By artyomx33Updated 2026-05-11cross-pollination-engine@clawhub_artyomx33/cross-pollination-engine
Knowledge Base Q&AInformation Retrieval
According to AlphaMoat, as of 2026-09, Cross-Pollination Engine has 3,579 downloads and 5 stars — ranked #3,050 of 5,078 AI skills overall, and #278 of 442 in Knowledge.
| Platform | Installs | Downloads | Stars | Comments |
|---|---|---|---|---|
| ClawHub ↗ | 107 | 3.3K | 5 | - |
| SkillHub ↗ | 205 | 3.6K | 5 | — |
Platforms count differently and update at different times.
Examples from the main text: resistance wheels -> Rollerblades, gaming XP systems -> Duolingo, hotel concierge -> software onboarding. The process has four steps: define the core job (strip away industry context), find who else solves it (often surprising industries), extract principles (not surface features), and translate to your context (adapt, don't copy). An industry inspiration library maps needs to sources: trust looks at banking/healthcare/aviation (verification, credentials, checklists); engagement at gaming/fitness apps/streaming (XP, streaks, personalization, progress); onboarding at hotels/theme parks/luxury retail (concierge, anticipation, personal touch); simplicity at Apple/IKEA/Google (feature cutting, hidden complexity); urgency at e-commerce/airlines/fast food (scarcity, anchoring, speed promises); and community at CrossFit/Harley-Davidson/Peloton (tribal identity, shared experience). Output follows a fixed template — problem, core job, per-industry how-they-solve-it/key-principle/applied-to-us blocks, synthesis, and a concrete next step; it compounds with jtbd-analyzer, first-principles-decomposer, six-thinking-hats, and app-planning-skill.
Profile published 2026-10-27
Generated from the skill’s documentation as examples; not results of actual runs.
The counting method changed in 2026-09: skills with the same name are now counted separately by author, and the full catalog is covered. Dashed lines show months before the change; they are not compared with later months, and no growth is computed across the change.
| Month | Downloads | MoM | Stars |
|---|---|---|---|
| 2026-09 | 3.6K | — | 5 |
| 2026-08 | 3.3K | +3.5% | 5 |
| 2026-07 | 3.2K | +8.1% | 5 |
| 2026-06 | 2.9K | +6.7% | 5 |
| 2026-05 | 2.7K | — | 5 |
| 2026-03 | 2.4K | — | 5 |
The author’s original file, shown as plain text without edits or review by AlphaMoat. Links are not clickable; check commands before running them. Fetched 2026-10-23.
--- name: cross-pollination-engine description: Systematically borrow ideas from unrelated industries to solve problems. Innovation often comes from adjacent fields. Use when user says "cross-pollination", "how would X solve this", "borrow ideas from", "what can we learn from", "think outside the box", "how would Disney/Apple/Amazon do this", "different industry", "steal ideas". --- # Cross-Pollination Engine ## The Core Insight Most "innovation" is applying proven solutions from one domain to another.
- Resistance wheels → Rollerblades - Gaming XP systems → Duolingo - Hotel concierge → Software onboarding ## The Process 1. **Define the core job** (strip away industry context) 2. **Find who else solves it** (often surprising industries) 3. **Extract principles** (not surface features) 4. **Translate to your context** (adapt, don't copy) ## Industry Inspiration Library | Need | Look At | Why | |------|---------|-----| | **Trust** | Banking, Healthcare, Aviation | Verification, credentials, checklists | | **Engagement** | Gaming, Fitness apps, Streaming | XP, streaks, personalization, progress | | **Onboarding** | Hotels, Theme parks, Luxury retail | Concierge, anticipation, personal touch | | **Simplicity** | Apple, IKEA, Google | Feature cutting, hidden complexity | | **Urgency** | E-commerce, Airlines, Fast food | Scarcity, anchoring, speed promises | | **Community** | CrossFit, Harley-Davidson, Peloton | Tribal identity, shared experience | ## Output Format ``` PROBLEM: [What you're solving] CORE JOB: [Stripped to fundamentals] FROM [Industry 1]: How they solve it: [x] Key principle: [y] Applied to us: [z] FROM [Industry 2]: How they solve it: [x] Key principle: [y] Applied to us: [z] SYNTHESIS: [Combined approach] NEXT STEP: [Concrete action] ``` ## Prompt Starters - "How would Disney solve our onboarding?" - "What would Amazon do with our data?" - "If this were a game, how would it work?" - "How do luxury hotels make people feel special?" ## Integration Compounds with: - **jtbd-analyzer** → Understand job first, then find who else solves it - **first-principles-decomposer** → Strip context to find fundamental need - **six-thinking-hats** → Green Hat pairs naturally with cross-pollination - **app-planning-skill** → Apply borrowed patterns to new apps --- See references/examples.md for Artem-specific cross-pollinations
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Data month: 2026-09 · Downloads, stars and installs are aggregated monthly from public skill registries (ClawHub, SkillHub). See methodology.