Cross-Pollination Engine
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".
MIT-0 · Free to use, modify, and redistribute. No attribution required.
⭐ 5 · 2.1k · 4 current installs · 4 all-time installs
MIT-0
Security Scan
OpenClaw
Benign
high confidencePurpose & Capability
Name, description, and SKILL.md all describe brainstorming cross-industry idea transfer; nothing in the bundle asks for unrelated capabilities, binaries, or credentials.
Instruction Scope
The runtime instructions are limited to a human-style process (define job, extract principles, translate). They do not instruct reading files, environment variables, or contacting external endpoints.
Install Mechanism
No install spec and no code files — nothing is written to disk or fetched at install time. Lowest-risk install posture.
Credentials
No required env vars, credentials, or config paths are declared; the skill's behavior does not imply a need for additional secrets.
Persistence & Privilege
No privileged flags (always, disableModelInvocation) are set; the skill does not request permanent presence or autonomous invocation.
Assessment
This skill is an instruction-only brainstorming tool and is internally consistent. Before installing, consider: (1) legal/ethical risk — avoid asking it to reproduce proprietary processes or confidential data from other companies; (2) composition risk — only combine it with other skills you trust, since chaining it to skills that have network or credential access could expand the attack surface; and (3) review references/examples.md for any organization-specific examples that might expose sensitive details. No technical credentials or installs are required, so the security risk from this package itself is minimal.Like a lobster shell, security has layers — review code before you run it.
Current versionv1.0.0
Download ziplatest
License
MIT-0
Free to use, modify, and redistribute. No attribution required.
SKILL.md
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
- Define the core job (strip away industry context)
- Find who else solves it (often surprising industries)
- Extract principles (not surface features)
- 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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