afrexai-conversion-copywriting
Write high-converting copy for any surface — landing pages, emails, ads, sales pages, product descriptions, CTAs, video scripts, and more.
Skill by LeoYeAI
Install
Works with Claude Code, Claude apps, Codex, Cursor, Gemini CLI, GitHub Copilot, VS Code, OpenCode, Goose, Windsurf. Read the repository before you give any tool access to your data.
npx agentmarket install skill/leoyeai-afrexai-conversion-copywriting
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About
Use cases: testing, writing, marketing, sales
Reviews
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Permissions
What this skill can do and what it asks for, from its SKILL.md. Checked Oct 25, 2026.
- Tools
- No tools found
- Secrets
- None asked for
- Install scripts
- None found
Network hosts it talks to 1
codeload.github.com· found in install command
Files it touches
~/.claude/skills/afrexai-conversion-copywriting
What's inside
- Skill name
afrexai-conversion-copywriting- Description
- Write high-converting copy for any surface — landing pages, emails, ads, sales pages, product descriptions, CTAs, video scripts, and more. Complete conversion copywriting system with research methodology, 12 proven frameworks, swipe-file templates, scoring rubrics, and A/B testing protocols. Use when you need to write or review any copy meant to drive action.
- License
- MIT
- Instructions
- 737 lines in SKILL.md · view on GitHub
Agent Skills spec issues
- body: 737 lines (spec recommends under 500)
Files (3)
- README.md
- SKILL.md
- _meta.json
SKILL.md (first lines)
# Conversion Copywriting Engine
> Copy is salesmanship in print. This isn't about writing — it's about selling. Every word earns its place or gets cut.
## Quick Health Check
Rate the copy 1-5 on each dimension. Score < 24 = rewrite needed:
| # | Dimension | Question |
|---|-----------|----------|
| 1 | Clarity | Can a 12-year-old understand the offer in 5 seconds? |
| 2 | Specificity | Are there numbers, timeframes, and concrete outcomes? |
| 3 | Desire | Does the reader WANT the outcome described? |
| 4 | Proof | Is there evidence (testimonials, data, logos, case studies)? |
| 5 | Urgency | Is there a reason to act NOW vs later? |
| 6 | Friction | Are objections addressed before they arise? |
| 7 | Voice | Does it sound like a human, not a corporation? |
| 8 | CTA | Is the next step crystal clear and low-risk? |
**Score: /40** — Below 32 = significant opportunity. Below 24 = copy is actively losing money.
---
## Phase 1: Research Before Writing
Never write a single word until you complete this. Bad research = bad copy, no matter how clever.
### 1.1 Voice of Customer (VoC) Mining
The goal: steal your customer's EXACT words and mirror them back.
**Sources (ranked by value):**
| Source | What to Extract | Where to Find |
|--------|----------------|---------------|
| Support tickets | Pain language, frustration words | Helpdesk, Intercom, Zendesk |
| Sales call recordings | Objections, "I wish...", buying triggers | Gong, call notes |
| Review sites | Praise patterns, complaint patterns | G2, Capterra, Trustpilot, Amazon |
| Reddit/forums | Unfiltered problems, slang, emotional language | r/[industry], Quora, niche forums |
| Competitor reviews | What competitors fail at (your opportunity) | G2, App Store, Amazon |
| Survey responses | Direct answers to "why did you buy/not buy?" | Typeform, post-purchase surveys |
| Social comments | Reaction language, share triggers | Twitter replies, LinkedIn comments |
**VoC Extraction Template:**
```yaml
voC_research:
product: "[Product name]"
date: "YYYY-MM-DD"
pain_statements: # Exact quotes about the problem
- quote: "I spend 3 hours every morning just reconciling invoices"
source: "G2 review - AccountingSoft competitor"
frequency: "high" # How often this sentiment appears
- quote: ""
source: ""
frequency: ""
desire_statements: # What they WANT (outcome language)
- quote: "I just want to click one button and have it done"
source: "Reddit r/smallbusiness"
frequency: "medium"
- quote: ""
source: ""
frequency: ""
objection_statements: # Why they hesitate
- quote: "Every tool like this requires a PhD to set up"
source: "Support ticket"
frequency: "high"
- quote: ""
source: ""
frequency: ""
trigger_events: # What made them start looking
- "Hired 5th employee and spreadsheets broke"
- "Missed a tax deadline"
- ""
words_they_use: # Industry/audience vocabulary
- "reconciliation" not "financial harmonization"
- "setup" not "onboarding flow"
- ""
competitors_they_mention: []
buying_criteria: # What matters most (ranked)
- "Easy to set up (< 1 hour)"
- "Integrates with QuickBooks"
- ""
```
### 1.2 Awareness Levels (Eugene Schwartz)
Every piece of copy must match the reader's awareness level. Writing "Buy now!" to someone who doesn't know they have a problem = wasted words.
| Level | They Know... | Your Job | Lead With |
|-------|-------------|----------|-----------|
| **Unaware** | Nothing about the problem | Educate about the pain | Story, shocking stat, question |
| **Problem-Aware** | They have a problem | Agitate the pain, introduce solution category | "Tired of X? Here's why..." |
| **Solution-Aware** | Solutions exist | Differentiate YOUR solution | "Unlike other tools, we..." |
| **Product-Aware** | Your product exists | Overcome objections, prove value | Social proof, comparison, demo |
| **Most Aware** | Your product, ready to buy | Remove final friction | Deal, guarantee, urgency |
**Rule:** The less aware they are, the longer the copy needs to be. Unaware = long-form education. Most Aware = short CTA + offer.
### 1.3 One Reader, One Offer, One Action
Before writing, fill this in:
```yaml
copy_brief:
surface: "" # Landing page, email, ad, sales page, etc.
one_reader: "" # Specific person (not "small businesses" — "Sarah, ops manager at 50-person agency")
awareness_level: "" # Unaware / Problem / Solution / Product / Most Aware
one_offer: "" # What exactly are you offering?
one_action: "" # What exactly should they DO?
primary_emotion: "" # Fear, desire, curiosity, frustration, hope
proof_available: [] # Testimonials, case studies, data points you can useFrom LeoYeAI/openclaw-master-skills, MIT.
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Signals
- Stars
- 2,168
- Forks
- 325
- Open issues
- 13
- Last commit (this folder)
- May 5, 2026 (5 months ago)
- Last release
- Jul 20, 2026 (3 months ago)
From GitHub (fetched Oct 24, 2026).
Details
- License
- MIT
- Website
- myclaw.ai
- First seen
- Oct 24, 2026
- Last checked
- Oct 24, 2026
- Source
- GitHubgithub-graphql
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Cite this page
afrexai-conversion-copywriting skill. Agent Mart. https://agentmart.dev/skills/leoyeai-afrexai-conversion-copywriting (last updated 2026-10-24)