Lease Abstract Extractor
Extract key lease terms (dates, rent, deposit, renewal and notice deadlines, fees, responsibilities) into a table or JSON, with red flags flagged.
New Added
Use it when
Onboard a new property or portfolio, prepare for an acquisition, or build your lease calendar without reading every page by hand.
Not for
Legal interpretation. Confirm anything unusual with an attorney, and redact SSNs and bank info before pasting.
The prompt
Fill in the variables (optional)
Type below and the prompt updates. Anything you leave blank stays as a {{variable}} for you to fill in later. Nothing you type leaves your browser.
Table or JSON
Paste the lease (redact SSNs, bank details) or upload the PDF in a model that reads files
You are an expert lease analyst. Extract the following from the LEASE TEXT. Use only what is written. If a term is missing or unclear, write "Not found" or "Unclear: [quote]". Never guess. Fields: - Parties (landlord entity, tenant names), property address, unit - Lease start date, end date (format YYYY-MM-DD), term length - Monthly rent, due date, grace period, late fee terms - Security deposit amount; other deposits/fees (pet, admin, parking, storage) - Renewal terms (auto-renew? notice to renew/vacate: how many days, by whom) - Rent increase terms - Utilities: who pays which - Maintenance responsibilities (tenant vs. landlord), including lawn/snow/pests - Pets, smoking, subletting, occupancy limits - Early termination terms - Entry/notice requirements - Any unusual or one-sided clauses (RED FLAGS), quoting them Output format: {{output_format}} Then add: KEY DATES (a list of calendar reminders to set, e.g., "Notice-to-vacate deadline: 60 days before end date"), and CONFIDENCE: High/Medium/Low with one sentence on why (e.g., scanned text was garbled). LEASE TEXT {{lease_text}}
Variables
| Variable | What to enter | Example |
|---|---|---|
{{output_format}} | Table or JSON | a two-column table (Field | Value) |
{{lease_text}} | Paste the lease (redact SSNs, bank details) or upload the PDF in a model that reads files | [Residential Lease Agreement text...] |
Example output
Illustrative output using the example values. Your results will vary by AI tool and inputs. All names and details are fictional.
| Field | Value | |---|---| | Start / End | 2026-03-01 / 2027-02-28 (12 months) | | Monthly rent | $1,250, due on the 1st | | Grace period / late fee | 5 days; $50 on day 6, then $10/day, max $150 | | Security deposit | $1,250 | | Pet fees | $300 non-refundable pet fee; $25/mo pet rent | | Renewal | Auto-renews month-to-month unless either party gives 60 days' written notice | | Utilities | Tenant: electric, gas, internet. Landlord: water, sewer, trash | | Lawn/snow | Tenant mows; landlord handles snow removal | | Early termination | 2 months' rent fee with 60 days' notice | | RED FLAGS | "Tenant responsible for all repairs under $500," which may conflict with habitability law in some states | KEY DATES: Notice deadline 2026-12-30 (60 days before end) · Rent due the 1st · Late fee starts the 6th CONFIDENCE: High. Clean text, all core fields found.
Tips
- Ask for JSON if you plan to import into a spreadsheet or database.
- Run it on your oldest leases first; they usually have the most surprises.
- Coming soon: a hosted DoorPrompts lease abstractor. Follow @doorprompts on X to hear first.
Works in
Don't paste anything you're not allowed to share (SSNs, bank details, private tenant records) into an AI tool. Check your company's AI policy.
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