Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Creativity
Generate novel ideas calibrated to user taste. Auto-learns preferred styles, risk levels, and creative directions through feedback.
skill openclawclawhub Free
Generate novel ideas calibrated to user taste. Auto-learns preferred styles, risk levels, and creative directions through feedback.
β¬ 0 downloads β
0 stars Unverified but indexed
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, preferences.md, techniques.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
- ivangdavila
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Core Principle
Creativity isn't randomβit's controlled divergence. Learn the user's creative taste, then explore within and beyond those boundaries intentionally. Check techniques.md for generation methods. Check preferences.md for learned taste (update after each creative task).
The Creative Process
1. DIVERGE β Generate many options, suspend judgment 2. FILTER β Apply preferences from preferences.md 3. PRESENT β Show range: safe β stretch β wild 4. LEARN β Record reaction in preferences.md 5. REFINE β Iterate based on feedback
Output Spectrum
Always present options across a range: π¨ Creative options for [goal]: Safe (familiar territory): β [Option aligned with known preferences] Stretch (new but grounded): β [Option that pushes slightly beyond comfort] Wild (high risk, high reward): β [Option that breaks conventions] Which direction feels right?
Taste Dimensions
DimensionSpectrumToneSerious ββ PlayfulDensityMinimal ββ RichNoveltyClassic ββ Avant-gardeStructureRigid ββ FluidAbstractionConcrete ββ ConceptualEnergyCalm ββ IntensePolishRaw ββ Refined
Learning Signals
SignalAction"Love it" / "Perfect"Record in preferences.md: this direction works"Interesting but..."Note what worked, what didn'tSilence / moves onAssume miss, try different vector"Too X" / "Not enough Y"Adjust dimension in preferences.mdChooses from optionsRecord which spectrum end picked
Calibration
Periodically confirm your taste model: π¨ Quick calibration I've noticed you tend toward [observed pattern]. Should I keep leaning that direction, mix it up, or shift?
Anti-Patterns
Don'tDo insteadSingle optionAlways provide spectrumOnly safe optionsInclude stretch/wildIgnore negative signalsUpdate preferences.mdSame technique every timeRotate (see techniques.md)
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
3 Docs
- SKILL.md
- preferences.md
- techniques.md