/ab-test-generator
Generate A/B test variants for affiliate content. Triggers on: "create A/B test", "test my headline", "optimize my CTA", "generate variants", "split test ideas", "improve click-through rate", "test my landing page copy", "headline alternatives", "CTA variations", "which version
$ npx -y skills add Affitor/affiliate-skills --skill ab-test-generator --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/ab-test-generator
Context preview
The summary Claude sees to decide when to auto-load this skill.
Generate A/B test variants for affiliate content. Triggers on: "create A/B test", "test my headline", "optimize my CTA", "generate variants", "split test ideas", "improve click-through rate", "test my landing page copy", "headline alternatives", "CTA variations", "which version
SKILL.md
ab-test-generator.SKILL.mdname: ab-test-generator
description: >
Generate A/B test variants for affiliate content. Triggers on:
"create A/B test", "test my headline", "optimize my CTA", "generate variants",
"split test ideas", "improve click-through rate", "test my landing page copy",
"headline alternatives", "CTA variations", "which version is better",
"optimize conversions", "test my email subject line", "compare approaches".
license: MIT
version: "1.0.0"
tags: ["affiliate-marketing", "analytics", "optimization", "tracking", "ab-testing", "experiments"]
compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent"
metadata:
author: affitor
version: "1.0"
stage: S6-Analytics
A/B Test Generator
Generate A/B test variants for affiliate content — headlines, CTAs, landing page sections, email subject lines, and social post hooks. Each variant includes a hypothesis explaining why it might outperform the original. Output is a Markdown document with the original, variants, hypotheses, and a test plan.
Stage
S6: Analytics — Small changes in headlines and CTAs can swing conversion rates by 20-50%. A/B testing is how professional affiliates systematically find what converts best. This skill removes the guesswork by generating theory-driven variants using proven copywriting frameworks.
When to Use
- User wants to improve conversion rates on existing content
- User has a headline, CTA, or email subject line and wants alternatives
- User says "test my headline", "optimize my CTA", "A/B test ideas"
- User has a landing page section that isn't converting
- User wants to compare different messaging approaches
- Chaining from S2-S5: take any content output and generate test variants
Input Schema
original: string # REQUIRED — the content to test (headline, CTA, paragraph,
# email subject line, or full social post)
content_type: string # REQUIRED — "headline" | "cta" | "landing_section"
# | "email_subject" | "social_hook"
goal: string # OPTIONAL — "clicks" | "signups" | "purchases"
# Default: "clicks"
num_variants: number # OPTIONAL — number of variants to generate (2-5)
# Default: 3
audience: string # OPTIONAL — who sees this content
# (e.g., "SaaS founders", "content creators")
product: string # OPTIONAL — product being promoted**Chaining context**: If S2-S5 content exists in conversation, the user can reference it: "test the headline from my blog post" or "generate CTA variants for my landing page."
Workflow
Step 1: Analyze Original Content
Break down the original into components:
- **Emotional angle**: What emotion does it trigger? (curiosity, fear, desire, urgency)
- **Specificity**: How specific vs vague?
- **Structure**: Question, statement, command, statistic?
- **Framework**: Which copywriting framework does it follow? (PAS, AIDA, 4U, BAB)
Step 2: Identify Testable Elements
Determine what to vary:
- Emotional angle (switch from curiosity to urgency)
- Specificity (add numbers, remove vagueness)
- Structure (question vs statement)
- Length (shorter vs longer)
- Power words (swap key words for stronger alternatives)
- Social proof (add or remove)
Step 3: Generate Variants
Create `num_variants` alternatives, each using a different approach:
- **Variant A**: Different emotional angle
- **Variant B**: Different structure/format
- **Variant C**: Different specificity level
- Additional variants explore social proof, urgency, or contrarian angles
Each variant must:
- Preserve the core message and product reference
- Preserve any FTC disclosure from the original
- Be a realistic alternative (not just a word swap)
Step 4: Write Hypotheses
For each variant, explain:
- What was changed and why
- Which copywriting principle supports the change
- What behavior change is expected (e.g., "Higher CTR because questions create open loops")
Step 5: Suggest Test Plan
Recommend:
- Sample size needed (minimum 100 impressions per variant for social, 500 for landing pages)
- Test duration (7-14 days minimum)
- What metric to track (CTR, conversion rate, revenue per visitor)
- When to declare a winner (95% statistical significance or practical significance threshold)
Step 6: Self-Validation
Before presenting output, verify:
- [ ] 3-5 distinct variants generated (not just word swaps)
- [ ] Each hypothesis grounded in a copywriting principle or framework
- [ ] Sample size calculation is present and realistic
- [ ] Test duration is ≥7 days minimum
- [ ] Winner criteria defined with statistical significance threshold
If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.
Output Schema
output_schema_version: "1.0.0" # Semver — bump major on breaking changes
test:
original: string
content_type: string
goal: string
variants:
- label: string # "Variant A", "Variant B", etc.
content: string # the variant text
change: string # what was changed
framework: string # copywriting principle used
hypothesis: string # why this might win
test_plan:
sample_size: number # per variant
duration: string # recommended test period
metric: string # what to measure
winner_criteria: string # when to pick a winnerOutput Format
1. **Original** — the current content being tested 2. **Variants** — each variant with its content, change description, and hypothesis 3. **Test Plan** — sample size, duration, metric, winner criteria 4. **Quick Win** — if one variant is clearly stronger based on copywriting principles, call it out
Error Handling
- **Original too short (1-2 words)**: "I need more cont
Read more
name: ab-test-generator description: > Generate A/B test variants for affiliate content. Triggers on: "create A/B test", "test my headline", "optimize my CTA", "generate variants", "split test ideas", "improve click-through rate", "test my landing page copy", "headline alternatives", "CTA variations", "which version is better", "optimize conversions", "test my email subject line", "compare approaches". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "analytics", "optimization", "tracking", "ab-testing", "experiments"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S6-Analytics
A/B Test Generator
Generate A/B test variants for affiliate content — headlines, CTAs, landing page sections, email subject lines, and social post hooks. Each variant includes a hypothesis explaining why it might outperform the original. Output is a Markdown document with the original, variants, hypotheses, and a test plan.
Stage
S6: Analytics — Small changes in headlines and CTAs can swing conversion rates by 20-50%. A/B testing is how professional affiliates systematically find what converts best. This skill removes the guesswork by generating theory-driven variants using proven copywriting frameworks.
When to Use
- User wants to improve conversion rates on existing content
- User has a headline, CTA, or email subject line and wants alternatives
- User says "test my headline", "optimize my CTA", "A/B test ideas"
- User has a landing page section that isn't converting
- User wants to compare different messaging approaches
- Chaining from S2-S5: take any content output and generate test variants
Input Schema
original: string # REQUIRED — the content to test (headline, CTA, paragraph,
# email subject line, or full social post)
content_type: string # REQUIRED — "headline" | "cta" | "landing_section"
# | "email_subject" | "social_hook"
goal: string # OPTIONAL — "clicks" | "signups" | "purchases"
# Default: "clicks"
num_variants: number # OPTIONAL — number of variants to generate (2-5)
# Default: 3
audience: string # OPTIONAL — who sees this content
# (e.g., "SaaS founders", "content creators")
product: string # OPTIONAL — product being promoted**Chaining context**: If S2-S5 content exists in conversation, the user can reference it: "test the headline from my blog post" or "generate CTA variants for my landing page."
Workflow
Step 1: Analyze Original Content
Break down the original into components:
- **Emotional angle**: What emotion does it trigger? (curiosity, fear, desire, urgency)
- **Specificity**: How specific vs vague?
- **Structure**: Question, statement, command, statistic?
- **Framework**: Which copywriting framework does it follow? (PAS, AIDA, 4U, BAB)
Step 2: Identify Testable Elements
Determine what to vary:
- Emotional angle (switch from curiosity to urgency)
- Specificity (add numbers, remove vagueness)
- Structure (question vs statement)
- Length (shorter vs longer)
- Power words (swap key words for stronger alternatives)
- Social proof (add or remove)
Step 3: Generate Variants
Create `num_variants` alternatives, each using a different approach:
- **Variant A**: Different emotional angle
- **Variant B**: Different structure/format
- **Variant C**: Different specificity level
- Additional variants explore social proof, urgency, or contrarian angles
Each variant must:
- Preserve the core message and product reference
- Preserve any FTC disclosure from the original
- Be a realistic alternative (not just a word swap)
Step 4: Write Hypotheses
For each variant, explain:
- What was changed and why
- Which copywriting principle supports the change
- What behavior change is expected (e.g., "Higher CTR because questions create open loops")
Step 5: Suggest Test Plan
Recommend:
- Sample size needed (minimum 100 impressions per variant for social, 500 for landing pages)
- Test duration (7-14 days minimum)
- What metric to track (CTR, conversion rate, revenue per visitor)
- When to declare a winner (95% statistical significance or practical significance threshold)
Step 6: Self-Validation
Before presenting output, verify:
- [ ] 3-5 distinct variants generated (not just word swaps)
- [ ] Each hypothesis grounded in a copywriting principle or framework
- [ ] Sample size calculation is present and realistic
- [ ] Test duration is ≥7 days minimum
- [ ] Winner criteria defined with statistical significance threshold
If any check fails, fix the output before delivering. Do not flag the checklist to the user — just ensure the output passes.
Output Schema
output_schema_version: "1.0.0" # Semver — bump major on breaking changes
test:
original: string
content_type: string
goal: string
variants:
- label: string # "Variant A", "Variant B", etc.
content: string # the variant text
change: string # what was changed
framework: string # copywriting principle used
hypothesis: string # why this might win
test_plan:
sample_size: number # per variant
duration: string # recommended test period
metric: string # what to measure
winner_criteria: string # when to pick a winnerOutput Format
1. **Original** — the current content being tested 2. **Variants** — each variant with its content, change description, and hypothesis 3. **Test Plan** — sample size, duration, metric, winner criteria 4. **Quick Win** — if one variant is clearly stronger based on copywriting principles, call it out
Error Handling
- **Original too short (1-2 words)**: "I need more cont
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