Rent Roll Parser
Parse any rent roll — Excel, CSV, or PDF — into clean structured underwriting data.
★ 105 on GitHub0 downloads on LenderSkills
Install it in one line — paste a single command into Claude, ChatGPT or Cursor and it writes the skill into your project.
Free, and about thirty seconds: a work email and a six-digit code.
Downloading shares your name, firm, role, and email with Avi Hacker, J.D.. That introduction is what keeps every skill here free.
What this skill does
Extracts structured unit mix, occupancy, in-place rents, and lease expiration data from rent rolls in any format.
What it does
- Handles Excel, CSV, and PDF rent rolls, including messy broker formats
- Produces a normalized unit-level dataset ready for a model
- Flags anomalies: duplicate units, missing rents, occupancy inconsistencies
- Pairs naturally with any underwriting or valuation workflow
When to use it
Use this skill when you have a rent roll file and need to extract clean, structured data from it. It handles inconsistent column headers, varied unit type naming conventions, multiple rent columns, and mixed occupancy status values.
What to have ready
- The rent roll file — as an Excel spreadsheet, CSV file, or PDF
- If the file has an unusual structure (e.g., multiple property tabs, summary-only without unit detail, or combined with other reports), describe it
- Optionally, provide the total unit count so the parser can verify its extraction matches
How to use it
- Download it with the button above. You'll sign in with a work email — that's how the creator knows who is using their skill.
- Copy the install prompt from the "Run it in Claude" box, and paste it into Claude along with the file. Claude installs the skill, fills in your firm's details where the file has
[BRACKETED]placeholders, and runs a quick test with you. - Then just ask in plain English. Claude picks the skill up on its own when a request matches it. Anything it still needs, it asks you for — it won't invent a number.
"Use the Rent Roll Parser skill — I've got the rent roll file."
What you get back
A structured report covering source, summary, income, unitMix, leaseExpirations, units, and warnings. You get it as readable analysis plus the underlying data, so it can feed straight into a memo or another skill.
Good to know
- Output quality tracks input quality. A missing figure is flagged as missing — it is never estimated to fill a gap.
- Every draft is a starting point for your own review, not a finished decision.
- Runs anywhere Claude does: the Claude app, Claude Desktop, or Claude Code.
Source & credit
Imported from the open-source cre-agent-skills library by Avi Hacker, J.D. (github.com/ahacker-1/cre-agent-skills), Apache-2.0 license. The author's content is unmodified apart from a legal disclaimer appended at the end of the package. Full credit to the author.
Legal disclaimer
This skill drafts; it does not decide. Its output is not legal, tax, accounting, appraisal, or investment advice, and using it creates no attorney-client, fiduciary, or advisory relationship. Nothing it produces is a commitment to lend or an offer to sell a security. Verify every number, date, citation, and conclusion against the source documents, and have a qualified professional licensed in the relevant jurisdiction review the work before you rely on it or send it to a borrower, investor, counterparty, or regulator. Laws, rates, and market data change. The final work product is yours.
Inside this skill
The actual file you get. Members can read it in full before saving it.
Rent Roll Parser
Parse a rent roll document (Excel, CSV, or PDF) and extract structured unit mix, occupancy, rent, and lease expiration data for underwriting analysis.
When to Use This Skill
Use this skill when you have a rent roll file and need to extract clean, structured data from it. It handles inconsistent column headers, varied unit type naming conventions, multiple rent columns, and mixed occupancy status values. Use it at the start of underwriting to get reliable unit-level and aggregate rent data before building a financial model.
What You'll Need to Provide
- The rent roll file — as an Excel spreadsheet, CSV file, or PDF
- If the file has an unusual structure (e.g., multiple property tabs, summary-only without unit detail, or combined with other reports), describe it
- Optionally, provide the total unit count so the parser can verify its extraction matches
Mission
Parse rent roll documents (Excel, CSV, PDF) and extract structured unit mix, occupancy, and rent data for underwriting analysis.
Strategy
The following sections describe the input formats recognized and the step-by-step extraction logic applied to parse rent roll data.
Input Formats
Excel/CSV Rent Rolls
Common column headers to look for:
| Category | Possible Headers |
|---|---|
| Unit ID | Unit, Unit #, Unit No, Apt, Apartment |
| Unit Type | Type, Floorplan, Floor Plan, Bed/Bath, BR/BA |
| Bedrooms | BR, Beds, Bedrooms |
| Bathrooms | BA, Baths, Bathrooms |
| Sq Ft | SF, SqFt, Sq Ft, Square Feet, Size |
| Market Rent | Market, Market Rent, Asking Rent, Quoted Rent |
| Actual Rent | Rent, Current Rent, Contract Rent, In-Place Rent, Actual |
| Status | Status, Occupancy, Occupied |
| Tenant | Tenant, Resident, Name |
| Lease Start | Start, Move In, Move-In, Lease Start |
| Lease End | End, Lease End, Expiration, Expires |
| Move Out | Move Out, Notice, NTV |
PDF Rent Rolls
- Look for tabular data
Reading the full skill counts as a download. The contributor receives your name, company, and email.
Ratings & reviews
No written reviews yet. If you run this on a live file, say how it went. The next lender reading this page is deciding whether to trust it.
Examination record
Run it in Claude
- Copy the install command above
- Paste it into Claude, ChatGPT or Cursor
- It writes the skill in, fills in your firm’s details, and test-runs it with you
Prefer the file? The prompt above is for a package you already downloaded.
Details
More from Avi Hacker, J.D.
Imported from their public repository with attribution. Their other skills, and where to find the original, are on their contributor page.