Problem Framing

Community

Productfculty-aipm

problem-framing

Use this skill when the user asks to "frame a problem", "define the problem", "write a problem statement", "articulate the user problem", "what problem are we solving", "help me think through the problem", "is this the right problem to solve", "clarify the problem", or when a user presents an idea and needs help distinguishing the problem from the solution. Do NOT use this skill if the user is ready to write a full PRD — use the execution/prd-authoring skill or /write-prd command instead.

Overview

Publisher	Productfculty-aipm
Repository	`PM-Copilot-by-Product-Faculty`
Skill name	`problem-framing`
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 Problem Framing 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/problem-framing
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/problem-framing

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/problem-framing .claude/skills/problem-framing

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

Use it in TypingMind

Enable Problem Framing 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 Problem Framing 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 Problem Framing 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.

Problem Framing

You are helping the user articulate the problem they're solving with precision. A sharp problem statement prevents the most common PM mistake: building a solution looking for a problem.

Frameworks: Teresa Torres (problem vs. solution distinction), Marty Cagan (the right problem), Bob Moesta (demand-side thinking).

Step 1 — Load Context

Read memory/user-profile.md and context/product/personas.md to ground the problem in the user's specific product and user segment.

Step 2 — Separate Problem from Solution

Before anything else, check: is what the user presented a problem or a solution?

Solution in disguise: "Users want dark mode" → Ask: what problem does dark mode solve?
Problem stated as a metric: "Retention is dropping" → Ask: what user struggle causes this?
Problem stated as a feature request: "Users asked for export" → Ask: what are they trying to do that export enables?

Redirect solution-framing to the underlying struggle.

Step 3 — Problem Statement Workshop

Write three alternative problem statements and present them for the user to react to:

Format for each: "[User segment] struggles to [action/task] when [context/trigger] because [root cause], which means [cost of the problem — time lost, goal not achieved, workaround required]."

Make the three versions differ in:

Scope (narrow vs. broad problem)
User segment (different personas)
Root cause (different underlying why)

Ask: "Which of these best captures the problem you're trying to solve? Or is the real problem something different?"

Step 4 — Problem Validation Questions

For the chosen problem statement, stress-test it:

Is it observable? Can you point to a user behavior that proves this problem exists?
Is it frequent? How often does this situation occur for affected users?
Is it severe? What does the user do when this problem hits? (Workaround = severe; ignore = not severe)
Is it growing? Is this problem getting worse, better, or staying flat?
Is it ours to solve? Does solving this fit our product's positioning and capabilities?

If any answer is "I don't know", flag it as an open question.

Step 5 — Problem Brief Output

Write a one-page problem brief:

Problem: [Chosen problem statement from Step 3] Who: [Primary user segment — specific, not generic] When: [The triggering situation — context in which the problem occurs] Current behavior: [What the user does today — the workaround or the abandonment] Cost of inaction: [What happens if we don't solve this — to the user and to us] Evidence: [What data, research, or observations support this problem existing] Open questions: [What we still need to learn to be confident in this problem] Is this the right problem? [Your recommendation — should we invest in solving this?]

Frequently asked questions

What does the Problem Framing AI skill do?

Why use Problem Framing on TypingMind?

Because you install it once and use it with any model. Problem Framing 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 Problem Framing 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/problem-framing. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Problem Framing?

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 Problem Framing?

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

Is the Problem Framing 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

Problem Framing

Step 1 — Load Context

Step 2 — Separate Problem from Solution

Step 3 — Problem Statement Workshop

Step 4 — Problem Validation Questions

Step 5 — Problem Brief Output

Frequently asked questions

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