value-prop-lister
Skill0 starsChanged 47 days agoMITView on GitHub
Extract and rank the real value propositions a product delivers, pulled from won-deal notes and actual customer quotes rather than marketing copy. Use when the user has call notes, testimonials, win/loss notes, or reviews and wants to know "what do customers actually value", "what should we lead with", or needs evidence-based value props for cold outreach. Writes ranked, quote-backed value props into outreach-brief.md. Prefer this over inventing benefits whenever real customer evidence exists.
2 other projects use a version of this.
Adopted by
Most recently taken up by
- vicfromthegtmclub/gtmskillstheir own version, first seen Aug 10, 2026
- l3mpire/claude-skillstheir own version, first seen Apr 13, 2026
Other versions2 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 2
- l3mpire/claude-skills★ 9same name
- vicfromthegtmclub/gtmskills★ 1same name
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository15 other files it gives its agents.
- cold-call-scriptSkill
- competitor-finderSkill
- copywriting-first-touchSkill
- copywriting-follow-upSkill
- copywriting-linkedin-dmSkill
- deep-company-analyserSkill
- icp-definerSkill
- n8n-workflow-builderSkill
- offer-definerSkill
- outreach-strategistSkill
- pain-identifierSkill
- persona-definerSkill
- pipeline-analyserSkill
- reply-rate-analyserSkill
- tam-sam-som-sizerSkill
The file
We split this skill into the rules it gives an agent
4 rules. About 0 are common, 3 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈3
Distinctive · estimate
This author's own choices. Worth a look.
1
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 13
If the user has none, say so plainly and suggest they pull 3-5 recent customer quotes first.
- Distinctive: line 16
Read every piece of evidence and pull the exact phrases where a customer describes a benefit, an outcome, or a relief.
- Distinctive: line 19
Keep the single strongest real quote as proof for each.
- Very specific: line 22
Write into section 5 (Value propositions) of outreach-brief.md as a ranked list.
≈ “Common” is an estimate: at least 1 in 5 of the 350,495 skill files we read have a rule of the same kind, not the same words. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Value Prop Lister
The value props that win deals are the ones customers say back to you, not the ones on the homepage. This skill mines real evidence and ranks what actually matters.
Input needed
- Won-deal notes, call transcripts, testimonials, reviews, or anywhere a customer described the value in their own words.
If the user has none, say so plainly and suggest they pull 3-5 recent customer quotes first. Do not invent value props from thin air; a guessed benefit poisons every email built on it.
Method
- Read every piece of evidence and pull the exact phrases where a customer describes a benefit, an outcome, or a relief.
- Cluster the phrases into distinct value props. Merge duplicates.
- Rank by three things: how often it shows up, how strongly it's said, and how tightly it's tied to money or time.
- Keep the single strongest real quote as proof for each.
Output
Write into section 5 (Value propositions) of outreach-brief.md as a ranked list. For each:
- The value prop in plain language.
- The evidence: one verbatim customer quote.
- A line on why it ranks where it does.
Lead with the value prop that has the most and strongest evidence. That is your cold-email opener fuel.
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
Your trail
Files you open will collect here, so you can find them again.
Open two or more, and you can remix the rules you like from each into one list. Kept in this browser only.
Now do this for your own.
Bring your CLAUDE.md, AGENTS.md or skills. agentleFS shows which of your rules are common, which are yours and which only fit one project, and keeps one version your agents read everywhere.