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…
Design the complete free-to-premium value ladder for affiliate promotions. Triggers on: "value ladder", "customer journey", "upsell path", "ascension model", "free to paid funnel", "tripwire offer", "upsell strategy", "downsell", "product ladder", "price ladder", "customer
$ npx -y skills add Affitor/affiliate-skills --skill value-ladder-architect --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/value-ladder-architectContext preview
The summary Claude sees to decide when to auto-load this skill.
Design the complete free-to-premium value ladder for affiliate promotions. Triggers on: "value ladder", "customer journey", "upsell path", "ascension model", "free to paid funnel", "tripwire offer", "upsell strategy", "downsell", "product ladder", "price ladder", "customer
name: value-ladder-architect description: > Design the complete free-to-premium value ladder for affiliate promotions. Triggers on: "value ladder", "customer journey", "upsell path", "ascension model", "free to paid funnel", "tripwire offer", "upsell strategy", "downsell", "product ladder", "price ladder", "customer ascension", "funnel architecture", "map my funnel", "design my funnel stages", "monetization path". license: MIT version: "1.0.0" tags: ["affiliate-marketing", "landing-pages", "conversion", "offers", "value-ladder", "pricing"] compatibility: "Claude Code, ChatGPT, Gemini CLI, Cursor, Windsurf, OpenClaw, any AI agent" metadata: author: affitor version: "1.0" stage: S4-Landing
Design the complete free → tripwire → core → upsell path for affiliate promotions. Maps the entire customer ascension journey, where each step delivers standalone value while naturally leading to the next. The value ladder IS the page sequence: squeeze → bridge → sales → upsell.
S4: Landing — The value ladder defines the sequence of pages and offers. Each rung is a landing page, email, or content piece that converts the visitor to the next level.
product: # REQUIRED
name: string # Product name
pricing_tiers: object[] # Available pricing tiers
- name: string # e.g., "Free", "Pro", "Enterprise"
price: string # e.g., "$0", "$49/mo", "$199/mo"
features: string[] # Key features at this tier
reward_value: string # Your commission
reward_type: string # "recurring" | "one-time" | "tiered"
url: string # Affiliate link
your_assets: string[] # OPTIONAL — content/resources you already have
# e.g., ["blog", "email list", "YouTube channel", "templates"]
# Default: ["blog"]
goal: string # OPTIONAL — "first_commission" | "maximize_ltv" | "build_list"
# Default: "first_commission"**Chaining from S4 grand-slam-offer**: Use `offer_stack` to position the core offer in the ladder. **Chaining from S4 bonus-stack-builder**: Use `bonus_stack` to populate tripwire and bonus tiers.
1. Map the product's pricing tiers and commission structure 2. Identify user's existing assets (blog, list, social following) 3. Determine goal: first commission (simple ladder) vs maximize LTV (complex ladder)
Read `shared/references/offer-frameworks.md` for the Value Ladder framework.
Map each rung:
**Rung 0: FREE (Awareness)**
**Rung 1: TRIPWIRE ($1-$49, impulse buy)**
**Rung 2: CORE (main affiliate product)**
**Rung 3: UPSELL (premium tier or complementary product)**
For each rung, specify:
Define what moves a person from one rung to the next:
Present the complete value ladder with implementation roadmap.
output_schema_version: "1.0.0"
value_ladder:
product_name: string
total_rungs: number
rungs:
- level: number # 0, 1, 2, 3
name: string # "Free", "Tripwire", "Core", "Upsell"
offer: string # What they get
price: string # Price point
page_type: string # "blog" | "squeeze" | "bridge" | "landing" | "email"
skill_to_build: string # Which affiliate skill creates this page
conversion_to_next: string # How they move to next rung
estimated_conversion: string # Benchmark conTurn any AI into your affiliate marketing team. 52 AI-powered skills across 8 stages with a closed-loop flywheel.
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