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Mk 051

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backtrue
mk-051

Comparing price acceptance across customer groups. Use when the task requires group-specific price distributions on a consistent basis. Apply this method to the specified inputs and verify the deliverable

Overview

Publisherbacktrue
Repositorythinkwithblack-skill
Skill namemk-051
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 051 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-051
  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-051 .claude/skills/mk-051
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Mk 051 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 051 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 051 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-051 | Comparing price acceptance across customer groups

For a regular chat, upload packs/mk-051.md. It includes the shared rules, this method, and required references

Purpose

This skill delivers: Group-specific price distributions on a consistent basis

Curve intersections, cost floors, and launch decisions are distinct tasks; a price intersection does not guarantee maximum profit

Required inputs

Available raw records: raw four-question price responses, respondent groups, product and question wording, offers, recruitment records, and cleaning rules

Method Steps

  1. Align product descriptions, quantities, the four price questions, currency, exposed offers, and sampling periods. Preserve each response's original group and identify overlap rather than treating the same person as two independent respondents
  2. Flag missing answers and contradictory price ordering under the established cleaning rule. If no rule exists, retain and flag the originals and compare results with and without contradictions; do not silently delete records to obtain intersections
  3. Use the same price grid and curve calculations for every group. Overlapping intervals, missing intersections, or rankings reversed by removing a few responses do not support stable price separation
  4. Differences that persist under comparable product terms and cleaning sensitivity support price or offer test candidates, followed by cost and actual purchase checks. CTR and completion rates describe recruitment response, not price acceptance
  5. Different offers or quantities invalidate a group-price explanation; rebuild comparable groups. Request the original four questions and product description rather than asking the customer to interpret curves

Calculation and Interpretation

At price p, the too-cheap curve is the share of valid four-question respondents whose too-cheap threshold is at least p; bargain uses the same direction. Expensive is the share whose expensive threshold is at most p; too-expensive uses that direction. PMC is the intersection of too-cheap and expensive; PME is the intersection of bargain and too-expensive. Discrete grids bracket crossings; do not invent exact intersections when none exist

Check example (hypothetical): A's interval is 800–1,000 and B's is 900–1,100. Retain the overlap and compare costs rather than automatically charging B more. Discovering that B saw a two-pack changes the finding to different product conditions and withdraws the group-price conclusion

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

Required output fields

OrderFieldHow to complete
1Price pointUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
2Valid response countUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
3Cumulative proportion for each questionUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
4Intersection definitionUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
5Interpretable resultUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
6Excluded/unprocessed countUse source evidence, an intermediate method result, or an explicit unknown; do not invent information
7LimitationsUse source evidence, an intermediate method result, or an explicit unknown; do not invent information

Verification cases

MK-051-C05 | A respondent's four price answers have a contradictory order

Expected: Retain and flag the original answers; report sensitivity separately under the established cleaning rules

MK-051-C06 | The curves do not have an intersection defined by the source

Expected: Deliver the distributions and the reason interpretation is unavailable; do not fabricate an intersection

Method sources

Source file: 營業額提升主要關鍵(一)縱深橫寬產品/產品線企劃策略

Location: PSM

Source basis: extracted from course materials

Source URL: https://docs.google.com/presentation/d/1lIddPByRFVZeT-TR3CSaL_lEKkpJRloL6JQBLg1fO50/edit

English translation of source excerpt:

Van Westendorp's PSM (Price Sensitivity Measurement) fundamentally asks about the target consumer's acceptance of a price. It asks not only whether a price is expensive or cheap, but also which price is "too cheap"

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 051 AI skill do?

Comparing price acceptance across customer groups. Use when the task requires group-specific price distributions on a consistent basis. Apply this method to the specified inputs and verify the deliverable

Why use Mk 051 on TypingMind?

Because you install it once and use it with any model. Mk 051 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 051 in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/backtrue/thinkwithblack-skill/tree/main/en/skills/mk-051. 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 051?

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 051?

As many as you like. As long as a model supports skills, you can use Mk 051 with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Mk 051 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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