Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
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".
skill openclawclawhub Free
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".
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Install for OpenClaw
Quick setup
- Download the package from Yavira.
- Extract the archive and review SKILL.md first.
- Import or place the package into your OpenClaw setup.
Package facts
- Download mode
- Yavira redirect
- Package format
- ZIP package
- Source platform
- Tencent SkillHub
- What's included
- SKILL.md, references/examples.md
Validation
- Use the Yavira download entry.
- Review SKILL.md after the package is downloaded.
- Confirm the extracted package contains the expected setup assets.
Install with your agent
Agent handoff
Hand the extracted package to your coding agent with a concrete install brief instead of figuring it out manually.
- Download the package from Yavira.
- Extract it into a folder your agent can access.
- Paste one of the prompts below and point your agent at the extracted folder.
New install
I downloaded a skill package from Yavira. Read SKILL.md from the extracted folder and install it by following the included instructions. Tell me what you changed and call out any manual steps you could not complete.
Upgrade existing
I downloaded an updated skill package from Yavira. Read SKILL.md from the extracted folder, compare it with my current installation, and upgrade it while preserving any custom configuration unless the package docs explicitly say otherwise. Summarize what changed and any follow-up checks I should run.
Trust & source
Release facts
- Source
- Tencent SkillHub
- Verification
- Indexed source record
- Version
- 1.0.0
Provenance
- Publisher
- artyomx33
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
The Core Insight
Most "innovation" is applying proven solutions from one domain to another. Resistance wheels β Rollerblades Gaming XP systems β Duolingo Hotel concierge β 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
NeedLook AtWhyTrustBanking, Healthcare, AviationVerification, credentials, checklistsEngagementGaming, Fitness apps, StreamingXP, streaks, personalization, progressOnboardingHotels, Theme parks, Luxury retailConcierge, anticipation, personal touchSimplicityApple, IKEA, GoogleFeature cutting, hidden complexityUrgencyE-commerce, Airlines, Fast foodScarcity, anchoring, speed promisesCommunityCrossFit, Harley-Davidson, PelotonTribal 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 β Understand job first, then find who else solves it first-principles-decomposer β Strip context to find fundamental need six-thinking-hats β Green Hat pairs naturally with cross-pollination app-planning-skill β Apply borrowed patterns to new apps See references/examples.md for Artem-specific cross-pollinations
Category context
Agent frameworks, memory systems, reasoning layers, and model-native orchestration.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- references/examples.md