dotfiles/dot_config/skillshare/skills/pricing-strategy/SKILL.md
Analyze and design pricing strategies including pricing models, competitive pricing analysis, willingness-to-pay estimation, and price elasticity. Use when setting prices, evaluating pricing models, preparing for a pricing change, or comparing freemium vs paid approaches.
npx skillsauth add pkking/dotfiles pricing-strategyInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Design a pricing strategy grounded in value delivery, competitive positioning, and willingness to pay.
You are developing a pricing strategy for $ARGUMENTS.
If the user provides files (competitor pricing, survey data, financial models, or usage data), read them first. Use web search to research competitor pricing if needed.
Understand the value delivered:
Evaluate pricing models — recommend the best fit:
| Model | Best For | Example | |---|---|---| | Flat-rate | Simple products, predictable costs | Basecamp ($99/mo flat) | | Per-seat | Collaboration tools, team products | Slack, Figma | | Usage-based | Infrastructure, API products | AWS, Twilio | | Tiered | Products with distinct user segments | Most SaaS (Free/Pro/Enterprise) | | Freemium | Products with viral/network effects | Spotify, Notion | | Freemium + usage | Platform products | Vercel, OpenAI API | | Value-based | High-impact enterprise tools | Salesforce, Palantir |
Analyze competitive pricing:
Design the pricing structure:
Estimate price sensitivity:
Plan pricing experiments:
Output a pricing recommendation:
Recommended Model: [Model type]
Value Metric: [What you charge on]
| Tier | Price | Target Segment | Key Features | Positioning |
|---|---|---|---|---|
Key Assumptions:
- [Assumption] → [How to test]
Risks:
- [Risk] → [Mitigation]
Think step by step. Save as markdown. Flag any assumptions that need validation before launch.
testing
Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.
testing
Interview the user relentlessly about a plan or design until reaching shared understanding, resolving each branch of the decision tree. Use when user wants to stress-test a plan, get grilled on their design, or mentions "grill me".
data-ai
Helps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express interest in extending capabilities. This skill should be used when the user is looking for functionality that might exist as an installable skill.
development
Run the full autonomous engineering pipeline end-to-end (plan, work, code review, test, commit, push, open PR, watch CI, fix CI failures until green). Use only when the user explicitly requests hands-off execution of a software task and provides a feature description; do not auto-route casual conversation here.