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Mk 006

Community
backtrue
mk-006

Prioritizing three lead selling points. Use when the task requires lead selling-point priorities and reasons for trade-offs. Apply this method to the specified inputs and verify the deliverable

Overview

Publisherbacktrue
Repositorythinkwithblack-skill
Skill namemk-006
Stars
249
Forks
24
Bundled files
2
LicenseMIT
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.

  • 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 006 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/backtrue/thinkwithblack-skill/tree/main/en/skills/mk-006
  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/backtrue/thinkwithblack-skill.git /tmp/thinkwithblack-skill
mkdir -p .claude/skills
cp -r /tmp/thinkwithblack-skill/en/skills/mk-006 .claude/skills/mk-006
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mk 006 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 006 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 006 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-006 | Prioritizing three lead selling points

For a regular chat, upload packs/mk-006.md. It includes the shared rules, this method, and required references

Purpose

This skill delivers: Lead selling-point priorities and reasons for trade-offs

Separate features, benefits, and evidence; do not claim exclusivity without competitor data

Required inputs

Available raw records: candidate product claims, supporting evidence, customer choice or lost-sale records, and competitor conditions

Method Steps

  1. Link each candidate benefit to product facts, verifiable evidence, the customer's current job, and actual competitor differences. Exclude unsupported, irrelevant, or unfulfillable promises
  2. Prioritize a condition that remarks or choice records show would block purchase, when the product can resolve it. If the product fails a necessary condition, change the offer rather than hiding the failure behind another attractive benefit
  3. Compare the remaining known trade-offs. For equally relevant benefits, favor direct evidence and a perceptible difference. Shared basic features remain supporting points; without competitor evidence, state owned capability rather than exclusivity
  4. Select up to three lead benefits addressing distinct important problems; deliver two if only two qualify. Internal votes express preference, not proof. If candidates cannot be distinguished, retain them and inspect an actual lost-sale/choice record or compare message response
  5. Re-rank after customer-task, competitor, or evidence changes. Move a former lead to support or remove it when differentiation or fulfillment disappears, identifying the replacement and its evidence

Calculation and Interpretation

For each benefit, deliver supporting fact → decision barrier resolved → lead/support/unresolved → reason another option was not selected → condition for changing rank. Do not invent weighted scores without established brand weights

Check example (hypothetical): a customer requires same-day pickup and verified stock exists, making pickup more relevant than packaging design. Stock updates show arrival in three days; remove the same-day promise despite its earlier internal vote count

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

Required output fields

OrderFieldHow to complete
1Factual featureUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
2Customer taskUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
3Tangible benefitUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
4Basis for comparisonUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
5Suitable angleUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
6Lead/supporting/to investigateUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
7ReasonUse source evidence, an intermediate method result, or an explicit unknown; do not invent information

Verification cases

MK-006-C05 | The specification is true, but no industry comparison data is available

Expected: Functional benefits may be proposed; do not claim the product is unique or number one

MK-006-C06 | The information consists only of technical terms

Expected: Explain their role under the known usage conditions first; do not invent unverified effects

Method sources

Source file: Meta廣告學程 101 讓AI幫你投出廣告

Location: USP

Source basis: extracted from course materials

Source URL: https://docs.google.com/presentation/d/19GaScd4rGE8V4iqPfemeK8-QAwbSIeOKGpB5OwwTMlo/edit

English translation of source excerpt:

Help identify the product's USP (Unique Selling Proposition). This is also your first opportunity to communicate with the AI. It is good if it identifies the point, but if it does not get what you mean, make sure to tell it your thinking

Bundled files

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

Frequently asked questions

What does the Mk 006 AI skill do?

Prioritizing three lead selling points. Use when the task requires lead selling-point priorities and reasons for trade-offs. Apply this method to the specified inputs and verify the deliverable

Why use Mk 006 on TypingMind?

Because you install it once and use it with any model. Mk 006 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 006 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/backtrue/thinkwithblack-skill/tree/main/en/skills/mk-006. 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 006?

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 006?

As many as you like. As long as a model supports skills, you can use Mk 006 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mk 006 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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