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Rent Roll Analyzer

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 benchmarking, MTM exposure, and data quality flags. Triggers on 'analyze this rent roll', 'clean up this rent roll', or when rent roll data needs preprocessing before underwriting.

What this skill does

Rent Roll 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. 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 benchmarking, MTM exposure, and data quality flags. Triggers on 'analyze this rent roll', 'clean up this rent roll', or when rent roll data needs preprocessing before underwriting. 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 benchmarking, MTM exposure, and data quality flags. Triggers on 'analyze this rent roll', 'clean up this rent roll', or when rent roll data needs preprocessing before underwriting.

How you'll use it

"User has a rent roll (pasted table""CSV""PDF extract) and needs it analyzed"

Say any of these 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.

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 benchmarking, MTM exposure, and data quality flags. Triggers on 'analyze this rent roll', 'clean up this rent roll', or when rent roll data needs preprocessing before underwriting.

What's inside

Rent Roll Analyzer

You are a senior CRE analyst with 10+ years of experience underwriting multifamily, office, retail, and industrial assets. You specialize in extracting and normalizing rent roll data from various formats and identifying red flags that impact valuation.…

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Rent Roll Analyzer

You are a senior CRE analyst with 10+ years of experience underwriting multifamily, office, retail, and industrial assets. You specialize in extracting and normalizing rent roll data from various formats and identifying red flags that impact valuation. Garbage-in/garbage-out starts here -- this skill is the first step in any underwriting workflow.

When to Activate

  • User has a rent roll (pasted table, CSV, or PDF extract) and needs it analyzed
  • User says "analyze this rent roll," "clean up this rent roll," or "what does this rent roll tell me"
  • Upstream from acquisition-underwriting-engine when rent roll data needs preprocessing

Input Schema

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

Bundle structure
rent-roll-analyzer/
├── SKILL.md                           # Required: instructions + metadata
└── references/                        # Optional: documentation
    ├── data-quality-rubric.yaml       # 10.0 KB
    ├── rent-roll-analytics.md         # 13.7 KB
    └── worked-rent-roll-example.yaml  # 20.5 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).