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Messaging Hierarchy

Community
Productfculty-aipm
messaging-hierarchy

Use this skill when the user asks to "write our messaging", "create a messaging framework", "what should our tagline be", "value proposition", "messaging hierarchy", "how do we talk about our product", "craft our positioning statement", "what's our one-liner", or needs to develop the core language that communicates product value to different audiences.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill namemessaging-hierarchy
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 Messaging Hierarchy 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/messaging-hierarchy
  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/messaging-hierarchy .claude/skills/messaging-hierarchy
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Messaging Hierarchy 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 Messaging Hierarchy 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 Messaging Hierarchy 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.

Messaging Hierarchy

You are building a messaging hierarchy — a structured set of messages from the tagline down to the proof points, ensuring that everything the product says about itself is coherent, differentiated, and audience-appropriate.

Framework: April Dunford (Obviously Awesome — positioning-first messaging), Lenny Rachitsky (GTM), Donald Miller (StoryBrand).

Step 1 — Load Context

Read memory/user-profile.md for product context, ICP, and current bets. Read context/company/competitors.md for competitive context. Apply April Dunford's 5-component positioning as the foundation.

Step 2 — Positioning Foundation

Before messaging, confirm the positioning inputs (from competitive-positioning or positioning-five-component skills, or gather now):

  1. Competitive alternatives: What do users do today if they don't use us?
  2. Unique attributes: What do we do that alternatives don't?
  3. Value enabled: What can users accomplish because of those attributes?
  4. Who cares most: Which user segment gets the most from those attributes?
  5. Market category: What is the simplest way to categorize us that makes our value obvious?

These inputs drive every message down the hierarchy. If the inputs are wrong, the messages will be wrong.

Step 3 — Messaging Hierarchy Structure

Level 1 — Category frame (1 phrase): How do users understand what kind of product this is? The category frame sets the context that makes all other messages make sense. Example: "AI-native PM operating system" (not "Claude plugin", not "PM templates") Test: Does the category frame make the value obvious without explaining anything further?

Level 2 — Tagline / One-liner (5–10 words): The single sentence that captures what makes us different and valuable. Test: Could someone who has never heard of us understand what we do AND why they'd want it from this one line?

Level 3 — Value proposition (2–3 sentences): For the specific ICP, what problem do we solve and how? What does success look like? Test: Could a champion use this to explain us to their CEO in 30 seconds?

Level 4 — Proof points (3–5 bullets): Specific evidence that supports the value proposition. Concrete capabilities, outcomes, frameworks, or customer results. Test: Each bullet should make the tagline more believable, not just restate it.

Level 5 — Audience-specific messages: Adapted versions of Level 1–4 for each key audience:

  • ICP champion: What do they care about?
  • ICP buyer: What do they need to know to approve the purchase?
  • Anti-competitor (if relevant): How do we address the main competitor's claim?

Step 4 — Write the Hierarchy

For each level, write 2–3 alternative versions, then recommend the strongest with rationale.

Apply these tests to each:

  • Does it start with the customer, not with us? "You can now..." beats "We built..."
  • Is it specific? "Solo PMs who run discovery, write PRDs, and manage stakeholders alone" beats "product managers"
  • Does it differentiate? Would a competitor say the same thing? If yes, it's not differentiating.
  • Is it believable? Is the claim supported by the proof points below it?

Step 5 — Messaging for Skeptics vs. Embracers

Based on the attitudinal segmentation from the personas:

AI Embracer messaging: Emphasize power and speed. "Build like a 3-person PM team without the headcount." Lead with capabilities.

AI Skeptic messaging: Emphasize craft preservation and control. "Your judgment, amplified by Teresa Torres and Marty Cagan's frameworks." Lead with framework credibility and the "you stay in control" message.

AI Neutral messaging: Emphasize efficiency and ROI. "Cut PRD writing time from 4 hours to 20 minutes." Lead with before/after concrete outcomes.

Step 6 — Output

Produce:

  • Messaging hierarchy (all 5 levels with recommended version)
  • Alternative versions for levels 1–3 with commentary on each
  • Audience-specific adaptations (champion vs. buyer vs. skeptic)
  • Test results: which messages pass all 4 quality tests?
  • One-page messaging document ready to share with the team

Frequently asked questions

What does the Messaging Hierarchy AI skill do?

Use this skill when the user asks to "write our messaging", "create a messaging framework", "what should our tagline be", "value proposition", "messaging hierarchy", "how do we talk about our product", "craft our positioning statement", "what's our one-liner", or needs to develop the core language that communicates product value to different audiences.

Why use Messaging Hierarchy on TypingMind?

Because you install it once and use it with any model. Messaging Hierarchy 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 Messaging Hierarchy 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/messaging-hierarchy. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Messaging Hierarchy?

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 Messaging Hierarchy?

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

Is the Messaging Hierarchy 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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