kylinfish

kylinfish / tw-house-ops

Public

AI-powered house hunting pipeline for Taiwan, built on Claude Code. Inspired by @santifer/career-ops — same ops-style approach, applied to 台灣租屋 & 購屋.

45
3
69% credibility
Found Apr 11, 2026 at 45 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
JavaScript
AI Summary

An AI-powered workflow for Claude that automates discovering, evaluating, tracking, and planning for rental and purchase properties across major Taiwan real estate websites.

How It Works

1
🏠 Discover your house hunting buddy

You hear about a smart AI helper that scans Taiwan rental and buying sites to find dream homes matching your needs.

2
📱 Open it in your AI chat

Download the folder and load it into your favorite AI assistant like Claude, where it guides you through a quick setup.

3
👤 Share your wishlist

Tell it your budget, favorite neighborhoods, commute time, and must-haves like parking or pet-friendly spots—it remembers everything.

4
Start hunting
🌆
Scan neighborhoods

Let it search popular sites for fresh listings that fit your criteria.

🔗
Check one listing

Paste a home link to get an instant deep dive evaluation.

5
📋 Review smart reports

Get easy-to-read scores on price fairness, location perks, and risks, plus commute times and market comparisons.

6
📊 Track and compare

Build a personal list of favorites, compare them side-by-side, and plan visits with checklists.

🎉 Your perfect home plan

Celebrate having a clear tracker of top picks, affordability checks, and next steps to snag your ideal place.

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Star Growth

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AI-Generated Review

What is tw-house-ops?

tw-house-ops is an AI-powered house search pipeline for Taiwan's rental and buying markets, scanning sites like 591, Rakuya, and Sinyi for new listings that match your profile. Paste a URL or type `scan` to trigger evaluations comparing prices to real estate registries, calculating commutes, scoring on price, space, location, condition, and risks—then tracks everything in Markdown tables. Built in JavaScript on Claude Code, it requires agent-browser for real page scraping, delivering reports, affordability calcs, and visit prep lists without you lifting a finger.

Why is it gaining traction?

Inspired by @santifer/career-ops, it applies the same ops-style automation to AI-powered house hunting, standing out with batch pipelines (`pipeline`), side-by-side compares (`compare 001, 003`), and upgrade planning for sellers—features no generic scraper offers. Developers dig the Claude-first workflow: clone, onboard in minutes, and command-line simplicity yields structured insights like five-dimension scores and negotiation strategies. As an AI-powered GitHub project, it hooks those tired of manual Zillow-style browsing in Taiwan's fragmented market.

Who should use this?

Taiwan renters hunting under 30k TWD/month, first-time buyers maxing 30M TWD homes, or upgraders planning sell-buy swaps in Taipei districts like Da'an. Devs fluent in Claude Code and npm who want AI-powered search to filter deal-breakers like ground floors or old buildings before wasting weekends viewing duds. Skip if you're not in Taiwan or prefer no-browser agents.

Verdict

With 45 stars and a 0.7% credibility score, it's early-stage but docs are solid and tests exist—worth forking for personal use if you're in the market. Production teams, wait for more polish; solo house hunters, try it now for the time savings.

(198 words)

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