Ab Test Generator logo

Ab Test Generator

Organization
Affitor
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 is better", "optimize conversions", "test my email subject line", "compare approaches".

Overview

PublisherAffitor
Repositoryaffiliate-skills
Skill nameab-test-generator
Stars
705
Forks
209
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Affitor on GitHub. Read the source before you install it.

Installation

Install the Ab Test Generator AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Affitor/affiliate-skills/tree/main/skills/analytics/ab-test-generator
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Affitor/affiliate-skills.git /tmp/affiliate-skills
mkdir -p .claude/skills
cp -r /tmp/affiliate-skills/skills/analytics/ab-test-generator .claude/skills/ab-test-generator
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ab Test Generator in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Ab Test Generator on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Ab Test Generator is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

yaml
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

yaml
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 winner

Output 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 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 remarkable
  • performance-report (S6) — test results for reporting

Fed By

  • viral-post-writer (S2) — posts to test variations of
  • twitter-thread-writer (S2) — thread hooks to test
  • landing-page-creator (S4) — landing page elements to test
  • content-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
yaml
chain_metadata:
  skill_slug: "ab-test-generator"
  stage: "analytics"
  timestamp: string
  suggested_next:
    - "performance-report"
    - "viral-post-writer"
    - "landing-page-creator"

Frequently asked questions

What does the Ab Test Generator AI skill do?

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".

Why use Ab Test Generator on TypingMind?

Because you install it once and use it with any model. Ab Test Generator is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Ab Test Generator in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Affitor/affiliate-skills/tree/main/skills/analytics/ab-test-generator. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Ab Test Generator?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Ab Test Generator?

As many as you like. As long as a model supports skills, you can use Ab Test Generator with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Ab Test Generator AI skill free?

Yes. It is published on GitHub by Affitor under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇