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Audience Tailoring

Community
Productfculty-aipm
audience-tailoring

Use this skill when the user asks to "tailor this for different audiences", "write this for an exec vs. engineering", "adapt this message for different stakeholders", "translate this for a non-technical audience", "help me communicate this to [specific role]", or has an existing document or message and wants to produce multiple audience-specific versions. This is a rewriting skill — it takes existing content and adapts it, not generates from scratch.

Overview

PublisherProductfculty-aipm
RepositoryPM-Copilot-by-Product-Faculty
Skill nameaudience-tailoring
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 Audience Tailoring 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/audience-tailoring
  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/audience-tailoring .claude/skills/audience-tailoring
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Audience Tailoring 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 Audience Tailoring 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 Audience Tailoring 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.

Audience Tailoring

You are adapting existing content for different audiences. The same underlying information needs to be structured, scoped, and toned differently depending on what the audience needs to do with it.

Framework: Pyramid Principle (structure matches audience's decision-making needs), Lenny's 14 PM habits (hunting for misalignment, clarity as core PM skill).

Step 1 — Load Context

Read memory/user-profile.md for stakeholder details — their roles, communication styles, sensitivities, and history. The more specific the memory, the more tailored the output.

Step 2 — Understand the Source Content

Identify:

  • What is the content being adapted? (PRD section, status update, decision memo, research synthesis?)
  • What is the core message or decision the content contains?
  • What is the source audience's level of technical or product context?

Step 3 — Audience Analysis

For each target audience, establish:

Executive / C-level:

  • Needs: Decision, risk, outcome — in that order
  • Reads for: "What do I need to do or approve?"
  • Allergic to: Details, jargon, long context, buried asks
  • Format: Pyramid Principle — conclusion first, support second

Engineering / Technical team:

  • Needs: Context (why), constraints (what not to do), decision points (where they have input)
  • Reads for: "What does this mean for my work? What decisions do I need to make?"
  • Allergic to: Over-specified implementation, condescension, lack of technical depth
  • Format: Context → What's being built → Technical unknowns → Asks

Design:

  • Needs: User problem, user flows, principles (not implementation)
  • Reads for: "What experience are we creating? What's the user's mental model?"
  • Allergic to: Wireframe-level specs in PRDs, solutions disguised as requirements
  • Format: User stories, flows, principles, open questions

Customer:

  • Needs: "What's in it for me?" — tangible benefit in plain language
  • Reads for: Understanding what changed and why it matters to them
  • Allergic to: Internal jargon, process details, corporate hedging
  • Format: Narrative — "you told us X, so we built Y, here's how to use it"

Board / Investors:

  • Needs: Market context, competitive position, strategic rationale, progress vs. plan
  • Reads for: "Is this team making good product bets?"
  • Allergic to: Feature details, tactical minutiae, defensive framing
  • Format: Insight → Strategic rationale → Progress → Next bet

Customer Success / Support:

  • Needs: What changed, how to explain it, what questions users will ask, what to escalate
  • Reads for: "How do I talk about this with customers?"
  • Allergic to: Technical implementation details, strategic context they can't use
  • Format: What shipped → User impact → FAQs → Edge cases to escalate

Step 4 — Adapt the Content

For each target audience:

  1. Identify the most relevant subset of the source content
  2. Restructure the order to match the audience's reading priority
  3. Rewrite for vocabulary and depth level appropriate to the audience
  4. Add or remove context as needed
  5. Reframe any feature statements as user benefit statements (for external audiences)

Step 5 — Output

Produce the adapted version for each requested audience, clearly labeled. For each version, include a brief note on what was changed and why — this helps the user learn the tailoring principles for future communications.

Frequently asked questions

What does the Audience Tailoring AI skill do?

Use this skill when the user asks to "tailor this for different audiences", "write this for an exec vs. engineering", "adapt this message for different stakeholders", "translate this for a non-technical audience", "help me communicate this to [specific role]", or has an existing document or message and wants to produce multiple audience-specific versions. This is a rewriting skill — it takes existing content and adapts it, not generates from scratch.

Why use Audience Tailoring on TypingMind?

Because you install it once and use it with any model. Audience Tailoring 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 Audience Tailoring 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/audience-tailoring. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Audience Tailoring?

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 Audience Tailoring?

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

Is the Audience Tailoring 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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