This is the Hub's skills library, part of how AI.Edge and the A.CRE Accelerator teach the practical application of AI in commercial real estate. Browse them to see how a skill changes your AI's behavior, then try them in Claude, ChatGPT, or Gemini.
A.CRE
Built by A.CRE
Our in-house skills. Financial-model skills that operate official A.CRE Excel models for Accelerator members, plus capability skills that help AI.Edge members master what their AI can do.
Third-Party
Open-source, third-party
Publicly available CRE skills published under open licenses like MIT and Apache-2.0. We include them so you can see first-hand how a skill changes your AI's behavior. They aren't authored or endorsed by A.CRE, and the original author is credited on every page.
Coordinates the handoff from deal close to an operating asset. Fires when Dealpath
emits the deal-close event (Handoff 1 + Handoff 3 in
reference/connectors/_core/stack_wave4/lifecycle_handoffs.md).…
Builds the annual operating budget from property-level bottoms-up plus portfolio-level
assumptions. Revenue build from rent roll + market reference + renewal policy; expense
build from assumption…
Coordinates the transition from construction delivery to operating asset. Fires
on Procore schedule_milestone `temp_co_received` or `final_co_received` (with
units_ready_for_lease >= 1), or on…
Produces a complete disposition preparation package: T-12 normalization, rent roll scrub, data room index, buyer Q&A, retrade defense, broker selection, marketing timeline, value story, and buyer…
Ingests raw rent rolls (pasted table, CSV, or PDF extract) and produces a clean dataset with layered analytics: rollover schedule, mark-to-market waterfall, tenant concentration risk, WALT, rent…
Generates text-based stacking plans from rent rolls, providing floor-by-floor visual layout of tenant occupancy, lease expiration, contiguous availability analysis, rollover concentration, and…