customer jobs, understanding push/pull forces, or uncovering hidden needs beyond stated feature requests.

Why use Jtbd Building on TypingMind?

Because you install it once and use it with any model. Jtbd Building 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 Jtbd Building in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/menkesu/awesome-pm-skills/tree/main/jtbd-building. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Jtbd Building?

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 Jtbd Building?

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

Is the Jtbd Building AI skill free?

It is published on GitHub by menkesu. 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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