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Value Prop That Converts

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AIDevGTM
value-prop-that-converts

Write a developer value proposition that is specific, provable, and free of puffery. Use when the messaging leans on "powerful," "better," "seamless," or "best-in-class," when claims have no proof, or when the same line is supposed to reach both the developer and the buyer.

Overview

PublisherAIDevGTM
Repositorygtm-cofounder
Skill namevalue-prop-that-converts
Stars
323
Forks
31
Bundled files
Instructions only
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.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by AIDevGTM on GitHub. Read the source before you install it.

Installation

Install the Value Prop That Converts 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/AIDevGTM/gtm-cofounder/tree/main/skills/06-value-prop-that-converts
  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/AIDevGTM/gtm-cofounder.git /tmp/gtm-cofounder
mkdir -p .claude/skills
cp -r /tmp/gtm-cofounder/skills/06-value-prop-that-converts .claude/skills/value-prop-that-converts
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Value Prop That Converts 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 Value Prop That Converts 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 Value Prop That Converts 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.

The value prop that converts

"Better" is sloppy thinking. Better how, along what dimension, by how much, proven by whom? Developers test every claim you make. Give them numbers or give them nothing.

Use this when: your value prop contains puffery, your claims aren't attributed, or you're trying to make one sentence do the job of two audiences.

The core idea

Developers have a finely tuned BS detector and they will verify you. Specificity is credibility. Every strong dev value prop is: specific + provable + spoken in their language.

Framework: the value-prop rules (Frankl)

  1. Never say "better." Say better how, by how much, versus what.
  2. Time savings must be specific. ❌ "saves developer time" · ✅ "8× faster builds, 2 hrs → 15 min" (attributed).
  3. Two kinds of time, speak to both:
    • Chronos (Alpha Dev): clock hours saved per week.
    • Kairos (Empowered CTO): calendar time, weeks off a release cycle, competitive edge.
    • The same product must land both. "Release fast or die" worked for developer and CTO.
  4. Every claim needs proof. A demo is the weakest proof (ideal conditions). An attributed testimonial (name + title + company + number) is the strongest. Anonymous quotes are assumed invented.
  5. Sell the category, not the solution. Talk about the problem and the need for "a tool like this"; don't proactively pitch features; it trips developer defenses.
  6. Never "pleased to announce" / "excited to share." No one cares how you feel.

Framework: the three dimensions of a dev value prop (Czakon)

A complete value prop answers all three, fast:

  • What is it?: category / known-incumbent comparison / plain statement ("a Datadog alternative," "CI for monorepos").
  • For whom / what use case?: the ICP and the job (from who-is-this-for).
  • Why you over the 10 alternatives?: the legitimate, provable reason to exist.

Headline = what is it. Subhead = for whom / what job. For dev tools, weight the how over the why. Developers often already know why they hurt.

The puffery detector: flag and replace

BannedWhy devs discount itReplace with
Powerfuleveryone claims itthe specific thing it does
Easy to usethey'll test it in 60stime-to-value with a number
Best-in-classsays who, by what metricthe source or the number
Seamless integrationunprovable in the abstractnamed integrations + logos
Industry-leadingsays nothingreal share / user counts
Platformhears: integration headachethe one job it does
Revolutionary / cutting-edgepure airname the actual technology

Proof hierarchy (weakest → strongest)

your claim  <  a demo  <  a benchmark you ran  <  a named user's attributed result

Spend your effort at the right end.

Mistakes that look reasonable

  • Adjective stacking: "powerful, seamless, intuitive." Three words, zero information.
  • One line, two audiences: a Chronos-only message loses the buyer; a Kairos-only message loses the adopter.
  • Unattributed social proof: "developers love us." Which developers? At which company?
  • Leading with the why: for most dev tools the pain is known; lead with the how and the proof.

Your next 30 minutes

  • Run your homepage copy through the puffery table. Delete or replace every hit.
  • Rewrite your #1 claim with a number and an attribution (even a single named user).
  • Write one Chronos line (hours/week) and one Kairos line (weeks/release). Make sure both exist.
  • State your value prop as the three dimensions: what · for whom · why you.

Built from real dev-tool GTM experience, with frameworks from Adam Frankl (The Developer-Facing Startup) and Jakub Czakon (markepear.dev). If you can't tell whether your value prop actually lands with a buyer, get a human read. Reach out to me on LinkedIn.

Frequently asked questions

What does the Value Prop That Converts AI skill do?

Write a developer value proposition that is specific, provable, and free of puffery. Use when the messaging leans on "powerful," "better," "seamless," or "best-in-class," when claims have no proof, or when the same line is supposed to reach both the developer and the buyer.

Why use Value Prop That Converts on TypingMind?

Because you install it once and use it with any model. Value Prop That Converts 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 Value Prop That Converts in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/AIDevGTM/gtm-cofounder/tree/main/skills/06-value-prop-that-converts. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Value Prop That Converts?

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 Value Prop That Converts?

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

Is the Value Prop That Converts AI skill free?

Yes. It is published on GitHub by AIDevGTM 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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