Xiaolu Property Search

Problem being solved

Online property search is slowed by three recurring issues: misleading photos, opaque transaction prices, and under-specified requirements. Xiaolu Property Search organizes these lookups into a CLI workflow, covering second-hand homes, new builds, and rentals so an agent can query listings, market data, and neighborhood information in conversation instead of manually stitching together browser searches.

How the skill works

• Intent handling: defaults to second-hand homes; when a request is vague, ask for city, budget, commute, school district, or neighborhood constraints.
• Command discovery: read the CLI help output before querying and choose the relevant capability, avoiding guessed parameters that fail.
• Query dimensions: supports AI search, Lobster selection, aerial search, school-district search, subway search, and map-based search; results can include verified photos, transaction data, and school or neighborhood details.
• Output convention: describe each listing, neighborhood, transaction, school, or new-home item separately with highlights and a mini-program link for saving or contacting agents.
• Runtime constraints: the API allows 1 request per second; 429 means retry later; missing API key configuration should follow the provided page instructions.

Boundaries

City coverage is limited; if a city is unsupported, direct users to the Xiaolu Property Search app. The skill focuses on property information retrieval and lead organization, not on physical inspections, title verification, loan calculations, or transaction decisions.