pricing-and-wtplisted

<!-- version: 0.3.0 | outputs: memory/ideas/<slug>/pricing.json --> # Skill: pricing-and-wtp ## Purpose Determine what users would actually pay, not what the developer hopes to charge. Anchor WTP to pain intensity, desire strength, competitive pricing, and real monetization signals from market_insights — never to the cost of building. Pricing is the single decision with the highest leverage on unit economics: a $1/mo difference at 1,000 users is $12K/year. ## Input - Idea slug - `memory/ideas/<slug>/idea.md` (app concept, key features, `business_model`, `price_point_hypothesis`) - `memory/ideas/<slug>/competitors.json` (competitive pricing, pricing models in use, `anchors` for the B2B lane) - `memory/ideas/<slug>/desire_scores.json` (desire strength, primary/secondary drivers) - `memory/market_insights/<niche>-*-<YYYY>-<MM>.md` (trend data — **use all available platform files**) ### Using Market Insights Trend analysis files provide monetization reality-checks that desk research alone cannot: | Field | How it informs pricing | |---|---| | `monetization_evidence` | The strongest signal. If competitors are visibly making money (in-app purchases mentioned in reviews, subscription pricing in App Store listings, sponsored content), the market has validated WTP. If monetization_evidence is empty across all platforms, WTP is unproven — discount aspirational price and flag risk. | | Platform narratives — Reddit | Users discuss pricing directly: "I'd pay for X if...", "Y is ov