Research real estate properties with RAG-backed market analysis
Guide an agent through property search, buyer/renter preference capture, and evidence-backed shortlist notes from structured listing data.
npx skills add agentskillexchange/skills --skill rag-backed-real-estate-property-research
Use this skill when an operator needs an agent to turn structured real-estate listing data into conversational property-research notes and evidence-backed shortlists. The agent should load or connect to a known property dataset, normalize listing attributes, embed relevant records, retrieve candidate properties, ask clarifying preference questions, and produce reviewable summaries with the matching evidence, data source, and assumptions called out.
What this skill actually does
Invoke this instead of using a normal real-estate portal when the task requires repeatable analysis over a private, agency-owned, or custom listing dataset; multi-turn buyer/renter intake; or explainable summaries that combine search filters with retrieved context. Do not use it to make final financial, legal, appraisal, lending, valuation, buyer-representation, or buyer/seller recommendation decisions. Human review is required before sharing market advice or client-facing conclusions.
Scope boundary: this is a workflow for operating a RAG-backed property-research assistant using the referenced implementation pattern. It is not a generic Streamlit app listing, a LangChain framework card, a valuation tool, or a substitute for licensed real-estate judgment. The useful unit is the repeatable operator workflow: ingest property data, retrieve matching listings, summarize fit, surface limitations, and keep shortlist notes auditable.