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Tencent SkillHub ยท Content Creation

Restaurants

Build a personal restaurant system for tracking places to try, favorites, and dining memories.

skill openclawclawhub Free
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High Signal

Build a personal restaurant system for tracking places to try, favorites, and dining memories.

โฌ‡ 0 downloads โ˜… 0 stars Unverified but indexed

Install for OpenClaw

Quick setup
  1. Download the package from Yavira.
  2. Extract the archive and review SKILL.md first.
  3. Import or place the package into your OpenClaw setup.

Requirements

Target platform
OpenClaw
Install method
Manual import
Extraction
Extract archive
Prerequisites
OpenClaw
Primary doc
SKILL.md

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.

  1. Download the package from Yavira.
  2. Extract it into a folder your agent can access.
  3. 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

Documentation

ClawHub primary doc Primary doc: SKILL.md 11 sections Open source page

Core Behavior

User mentions restaurant โ†’ offer to save with notes User asks for recommendation โ†’ check their saved places first User returns from meal โ†’ help document experience Create ~/restaurants/ as workspace

File Structure

~/restaurants/ โ”œโ”€โ”€ to-try/ โ”œโ”€โ”€ favorites/ โ”œโ”€โ”€ visited/ โ”‚ โ””โ”€โ”€ 2024/ โ”œโ”€โ”€ by-cuisine/ โ””โ”€โ”€ by-occasion/

To-Try Entry

# sushi-nakazawa.md ## Location West Village, NYC ## Cuisine Omakase sushi ## Source Friend recommendation ## Price Range $$$$ ## Notes Need reservation weeks ahead

Visited Entry

  • # la-mercerie-2024-03.md
  • ## Date
  • March 15, 2024
  • ## Occasion
  • Anniversary dinner
  • ## What We Ordered
  • Burrata (excellent)
  • Duck breast (slightly dry)
  • Chocolate soufflรฉ (must order)
  • ## Verdict
  • โ˜…โ˜…โ˜…โ˜…โ˜† โ€” Would return for brunch

Favorites

# joes-pizza.md ## Go-To Order Plain slice, extra crispy ## Best For Quick lunch, late night ## Notes Cash only, expect line

By-Cuisine and By-Occasion

  • Simple lists linking to favorites:
  • # date-night.md
  • La Mercerie โ€” beautiful space
  • Via Carota โ€” classic Village
  • Carbone โ€” never fails

What To Track

Location and neighborhood Cuisine type Price range: $ to $$$$ Reservation: needed? how far ahead? Standout dishes Rating after visit

Surfacing Recommendations

When user asks "where should we eat": Ask occasion and cuisine preference Check THEIR saved places first Suggest from their data before general knowledge

What To Surface

"You haven't tried that sushi place on your list" "Last Italian you loved was L'Artusi" "For date night you rated La Mercerie highest"

Progressive Enhancement

Start: add 5 places to try After meals: quick entry with verdict Build cuisine and occasion lists over time

What NOT To Do

Recommend unsaved places without asking Forget dietary restrictions Over-organize โ€” simple notes work

Category context

Writing, remixing, publishing, visual generation, and marketing content production.

Source: Tencent SkillHub

Largest current source with strong distribution and engagement signals.

Package contents

Included in package
1 Docs
  • SKILL.md Primary doc