Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub Β· AI
Trip Discover
Recommend travel destinations based on vibe, budget, duration, and group size. Handles "suggest a trip", "where should I go", "weekend getaway", "compare X v...
skill openclawclawhub Free
Recommend travel destinations based on vibe, budget, duration, and group size. Handles "suggest a trip", "where should I go", "weekend getaway", "compare X v...
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
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
- swayamg20
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
When to activate
User asks for trip suggestions: "weekend trip", "where should I go", "suggest somewhere" User gives a vibe: "mountains", "beaches", "offbeat", "party", "peaceful" User says "plan from my saves" or "pick from my wishlist" User asks to compare: "Kasol vs Bir", "which is better"
Input parsing
Extract from user message (ask only if critical info missing): Vibe: mountains / beaches / heritage / adventure / spiritual / nightlife / offbeat Budget: total per person in βΉ (default: βΉ5000-8000 for weekend) Duration: weekend (2-3 days) / long weekend (4 days) / week Group: solo / couple / friends / family From city: assume Delhi unless stated or known from memory
How to recommend
Search the web for current relevant destinations Pick 2-3 destinations. Lead with your top pick. For each provide: Name + one opinionated line (not generic) Travel time from their city + how to get there Rough cost estimate per person Current weather Why THIS trip for THIS person
"Plan from my saves" flow
Check memory for saved destinations Filter by current vibe/budget/duration Recommend from saves first, then add new discoveries
Compare flow ("Kasol vs Bir")
Search web for both. Present side-by-side: Vibe, travel time, cost, weather, best for End with: "My pick: X β because..."
Response format
ποΈ My pick: Kasol, Himachal Pradesh Backpacker paradise with killer cafes and the Kheerganga trek. 12 hrs by Volvo from Delhi (βΉ1200). Stay: βΉ800-1500/night. March weather: 10-18Β°C, perfect trekking season. Total estimate: βΉ6,500/person for 3 days. Also consider: Tirthan Valley β quieter, great for couples Bir β paragliding + monasteries, slightly cheaper Want me to plan Kasol? Or compare any two?
Rules
Max 3 destinations. Never more. No generic descriptions β be specific and opinionated Always check current weather/season via web search Check saved places in memory if user has any
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
1 Docs
- SKILL.md