Best for
- Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'm…
coreyhaines31/marketingskills/skills/pricing/SKILL.md
When the user wants help with pricing decisions, packaging, or monetization strategy. Also use when the user mentions 'pricing,' 'pricing tiers,' 'freemium,' 'free trial,' 'packaging,' 'price increase,' 'value metric,' 'Van Westendorp,' 'willingness to pay,' 'monetization,' 'how much should I charge,' 'my pricing is wrong,' 'pricing page,' 'annual vs monthly,' 'per seat pricing,' 'should I offer a free plan,' 'pricing page teardown,' 'pricing page audit,' 'is my pricing page AI-readable,' or 'ca
Decision brief
You are an expert in SaaS pricing and monetization strategy. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay.
Compatibility matrix
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/coreyhaines31/marketingskills --skill "skills/pricing"Inspect the Agent Skill "pricing" from https://github.com/coreyhaines31/marketingskills/blob/7868cb9251fad80a73d26e488a5ad5f6c4a9f335/skills/pricing/SKILL.md at commit 7868cb9251fad80a73d26e488a5ad5f6c4a9f335. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
Check for product marketing context first: If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already c…
What type of product? (SaaS, marketplace, e-commerce, service)
What's the primary value you deliver?
What's your current conversion rate?
Optimizing for growth, revenue, or profitability?
Permission review
The documentation includes network, browsing, or remote request actions.
*Fast check — the "paste test":** give the pricing URL to a browsing-capable AI (Perplexity, ChatGPT with search, Claude with web) — or paste the rendered page text — and ask "what are the plans and prices?" A clean miss means agents fetchiEvidence record
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 75/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 42,015 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
You are an expert in SaaS pricing and monetization strategy. Your goal is to help design pricing that captures value, drives growth, and aligns with customer willingness to pay.
Check for product marketing context first:
If .agents/product-marketing.md exists (or .claude/product-marketing.md, or the legacy product-marketing-context.md filename, in older setups), read it before asking questions. Use that context and only ask for information not already covered or specific to this task.
Gather this context (ask if not provided):
1. Packaging — What's included at each tier?
2. Pricing Metric — What do you charge for?
3. Price Point — How much do you charge?
Price should be based on value delivered, not cost to serve:
Key insight: Price between the next best alternative and perceived value.
The value metric is what you charge for—it should scale with the value customers receive.
Good value metrics:
| Metric | Best For | Example |
|---|---|---|
| Per user/seat | Collaboration tools | Slack, Notion |
| Per usage | Variable consumption | AWS, Twilio |
| Per feature | Modular products | HubSpot add-ons |
| Per contact/record | CRM, email tools | Mailchimp |
| Per transaction | Payments, marketplaces | Stripe |
| Flat fee | Simple products | Basecamp |
Ask: "As a customer uses more of [metric], do they get more value?"
Good tier (Entry): Core features, limited usage, low price Better tier (Recommended): Full features, reasonable limits, anchor price Best tier (Premium): Everything, advanced features, 2-3x Better price
For detailed tier structures and persona-based packaging: See references/tier-structure.md
Four questions that identify acceptable price range:
Analyze intersections to find optimal pricing zone.
Identifies which features customers value most:
For detailed research methods: See references/research-methods.md
Market signals:
Business signals:
Product signals:
When someone wants to audit an existing pricing page for clarity, transparency, and AI-readability (not the pricing strategy itself, and not conversion-rate optimization — that's cro), run a teardown that scores it across two axes and returns prioritized fixes:
Fast check — the "paste test": give the pricing URL to a browsing-capable AI (Perplexity, ChatGPT with search, Claude with web) — or paste the rendered page text — and ask "what are the plans and prices?" A clean miss means agents fetching your page will struggle too (a heuristic, not proof every agent fails).
The AI-readiness fixes are usually high-impact, low-effort (put prices in text, add Offer schema). Hand implementation to schema (Product/Offer JSON-LD) and ai-seo (extractability, AI-bot access, llms.txt).
For the full 10-dimension rubric, scoring, and report template: See references/pricing-page-teardown.md. (AI-agent-readiness lens adapted from Kyle Poyar / Growth Unhinged.)
Alternatives
coreyhaines31/marketingskills
When the user wants to plan, design, or implement an A/B test or experiment, or build a growth experimentation program. Also use when the user mentions "A/B test," "split test," "experiment," "test this change," "variant copy," "multivariate test," "hypothesis," "should I test this," "which version is better," "test two versions," "statistical significance," "how long should I run this test," "growth experiments," "experiment velocity," "experiment backlog," "ICE score," "experimentation program
coreyhaines31/marketingskills
When the user wants to reduce churn, build cancellation flows, set up save offers, recover failed payments, or implement retention strategies. Also use when the user mentions 'churn,' 'cancel flow,' 'offboarding,' 'save offer,' 'dunning,' 'failed payment recovery,' 'win-back,' 'retention,' 'exit survey,' 'pause subscription,' 'involuntary churn,' 'people keep canceling,' 'churn rate is too high,' 'how do I keep users,' or 'customers are leaving.' Use this whenever someone is losing subscribers o
event4u-app/agent-config
Use when the user says "review the design", "check the UI", or wants a comprehensive UI/UX review. Uses a 7-phase methodology covering interaction, responsiveness, accessibility, and more.
K-Dense-AI/scientific-agent-skills
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.