Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub · Productivity
UX
Design and analyze user experiences that are intuitive, efficient, and aligned with user mental models.
skill openclawclawhub Free
Design and analyze user experiences that are intuitive, efficient, and aligned with user mental models.
⬇ 0 downloads ★ 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
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
Flow Analysis
Map every step to complete key tasks—identify unnecessary steps Each step is a potential dropout—minimize count and friction Question every required field—if not essential now, defer or remove Identify points requiring user memory—provide recognition instead
Mental Model Alignment
Use vocabulary users would expect—not internal/technical terms Match familiar patterns before inventing—innovation has learning cost Consistent metaphors throughout—don't mix paradigms in same product Align with platform conventions—users bring expectations from other apps
Friction Reduction
Smart defaults reduce decisions—good default better than more options Pre-fill from available context—location, previous selections, account data Auto-save progress—never lose user work Don't ask for information already available—or not yet needed
Progressive Disclosure
Show only what's needed for current task—hide advanced options until relevant Reveal complexity gradually—basic path first, power features discoverable Empty states guide to first action—not just "Nothing here" Teach by doing, not explaining—inline hints over tutorials
Feedback Design
Every action gets acknowledgment—visual, haptic, or audible Progress indication for waits over 1 second Error messages: what happened + what to do next Success confirmation for significant actions
Error Prevention
Design to prevent errors—constraints, confirmations, smart defaults Confirmation dialogs only for destructive/irreversible actions Undo available for reversible actions—reduces fear of exploring Inline validation catches errors before submission
Cognitive Load
One primary action per screen—clear visual hierarchy Group related information—chunking aids comprehension Limit simultaneous choices—too many options cause paralysis Consistent patterns across product—learned once, applied everywhere
Edge Cases to Design
Empty state: first time, cleared, filtered with no results Loading state: skeleton preferred over spinner for known layouts Error state: what went wrong, how to recover Partial state: some data available, some loading/failed Offline state: what works, what's queued, what's unavailable
Reversibility
Trash over permanent delete—recovery possible Preview before commit—show effect of action Draft states for complex work—don't require completion in one session Settings and decisions easy to change—not buried or locked
Task Completion
Define what success looks like for each flow First value delivered quickly—quick win before complex setup Clear next step always visible—no dead ends Completion feels complete—confirmation, celebration for big tasks
Accessibility Integration
Keyboard/switch navigation works for all flows Screen reader announces what's needed—labels, states, updates Sufficient contrast without relying on color alone Respects user preferences—motion, text size, dark mode
Copy and Labels
Button labels describe outcome—"Save Changes" not "Submit" Headings scannable—user finds what they need quickly Error text actionable—not just "Invalid input" Microcopy reduces uncertainty—helper text where questions arise
Consistency Checks
Same words for same concepts—create glossary if needed Same interaction patterns—swipe/tap/long-press mean same things Visual similarity reflects functional similarity Exceptions rare and justified
Category context
Workflow acceleration for inboxes, docs, calendars, planning, and execution loops.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
1 Docs
- SKILL.md