Mk 027

Community

backtrue

mk-027

Audience and selling-point matching. Use when the task requires a Persona × USP communication-priority matrix. Apply this method to the specified inputs and verify the deliverable

Overview

Publisher	backtrue
Repository	`thinkwithblack-skill`
Skill name	`mk-027`
Stars	249
Forks	24
Bundled files	2
License	MIT
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.
2 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by backtrue on GitHub. Read the source before you install it.

Installation

Install the Mk 027 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/backtrue/thinkwithblack-skill/tree/main/en/skills/mk-027
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.

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/backtrue/thinkwithblack-skill.git /tmp/thinkwithblack-skill
mkdir -p .claude/skills
cp -r /tmp/thinkwithblack-skill/en/skills/mk-027 .claude/skills/mk-027

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

Use it in TypingMind

Enable Mk 027 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 Mk 027 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 Mk 027 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.

MK-027 | Audience and selling-point matching

For a regular chat, upload packs/mk-027.md. It includes the shared rules, this method, and required references

Purpose

This skill delivers: A Persona × USP communication-priority matrix

Hypotheses are useful but do not establish demographics or market share; do not fabricate interview content or customer experiences

Required inputs

Available raw records: customer questions, won/lost-sale and usage records, verified product claims, evidence, and the current task

Method Steps

Identify the current task and buying barrier from questions, won/lost sales, and usage records, then match verified benefits. Persona age or occupation is background, not automatic evidence of priorities
A benefit resolving the condition blocking the current choice becomes the lead for that context. Shared necessary features remain support rather than fabricated exclusivity
Split different tasks within one role into different angles. The same task across roles may share a message; demographic segments do not require invented differences
Connect situation → concrete problem → consequence → supported product outcome, then write a usable message with fact, benefit, and evidence. If the product cannot resolve the key barrier, change the offer or suitable audience
Replace the lead when new remarks or product conditions change the barrier, identifying the replaced statement. Request one actual lost-sale reason or original question rather than a full persona questionnaire

Calculation and Interpretation

The mapping records task evidence, candidate USP, why it matters now, usable proof, message, and replacement condition. Without outcome data, describe a supported function rather than inventing quantified results

Check example (hypothetical): store manager A worries about cleaning before closing, supporting an evidenced quick-cleaning benefit. Manager B worries about fitting the equipment, supporting actual dimensions and compatibility instead of the same generic efficiency claim

Decision rules authored by ThinkWithBlack, 2026-10-14; original course sources remain below

Required output fields

Order	Field	How to complete
1	Context and job evidence	Use the supplied source, calculation, or explicit unknown
2	Candidate USP	Use the supplied source, calculation, or explicit unknown
3	Use in this situation	Use the supplied source, calculation, or explicit unknown
4	Proof source	Use the supplied source, calculation, or explicit unknown
5	Priority and reason	Use the supplied source, calculation, or explicit unknown
6	Actual message	Use the supplied source, calculation, or explicit unknown
7	Conditions for changing priority and unknowns	Use the supplied source, calculation, or explicit unknown

Verification cases

MK-027-C05 | An order contains maternity and baby products

Expected: Do not immediately identify the buyer as a mother; separate the buying and using roles

MK-027-C06 | Different clues support two situations

Expected: Keep both candidates and request the data that would distinguish them

Method sources

Source file: 行銷策略實戰學程Day1-小眾就是大眾 × 精準 Persona × 數位資產

Location: Persona

Source basis: extracted from course materials

Source URL: https://docs.google.com/presentation/d/11Jecvwonn6oA3y3zexPkNOv0iAJuL_7uqERiSNexjjw/edit

English translation of source excerpt:

Niches form the mass market × precise Personas × digital assets

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

assets/check-context.py15 KB
assets/context-contract.json10 KB

Frequently asked questions

What does the Mk 027 AI skill do?

Audience and selling-point matching. Use when the task requires a Persona × USP communication-priority matrix. Apply this method to the specified inputs and verify the deliverable

Why use Mk 027 on TypingMind?

Because you install it once and use it with any model. Mk 027 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 Mk 027 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/backtrue/thinkwithblack-skill/tree/main/en/skills/mk-027. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Mk 027?

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 Mk 027?

As many as you like. As long as a model supports skills, you can use Mk 027 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mk 027 AI skill free?

Yes. It is published on GitHub by backtrue under the MIT license. 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

MK-027 | Audience and selling-point matching

Purpose

Required inputs

Method Steps

Calculation and Interpretation

Required output fields

Verification cases

Method sources

Bundled files

Frequently asked questions

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