JV, preferred equity, programmatic structures, and promote mechanics
npx claudepluginhub firststreetai/realestate-services-plugins --plugin acquisitions-investmentsThis skill uses the workspace's default tool permissions.
Framework for modeling and comparing acquisition structures. Uses validated waterfall calculation code.
Provides Ktor server patterns for routing DSL, plugins (auth, CORS, serialization), Koin DI, WebSockets, services, and testApplication testing.
Conducts multi-source web research with firecrawl and exa MCPs: searches, scrapes pages, synthesizes cited reports. For deep dives, competitive analysis, tech evaluations, or due diligence.
Provides demand forecasting, safety stock optimization, replenishment planning, and promotional lift estimation for multi-location retailers managing 300-800 SKUs.
Framework for modeling and comparing acquisition structures. Uses validated waterfall calculation code.
returns.py:calculate_waterfall()| Factor | Favors JV | Favors Direct | Favors Pref Equity |
|---|---|---|---|
| Capital availability | Low GP capital | Ample capital | Capital-constrained |
| Deal size | Large (>$50M) | Moderate | Any |
| GP track record | Proven (LP will trust) | N/A | Any |
| Return profile | High enough for promote | Moderate | High for sponsor |
| Complexity tolerance | Higher | Lower | Moderate |
All promote and waterfall calculations MUST be performed by scripts/returns.py:calculate_waterfall(). Do NOT reason through promote tiers or catch-up provisions in natural language.