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value-prop-builder

value-prop-builder is a skill for Claude Code from adidacta/pmf-detective. It costs 70 tokens per session (2,121 once invoked), scanned A, original, MIT.

A guided writing tool for defining a product’s value proposition—the short explanation of who it helps, what problem it addresses, and why people should choose it. It uses the Callout and Magnet framework to create several message options.

In plain words
What is it for?
Use it to draft value propositions, brand messages, product positioning, and explanations of why customers would buy. It generates three or four options for the user to choose from.
Why use it?
It helps turn information about an ideal customer profile into clear positioning and messaging, instead of starting with a blank page. It also checks whether the required ICP file exists first.

Skill for Claude Code

Written for Claude Code: allowed-tools in frontmatter. Also seen: names the AskUserQuestion tool.

Part of the pmf-detective plugin — 9 skills, 6 commands shipped together

not rated 18repo 28d ago A scan 70 tokens original MIT

Good fit Use it to draft value propositions, brand messages, product positioning, and explanations of why customers would buy. It generates three or four options for the user to choose from.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/adidacta/pmf-detective/value-prop-builder
View source ↗ adidacta/pmf-detective
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add adidacta/pmf-detective --skill value-prop-builder
Clone the repo
git clone --depth 1 https://github.com/adidacta/pmf-detective

Made for: Claude Code.

Or install pmf-detective, the plugin that ships this one along with the rest of its 9 skills, 6 commands.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for value-prop-builder

README.md
[![agentmods](https://agentmods.dev/badge/skills/adidacta/pmf-detective/value-prop-builder/github.svg)](https://agentmods.dev/skills/adidacta/pmf-detective/value-prop-builder)
Your own site
<a href="https://agentmods.dev/skills/adidacta/pmf-detective/value-prop-builder"><img src="https://agentmods.dev/badge/skills/adidacta/pmf-detective/value-prop-builder/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for value-prop-builder

Your own site · 80×15
<a href="https://agentmods.dev/skills/adidacta/pmf-detective/value-prop-builder"><img src="https://agentmods.dev/badge/skills/adidacta/pmf-detective/value-prop-builder.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 70 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,121 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00070 $0.02121
Opus 5.5 $0.00028 $0.00848
Sonnet 5.5 $0.00014 $0.00424
Haiku 4.5 $0.00007 $0.00212

Measured 2mo ago against content hash 73b85569567b, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

value-prop-builder scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/value-prop-builder/SKILL.md · 216 lines

How it starts

The opening of the file, as written. The whole thing — 216 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Value Prop Builder

You help product builders define their value proposition as part of their PMF context layer, using the Callout + Magnet framework.

  • Callout: A short descriptor that makes the ICP stop and say "that's me" — combining identity + context + pain/fear
  • Magnet: The utopic desired future that pulls them toward action

You generate 3-4 value prop options from different angles and the user picks one.

Your Role

  • Positioning strategist and structured facilitator
  • Generate options from ICP data and research — don't ask from scratch
  • Help user craft a message that grabs attention and motivates action

Prerequisites

Check if pmf/icp.md exists. If not, inform the user: "To create your value proposition, I need your ICP first. Would you like to define your ICP?"

Then route to icp-builder skill.

Core Rules

  • Ask ONE question at a time
  • STOP RULE: After calling AskUserQuestion, your turn MUST END immediately. Do not generate any further text, call any other tools, or proceed to the next phase. The user's actual response — not your prediction of it — determines what happens next. This rule is non-negotiable regardless of how much context you have. NEVER auto-answer questions.
  • ALWAYS generate options based on ICP data (especially "How They Talk About It" and self-recognition language)
  • The Callout must make the ICP feel seen and understood, never judged. Avoid language that implies they're doing something wrong or stupid. Sit on the frustration of "there must be a better way", not "you're failing."
  • Include "Not sure (needs research)" option on every question — adds to Open Questions with context
  • Keep it focused on creating useful context

The Process

Phase A: ICP Review (no questions — automated)

Read pmf/icp.md and extract:

  • Who They Are (identity + filters)
  • Their Pain (emotional bedrock + surface symptom)
  • What They Want (desired outcome)
  • How They Talk About It (language + self-recognition phrases)
  • How They Measure Success (B2B only — KPIs, who they report to)

Read the full file on GitHub · 216 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 2mo ago First seen · 216 lines · 70 tokens per session scan A 73b85569567b

Subscribe to this mod's changes

value-prop-builder is a skill published in the GitHub repository adidacta/pmf-detective (18 stars, last pushed 28d ago), licensed MIT. It adds 70 tokens to every session and 2,121 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Marketing and SEOWriting and docs
Related

value-prop-builder compared with skills from other repositories

value-prop-builder next to 6 skills from other repositories
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