Home · Skills · Lease Trade Out Analyzer
Back to all skills

Lease Trade Out Analyzer

Analyzes whether to renew an existing tenant or trade out for a new one with full financial comparison. Models renewal economics (lower TI, no downtime, known credit) vs trade-out economics (market rent mark-up, TI/LC cost, vacancy cost, leasing commission, unknown credit risk). Produces NPV comparison with breakeven analysis.

What this skill does

Lease Trade Out Analyzer is an A.CRE Intelligence Hub skill that gives your AI agent the analyst-grade workflow a senior commercial real estate professional would run. Analyzes whether to renew an existing tenant or trade out for a new one with full financial comparison. Models renewal economics (lower TI, no downtime, known credit) vs trade-out economics (market rent mark-up, TI/LC cost, vacancy cost, leasing commission, unknown credit risk). Produces NPV comparison with breakeven analysis. Analyzes whether to renew an existing tenant or trade out for a new one with full financial comparison. Models renewal economics lower TI, no downtime, known credit vs trade-out economics market rent mark-up, TI/LC cost, vacancy cost, leasing commission, unknown credit risk . Produces NPV comparison with breakeven analysis. Activate it inside ChatGPT, Claude, Manus, or OpenClaw by saying something like "Use the Lease Trade Out Analyzer skill" — the Hub routes the request to this skill and the underlying primary-source CRE data feeds backends automatically.

How you'll use it

"Use the Lease Trade Out Analyzer skill"

Say something like this to your AI agent in the Hub, Claude, or ChatGPT to activate this skill.

Skill activation rules

Detailed routing logic, prompts the skill responds to, and operational guardrails as documented by the author.

Analyzes whether to renew an existing tenant or trade out for a new one with full financial comparison. Models renewal economics (lower TI, no downtime, known credit) vs trade-out economics (market rent mark-up, TI/LC cost, vacancy cost, leasing commission, unknown credit risk). Produces NPV comparison with breakeven analysis.

What's inside

Lease Trade-Out Analyzer

You are a senior asset manager and leasing strategist who never makes renewal-or-trade-out decisions on instinct. Every decision is backed by a full NPV comparison, breakeven analysis, and risk-adjusted overlay. You model both paths with discipline --…

Show full previewShow less

Lease Trade-Out Analyzer

You are a senior asset manager and leasing strategist who never makes renewal-or-trade-out decisions on instinct. Every decision is backed by a full NPV comparison, breakeven analysis, and risk-adjusted overlay. You model both paths with discipline -- renewal economics (lower TI, no downtime, known credit) against trade-out economics (market rent mark-up, full TI and LC cost, vacancy carrying cost, unknown credit risk) -- and produce a clear recommendation with quantified confidence. You operate at institutional standards: no concession given without NPV justification, no vacancy accepted without breakeven validation.

When to Activate

Trigger on any of these signals:

Full instructions and any reference files ship in the .skill bundle.

Bundle structure
lease-trade-out-analyzer/
├── SKILL.md                             # Required: instructions + metadata
└── references/                          # Optional: documentation
    ├── market-ti-benchmarks.yaml        # 13.8 KB
    ├── trade-out-cost-calculator.md     # 11.5 KB
    └── trade-out-decision-framework.md  # 12.8 KB

Who built it

With contributions from Avi Hacker.

How to run it

Not in the Hub? Download the .skill bundle above and follow the A.CRE skills install guide → to load it into Claude Desktop, ChatGPT, Cursor, or any other agent that supports skills.

Already in the Hub. If you're an AI.Edge Pro or A.CRE Accelerator member, this skill is bundled into the A.CRE Intelligence Hub direct connector (MCP server) — just ask your agent.

About this skill

Third-Party skill. This skill is redistributed under the Apache-2.0 license and is not authored or endorsed by Adventures in CRE. Use is governed by the upstream license and the original creator's terms. Original attribution: Mario Urquia (link) and contributors (Avi Hacker).