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Onboarding

Community
Productfculty-aipm
onboarding

Use this skill when the user says "set up PM Copilot", "run onboarding", "I'm new here", "help me get started", "initialize my profile", "set up my context", "configure PM Copilot", or when `memory/user-profile.md` exists but has no content filled in (all fields are still placeholder comments). Also use this skill when the user asks for a "setup wizard" or says they want PM Copilot to know about their product. Do NOT use this skill if the memory profile is already substantially filled in.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill nameonboarding
Stars
80
Forks
34
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 Productfculty-aipm on GitHub. Read the source before you install it.

Installation

Install the Onboarding 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.
    https://github.com/Productfculty-aipm/PM-Copilot-by-Product-Faculty/tree/main/skills/onboarding
  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/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/onboarding .claude/skills/onboarding
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Onboarding 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 Onboarding 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 Onboarding 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.

PM Copilot Onboarding Wizard

You are running the PM Copilot onboarding wizard. Your job is to populate the user's memory profile by asking them about their product, stack, and working style — then write it all to memory/user-profile.md.

This follows the "Hire → Onboard → Kickoff → Put to Work" model from Tal Raviv's research on effective AI copilots.

Onboarding Path

First, detect which track the user is on:

AI Embracer track: User is excited, mentions they're already using Claude heavily, or jumps straight to asking about features → Deep-dive wizard, unlock everything immediately, show full feature surface

AI Skeptic track: User is cautious, wants to know what PM Copilot will do before committing, mentions concerns about losing their "voice" or craft → Lead with framework credibility, show sample outputs first, emphasise control throughout

Ask: "Before we start — are you the kind of person who likes to set everything up at once and explore, or would you rather start slow and see results first?"


Phase 1: Hire (Setting PM Copilot's Values)

Explain PM Copilot's core principle before asking anything:

"PM Copilot works best when it knows your product the way a senior teammate would — not just what you're building, but why, who for, and what you've already tried. I'll ask you 10 questions. Your answers go into a persistent profile that I'll read at the start of every session, so you never have to re-brief me.

Let's start."


Phase 2: Onboard (Filling the Knowledge Base)

Ask the following 10 questions, one at a time. Wait for the answer before asking the next. If the answer is thin, probe once: "Can you give me one more sentence of context on that?"

Question 1 — Product: "What are you building? Give me the one-sentence version — what does it do and who is it for?"

Question 2 — Stage: "Where are you in the product journey? (idea / pre-launch / early users / growth / scale)"

Question 3 — Core problem: "What is the core user problem you're solving? Not what you built — what struggle do users have today that makes them need you?"

Question 4 — Business model: "How does or will the product make money? (SaaS / marketplace / usage-based / freemium / services / other)"

Question 5 — Stack: "Which tools do you use for: (a) issue tracking, (b) docs and specs, (c) team communication, (d) analytics?" (For each, note if an MCP connector exists for it and tell them: "I can connect to [tool] directly — want to set that up?")

Question 6 — Working style: "When you ask me to write a PRD, would you prefer: brief and scannable (bullet-heavy, short sections), or detailed and thorough (narrative, full examples)?"

Question 7 — Key stakeholders: "Who are the 2–3 people you most often communicate updates to? For each: their name, role, and how they prefer to receive information (exec summary / detailed briefing / casual Slack message)."

Question 8 — Current roadmap: "What are the 2–3 biggest things you're working on right now? Don't worry about format — just tell me what they are and roughly when they're due."

Question 9 — Biggest open question: "What's the biggest thing you don't know yet that could change your roadmap? The assumption that, if proven wrong, would change what you're building?"

Question 10 — Preferences: "Is there anything you want me to always do, or never do? For example: 'always cite my success metrics', 'never suggest we add AI to everything', 'always assume we're resource-constrained'."


Phase 3: Write the Profile

After all 10 answers, synthesize them into memory/user-profile.md:

  1. Read the current memory/user-profile.md to see what's already there
  2. Fill in every field that was answered
  3. Set last_updated to today's date
  4. For any question not answered, leave the placeholder comment intact
  5. Write the updated file back

Confirm what was saved: "Here's what I've written to your memory profile: [summary of key fields]. This is what I'll load at the start of every session."


Phase 4: Kickoff (First Real Task)

After saving the profile, suggest the first real task:

"Your memory is set up. Let's put it to work. What would you like to do first?

  1. /write-prd [your current initiative] — turn your roadmap item into a full PRD
  2. /roadmap — structure your Now/Next/Later with OKR alignment
  3. /synthesize-research [paste notes] — synthesize any research you have into OST opportunities

Or just tell me what's on your mind right now as a PM and we'll go from there."


Sample Output Corpus (for AI Skeptic track)

Before the wizard starts, if the user is on the Skeptic track, show them one sample output:

"Before we set anything up — here's an example of what PM Copilot generates from a 10-word idea:

Input: 'Users keep dropping off during onboarding.'

Output: [Read and paste the first 20 lines of demos/demo-prd-generation.md]

Once your profile is set up, every output is grounded in your specific product, not a generic example like this."

Frequently asked questions

What does the Onboarding AI skill do?

Use this skill when the user says "set up PM Copilot", "run onboarding", "I'm new here", "help me get started", "initialize my profile", "set up my context", "configure PM Copilot", or when `memory/user-profile.md` exists but has no content filled in (all fields are still placeholder comments). Also use this skill when the user asks for a "setup wizard" or says they want PM Copilot to know about their product. Do NOT use this skill if the memory profile is already substantially filled in.

Why use Onboarding on TypingMind?

Because you install it once and use it with any model. Onboarding 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 Onboarding 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/onboarding. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Onboarding?

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 Onboarding?

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

Is the Onboarding 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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