ab-test-generator
Skill757 starsChanged 8 months agoMITView on GitHub
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".
In this repository55 other files it gives its agents.
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The file
We split this skill into the rules it gives an agent
7 rules. About 0 are common, 6 are distinctive, and 1 is very specific to this project.
≈0
Common · estimate
Many files like this have a rule of this kind.
≈6
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 57
Chaining context: If S2-S5 content exists in conversation, the user can reference it: "test the headline from my blog post" or "generate …
- Very specific: line 81
Create num_variants alternatives, each using a different approach:
- Distinctive: line 103
Test duration (7-14 days minimum)
- Distinctive: line 105
When to declare a winner (95% statistical significance or practical significance threshold)
- Distinctive: line 109
Before presenting output, verify:
- Distinctive: line 117
If any check fails, fix the output before delivering.
- Distinctive: line 190
Test results directly improve all content-producing skills → winning headlines, CTAs, and angles feed into next content creation cycle
≈ “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
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 promotedChaining 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
- Original — the current content being tested
- Variants — each variant with its content, change description, and hypothesis
- Test Plan — sample size, duration, metric, winner criteria
- 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 context. Paste the full headline, CTA, or email subject line you want to test."
- Content type unclear: "Is this a headline, CTA button text, email subject line, or social post hook? Knowing the format helps me generate better variants."
- Too many variants requested (>5): "I'll generate 5 high-quality variants. More than 5 makes testing impractical — you'd need a very large audience to reach statistical significance."
Examples
Example 1: Blog headline test
User: "Test this headline: 'HeyGen Review: Is It Worth It in 2026?'" Action: Generate 3 variants. Variant A: "I Tested HeyGen for 30 Days — Here's What Happened" (curiosity + personal experience). Variant B: "HeyGen vs Synthesia: Which AI Video Tool Wins?" (comparison + specificity). Variant C: "The AI Video Tool That Cut My Production Time by 80%" (result + specificity). Each with hypothesis.
Example 2: CTA button test
User: "Optimize this CTA: 'Start Free Trial'" Action: Variant A: "Try HeyGen Free — No Card Required" (reduces friction). Variant B: "Create Your First AI Video in 2 Minutes" (outcome-focused). Variant C: "Get Started Free →" (shorter, action-oriented). Test plan: minimum 500 clicks per variant, track conversion rate.
Example 3: Email subject line test
User: "I'm sending an email about Semrush. Test this subject: 'Check out Semrush — it's great for SEO'" Action: Identify weakness (vague, no hook). Variant A: "The SEO tool I use to rank #1 (not kidding)" (social proof + curiosity). Variant B: "Your competitors are using this — are you?" (FOMO). Variant C: "3 Semrush features that doubled my organic traffic" (specificity + result). Each preserves FTC compliance.
References
shared/references/ftc-compliance.md— Ensure variants preserve FTC disclosure from original. Referenced in Step 3.shared/references/flywheel-connections.md— master flywheel connection map
Flywheel Connections
Feeds Into
purple-cow-audit(S1) — winning variants reveal what resonates = what's remarkableperformance-report(S6) — test results for reporting
Fed By
viral-post-writer(S2) — posts to test variations oftwitter-thread-writer(S2) — thread hooks to testlanding-page-creator(S4) — landing page elements to testcontent-pillar-atomizer(S2) — volume mode variants for testing
Feedback Loop
- Test results directly improve all content-producing skills → winning headlines, CTAs, and angles feed into next content creation cycle
chain_metadata:
skill_slug: "ab-test-generator"
stage: "analytics"
timestamp: string
suggested_next:
- "performance-report"
- "viral-post-writer"
- "landing-page-creator"Does it work?
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