Home · Skills · Cost Segregation Analyzer
Back to all skills

Cost Segregation Analyzer

Evaluates whether a cost segregation study is worth pursuing for a CRE property by estimating reclassifiable components, quantifying PV of accelerated depreciation, modeling recapture at disposition, and determining breakeven hold period. Factors in bonus depreciation phase-down and passive activity limitations.

What this skill does

Cost Segregation 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. Evaluates whether a cost segregation study is worth pursuing for a CRE property by estimating reclassifiable components, quantifying PV of accelerated depreciation, modeling recapture at disposition, and determining breakeven hold period. Factors in bonus depreciation phase-down and passive activity limitations. Evaluates whether a cost segregation study is worth pursuing for a CRE property by estimating reclassifiable components, quantifying PV of accelerated depreciation, modeling recapture at disposition, and determining breakeven hold period. Factors in bonus depreciation phase-down and passive activity limitations. Activate it inside ChatGPT, Claude, Manus, or OpenClaw by saying something like "Use the Cost Segregation 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 Cost Segregation 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.

Evaluates whether a cost segregation study is worth pursuing for a CRE property by estimating reclassifiable components, quantifying PV of accelerated depreciation, modeling recapture at disposition, and determining breakeven hold period. Factors in bonus depreciation phase-down and passive activity limitations.

What's inside

Cost Segregation Analyzer

You are a CRE tax optimization engine specializing in cost segregation analysis. Given property acquisition details, you estimate the present value of accelerated depreciation benefits, model Section 1250/1245 recapture at disposition, and produce a…

Show full previewShow less

Cost Segregation Analyzer

You are a CRE tax optimization engine specializing in cost segregation analysis. Given property acquisition details, you estimate the present value of accelerated depreciation benefits, model Section 1250/1245 recapture at disposition, and produce a go/no-go recommendation on engaging an engineering firm for a formal study. Every number must be traceable, every assumption explicit.

Disclaimer: This analysis produces preliminary estimates for decision-making. A formal cost segregation study requires a qualified engineering firm and CPA review. Always consult qualified tax counsel before implementing.

When to Activate

Trigger on any of these signals:

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

Bundle structure
cost-segregation-analyzer/
├── SKILL.md                          # Required: instructions + metadata
└── references/                       # Optional: documentation
    ├── cost-seg-methodology.md       # 13.0 KB
    └── worked-cost-seg-example.yaml  # 17.5 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).