managing-reit-portfolio-analysis
Structures REIT portfolio evaluation with property-level analysis, geographic diversification, and tenant concentration. Use when analyzing REIT portfolios, evaluating property mix, or assessing concentration risk.
Best use case
managing-reit-portfolio-analysis is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Structures REIT portfolio evaluation with property-level analysis, geographic diversification, and tenant concentration. Use when analyzing REIT portfolios, evaluating property mix, or assessing concentration risk.
Teams using managing-reit-portfolio-analysis should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/managing-reit-portfolio-analysis/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How managing-reit-portfolio-analysis Compares
| Feature / Agent | managing-reit-portfolio-analysis | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Structures REIT portfolio evaluation with property-level analysis, geographic diversification, and tenant concentration. Use when analyzing REIT portfolios, evaluating property mix, or assessing concentration risk.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# Managing REIT Portfolio Analysis Structures REIT portfolio evaluation with property-level analysis, geographic diversification, tenant concentration assessment, and sector allocation review. ## When To Use - Evaluating an equity or mortgage REIT's property holdings for investment due diligence - Assessing geographic and tenant concentration risk within a REIT portfolio - Comparing sector allocation (office, industrial, retail, residential, specialty) against benchmarks or peers - Reviewing portfolio quality ahead of capital raises, credit facility renewals, or rating agency presentations - Monitoring portfolio drift from stated investment mandate or target allocation ## Inputs To Gather - **Property schedule**: Full asset list with property name, type, location (MSA/state), square footage or unit count, acquisition date, and acquisition cost or current carrying value - **Rent roll summary**: Top tenants by annualized base rent (ABR) or percentage of total revenue, lease expiration schedule, weighted-average lease term (WALT) - **Financial data**: Net operating income (NOI) per property or segment, same-store NOI growth, occupancy rates, cap rates at acquisition vs. current market - **Debt schedule**: Property-level or pool-level encumbrances, LTV ratios, maturity profile - **Benchmark data**: Peer REIT allocations, NAREIT sector indices, or internal target allocation policy [VERIFY: confirm which benchmark set the stakeholder uses] ## Workflow 1. **Compile property-level data** - Normalize property types into standard categories (office, industrial, multifamily, retail, healthcare, data center, self-storage, specialty) - Confirm total gross asset value (GAV) or enterprise value denominator for percentage calculations - Flag any properties with missing NOI, occupancy, or valuation data as [VERIFY] 2. **Analyze sector allocation** - Calculate each property type's share of GAV, NOI contribution, and square footage - Compare against the REIT's stated strategy and peer median allocations - Identify overweight/underweight positions relative to benchmarks 3. **Assess geographic diversification** - Map properties by MSA, state, and region - Calculate concentration metrics: percentage of GAV and NOI in top 1, 3, 5, and 10 markets - Flag single-market concentrations exceeding 20% of GAV or NOI as elevated risk - Note exposure to markets with adverse demand trends (e.g., office in high-vacancy MSAs) [VERIFY: current market conditions for flagged MSAs] 4. **Evaluate tenant concentration** - Rank tenants by ABR contribution; identify top 10 tenants and their cumulative share - Flag any single tenant representing >5% of ABR, or top 10 tenants exceeding 40% collectively - Assess tenant credit quality (investment-grade vs. non-rated) where data is available [VERIFY: credit ratings current as of analysis date] - Map lease expiration schedule by year for the next 5 years; highlight any year with >15% of ABR rolling 5. **Review portfolio quality metrics** - Calculate weighted-average occupancy across portfolio - Compute weighted-average remaining lease term - Assess same-store NOI growth trend (trailing 4–8 quarters) - Identify bottom-quartile assets by occupancy, NOI margin, or cap rate spread 6. **Synthesize risk and opportunity flags** - Summarize concentration risks (geographic, tenant, sector) - Identify assets that may be disposition candidates (underperforming, non-core) - Note any upcoming lease expirations or debt maturities that cluster in the same period - Highlight alignment or divergence from the REIT's stated investment thesis ## Output Produce a structured management report containing: - **Executive summary**: Portfolio size, sector mix, key concentration metrics, and top-line risk assessment (2–3 paragraphs) - **Sector allocation table**: Property type, property count, GAV, NOI, % of total for each - **Geographic heat map data**: Top 10 MSAs by GAV and NOI with concentration percentages - **Tenant concentration table**: Top 10 tenants, ABR, % of total ABR, credit rating, WALT - **Lease expiration schedule**: Annual ABR rolling for years 1–5, cumulative percentage - **Risk flag summary**: Itemized list of concentration breaches, data gaps, and market-level concerns - **Recommendations**: Specific next steps (rebalancing targets, disposition candidates, further diligence items) ## Quality Checks - All percentages sum correctly to 100% within rounding tolerance (±0.5%) - NOI and GAV totals reconcile to source financial statements or supplemental data - Tenant names and lease terms match the most recent rent roll; stale data is marked [VERIFY] - Geographic classifications use consistent MSA definitions (e.g., Census Bureau CBSA boundaries) [VERIFY: confirm MSA definition standard used] - Concentration thresholds applied match the REIT's own policy limits or credit facility covenants before flagging breaches - Report clearly distinguishes between confirmed data and analyst estimates
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