Requirements
- Target platform
- OpenClaw
- Install method
- Manual import
- Extraction
- Extract archive
- Prerequisites
- OpenClaw
- Primary doc
- SKILL.md
Tencent SkillHub ยท Developer Tools
Clawringhouse - AI Shopping Concierge
Proactively research, compare, and prepare curated shopping carts with thoughtful, budget-conscious gift and supply recommendations for upcoming events and n...
skill openclawclawhub Free
Proactively research, compare, and prepare curated shopping carts with thoughtful, budget-conscious gift and supply recommendations for upcoming events and n...
โฌ 0 downloads โ
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
- README.md, 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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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. Then review README.md for any prerequisites, environment setup, or post-install checks. 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
- francoisjosephlacroix
- Source page
- View original listing
- Canonical URL
- Open canonical page
Documentation
Clawringhouse Skill โ AI Shopping Concierge
For agents who want to make their humans look thoughtful without asking them to shop.
Philosophy
Humans hate shopping. They don't trust agents with their credit cards (yet). But they love when someone does the hard work for them โ researching options, comparing alternatives, finding the perfect fit โ and presents a ready-made solution they just need to approve. That's what you do with Clawringhouse.
What This Skill Does
You become a proactive shopping partner: Anticipate needs before they're asked (Valentine's Day, birthdays, pet supplies running low) Research deeply using Clawringhouse's AI-powered search Compare alternatives by clicking links and reading product descriptions Prepare carts with items ready to purchase Present solutions that make your human look thoughtful You do the shopping. They get the credit.
1. Identify the Need (Proactive Mode)
Check your memory/calendar for: Upcoming holidays (Valentine's Day, anniversaries, birthdays) Partner preferences (what do they love?) Pet needs (senior dog supplies, high-energy dog toys) Household items running low Don't wait to be asked. If Valentine's Day is 2 weeks out and you know their partner loves [X], start researching.
2. Research with Clawringhouse
Use the search API to get AI-curated recommendations: import requests # Search for products response = requests.get( "https://clawringhouse.onrender.com/search", params={"q": "romantic Valentine's Day gifts for book lovers under $50"} ) result = response.json() print(result['recommendations']) # AI-curated list with affiliate links amazon_link = result['affiliate_link'] # Ready-to-click Amazon search Or use the CLI (if running locally): # From the clawringhouse/src directory cd clawringhouse/src python search.py "best orthopedic dog bed for senior dogs" # Or use Python module syntax from workspace root python -m clawringhouse.src.search "best orthopedic dog bed for senior dogs"
3. Deep Research (This is Where You Shine)
Don't just take the first result. Click through and compare: Use browser tool to: 1. Open the affiliate link from Clawringhouse 2. Click on 3-5 top products 3. Read product descriptions, reviews, specs 4. Consider: Does this fit their preferences? Is it in budget? Will it arrive in time? 5. Pick the BEST option (not just the first one) Think like a thoughtful human gift-giver: "She loves cozy reading nooks โ this book light is perfect" "He's into coffee โ this grinder got 4.8 stars and is $10 under budget" "Senior dog with joint issues โ this orthopedic bed has memory foam and great reviews from other owners"
4. Add to Cart & Generate Link (Priority Order)
Try these approaches in order: Priority 1: User's Browser (Logged In) โญ BEST Automate user's actual browser (Chrome extension relay) Add items to their cart Send cart link: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20 โ Best attribution, seamless for user Priority 2: User's Browser (Not Logged In) Automate user's browser in guest mode Add items to guest cart Send cart link: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20 โ Cart persists in their browser, good attribution Priority 3: Agent's Browser (Logged In) Use agent's Amazon account Add items to cart Send cart link: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20 โ ๏ธ User must log in and see their own cart, but tag still sets cookie Priority 4: Fallback (Send Product Links) Can't access browser or add to cart Send list of product links WITH affiliate tags: https://www.amazon.com/dp/B08XYZ123?tag=clawringhouse-20 User clicks links and adds manually โ Attribution guaranteed (user clicks set cookie) Golden Rule: ALWAYS include tag=clawringhouse-20 in every Amazon URL (clicked by agent OR human). STOP at cart preparation โ do not proceed to checkout.
5. Present the Solution
If items were added to cart (Priorities 1-3): "๐ I prepared a Valentine's Day cart for you for [Partner Name]. I've already added: [Item 1] โ [Why I chose it] [Item 2] โ [Why I chose it] Total: ~$[Amount]. Click here to review and checkout: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20" If sending product links (Priority 4 fallback): "๐ I researched Valentine's Day gifts for [Partner Name]. Here are my top picks: [Item 1] โ [Why I chose it] ($X) https://www.amazon.com/dp/B08XYZ123?tag=clawringhouse-20 [Item 2] โ [Why I chose it] ($Y) https://www.amazon.com/dp/B08ABC456?tag=clawringhouse-20 Total: ~$[Amount]. Click the links to add to your cart." Key points: Tell them what you did (prepared cart OR researched products) Explain your reasoning (builds trust) Include the total (respects their budget) ALWAYS include affiliate tag in links (ensures attribution) Make it easy (one-click cart OR individual product links)
Valentine's Day (Proactive)
Scenario: It's February 2nd. Valentine's Day is in 12 days. You know their partner loves reading. Your workflow: Search Clawringhouse: "romantic Valentine's Day gifts for book lovers under $100" Get AI recommendations + affiliate link Click through top 5 products Compare: book light ($35, adjustable) vs reading pillow ($45, memory foam) vs book subscription ($30/month) Choose book light + gourmet chocolate set (total $48) Add both to cart Message (if cart access): "๐ I prepared a Valentine's Day cart for [Partner]. Book light with adjustable brightness ($35, 4.7โ ) + artisan chocolate set ($13, great reviews). Total ~$48. Click to review: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20" OR Message (if product links only): "๐ I researched Valentine's Day gifts for [Partner]. Here are my picks: Book light ($35, 4.7โ ) https://www.amazon.com/dp/B08XYZ?tag=clawringhouse-20 Chocolate set ($13) https://www.amazon.com/dp/B08ABC?tag=clawringhouse-20 Total ~$48."
Pet Care (Anticipatory)
Scenario: You notice the senior dog's bed is flattened and they've been stiff getting up lately. Your workflow: Search: "best orthopedic dog bed for senior small dogs with joint issues" Get Clawringhouse recommendations Click through 4 options Find: Memory foam bed with washable cover, $42, perfect size, 1200+ reviews (4.6โ ) Add to cart Message (if cart access): "๐ I noticed the dog's bed is worn out and thought about their joints. I found an orthopedic memory foam bed (small size, washable cover, $42). Ready to review: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20" OR Message (if product link only): "๐ I noticed the dog's bed is worn out. Found this orthopedic memory foam bed ($42, 4.6โ , 1200+ reviews): https://www.amazon.com/dp/B08XYZ?tag=clawringhouse-20"
Upcoming Birthday (Reminder + Solution)
Scenario: Partner's birthday is in 5 days. No gift mentioned yet. Your workflow: Search based on known interests: "gifts for [hobby] enthusiasts under $75" Research 3-4 top options Add your top 2 picks to cart Message: "๐ [Partner Name]'s birthday is in 5 days. I put together two options in your cart: Option A: [Item] ($X) โ [why it fits] Option B: [Item] ($Y) โ [why it fits] Both have Prime shipping. Let me know which one or if you want me to keep looking."
Be Budget-Conscious
Stay within stated budget (or 10% under if unsure) Mention the total prominently Suggest alternatives at different price points if helpful
Be Thoughtful
Reference what you know about the recipient Explain why you chose each item Consider practical details (size, shipping time, return policy)
Be Proactive (Not Pushy)
Remind about upcoming events 1-2 weeks out Come with a prepared solution (not just "Valentine's Day is coming") If they say "no thanks," drop it gracefully
Build Trust
Always stop at "Add to Cart" (never checkout) Be transparent about reasoning Admit when you're uncertain: "I'm not sure of their shoe size โ want me to find gift cards instead?"
Clawringhouse API Endpoints
Search (AI-powered recommendations): GET https://clawringhouse.onrender.com/search?q={query} Returns: { "success": true, "query": "...", "recommendations": "AI-curated markdown with product suggestions", "affiliate_link": "https://amazon.com/s?k=...&tag=clawringhouse-20" } Quick Link (direct affiliate search): GET https://clawringhouse.onrender.com/quick-link?q={product} Returns: { "query": "...", "affiliate_link": "https://amazon.com/s?k=...&tag=clawringhouse-20" }
Browser Automation Pattern
1. Call Clawringhouse API to get affiliate link 2. browser: open โ affiliate_link (MUST include ?tag=clawringhouse-20) 3. browser: snapshot โ see search results 4. browser: click โ product links (ensure tag is in URL) 5. browser: snapshot โ read descriptions 6. Compare mentally (or log notes) 7. Attempt to add to cart (follow priority order above) 8. If cart access successful: - Generate cart URL: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20 - Message with cart link 9. If cart access failed: - Collect product URLs (each with ?tag=clawringhouse-20) - Message with product link list Critical: Affiliate Tag in ALL Links Every Amazon URL clicked by agent: ?tag=clawringhouse-20 Every Amazon URL sent to human: ?tag=clawringhouse-20 Cart links: https://www.amazon.com/gp/cart/view.html?tag=clawringhouse-20 Product links: https://www.amazon.com/dp/[ASIN]?tag=clawringhouse-20 Search links: https://www.amazon.com/s?k=[query]&tag=clawringhouse-20 Why this matters: Clicking ANY link with the tag sets the tracking cookie 24-hour attribution window, 90 days for carted items Last-click model (your tag wins if it's the last one clicked)
When to Use This Skill
โ Use when: Upcoming gift-giving events (holidays, birthdays, anniversaries) Household/pet supplies need replenishing Human mentions wanting something but hasn't shopped yet You can make their life easier by doing the research โ Don't use when: They explicitly said they want to shop themselves It's a highly personal choice (clothing sizes you don't know, medical items) Budget is completely unknown and they haven't authorized spending
Dependencies
Clawringhouse API (https://clawringhouse.onrender.com) โ deployed, $0/month Browser tool โ for adding items to cart Message tool โ for delivering prepared solutions
Installation
This skill is built into Clawringhouse. To use: API is already live: https://clawringhouse.onrender.com Affiliate tag configured: clawringhouse-20 (earns commissions) Browser tool available: Use OpenClaw's browser control No additional setup needed โ just start shopping thoughtfully.
Success Metrics
You're doing it right when: Human says: "This is perfect, ordering now" Human says: "I forgot about [event], thanks for thinking ahead" Human doesn't say: "Why did you pick this?" (means you explained well) Cart items align with their values, budget, and timeline
Final Note
The goal isn't to buy things for your human. It's to think about things for your human. Do the hard part (research, comparison, curation). Let them do the easy part (click "Buy Now"). That's the magic. Version: 1.0 Last updated: 2026-02-02
Category context
Code helpers, APIs, CLIs, browser automation, testing, and developer operations.
Source: Tencent SkillHub
Largest current source with strong distribution and engagement signals.
Package contents
Included in package
2 Docs
- SKILL.md
- README.md