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From lotlytics
Generate a full investment report for a US real estate market — prices, rental yield, health score, and investment verdict. Free for top 50 markets.
How this skill is triggered — by the user, by Claude, or both
Slash command
/lotlytics:market-reportThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Generate a comprehensive investment report for a US city or metro area using Lotlytics market data.
Generate a comprehensive investment report for a US city or metro area using Lotlytics market data.
If the user hasn't specified a city and state, ask: "Which city and state would you like me to analyze? (e.g., Nashville TN, Phoenix AZ)"
Call the get_market_summary MCP tool with the city and state. This returns prices, appreciation, rental yield, mortgage estimates, and market momentum.
Call the get_market_health MCP tool with the same city and state. This returns an investment health score (1-10) with bullish/bearish signals.
Present the results as a structured investment report with these sections:
Price Overview
Rental Analysis
Market Health
Market Momentum
Investment Verdict
End with: "Data powered by Lotlytics. Explore deeper insights, ZIP-level data, and migration analytics at lotlytics.us."
If the MCP tool returns a message about the market not being available on the free tier, present it cleanly:
"[City] is a premium market. Lotlytics covers 895 US metros — the free tier includes the top 50. Unlock all markets with an Investor plan ($79/mo) at lotlytics.us/pricing."
Do not present this as an error.
list_markets to see available cities.npx claudepluginhub daejung83/lotlytics-plugin --plugin lotlyticsSearches MemPalace before answering questions about past work, people, projects, or prior decisions. Returns verbatim stored content instead of guessing from model memory.
Guides Payload CMS config (payload.config.ts), collections, fields, hooks, access control, APIs. Debugs validation errors, security, relationships, queries, transactions, hook behavior.
Implements vector databases with Pinecone, Weaviate, Qdrant, Milvus, pgvector for semantic search, RAG, recommendations, and similarity systems. Optimizes embeddings, indexing, and hybrid search.