Offering Memo Parser
Pull property characteristics, deal terms, and financial highlights out of an OM or flyer.
★ 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 data from broker marketing material so underwriting can start immediately.
What it does
- Parses offering memoranda, brochures, and property flyers
- Extracts property characteristics and deal terms
- Captures the financial highlights as presented
- Records seller and broker information alongside the numbers
- Pairs with the Rent Roll and T12 parsers to cross-check what the OM claims
When to use it
Use this skill when you have an offering memorandum, marketing package, or property flyer for a commercial real estate deal and need to extract structured data from it. It handles PDF marketing documents, PowerPoint decks, Word documents, and property flyers (images).
What to have ready
- The offering memorandum, marketing brochure, or property flyer — as a PDF, PowerPoint, Word document, or image
- If the document is an image or scanned PDF, note that OCR quality will affect confidence
- Optionally, tell the parser if there is specific data you need prioritized (e.g., "I especially need the unit mix and asking price")
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 Offering Memo Parser skill — I've got the offering memorandum, marketing brochure."
What you get back
A structured report covering source, physical, amenities, unitMix, financials, investmentHighlights, and seller. 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.
Offering Memo Parser
Extract property characteristics, deal terms, financial highlights, and seller information from an Offering Memorandum (OM), marketing brochure, or property flyer.
When to Use This Skill
Use this skill when you have an offering memorandum, marketing package, or property flyer for a commercial real estate deal and need to extract structured data from it. It handles PDF marketing documents, PowerPoint decks, Word documents, and property flyers (images). Use it at the beginning of deal evaluation to get the key facts out of the OM before underwriting across multifamily, industrial, and other CRE sectors.
What You'll Need to Provide
- The offering memorandum, marketing brochure, or property flyer — as a PDF, PowerPoint, Word document, or image
- If the document is an image or scanned PDF, note that OCR quality will affect confidence
- Optionally, tell the parser if there is specific data you need prioritized (e.g., "I especially need the unit mix and asking price")
Mission
Parse Offering Memorandums (OMs), marketing brochures, and property flyers to extract property characteristics, asking price, and seller information.
Input Formats
- PDF marketing documents
- PowerPoint presentations
- Word documents
- Property flyers (images)
Strategy
Step 1: Identify Document Structure
Scan the document for standard OM section headers:
- Investment Summary / Executive Summary
- Property Overview / Property Description
- Location Overview / Market Overview
- Financial Summary / Financial Highlights
- Unit Mix / Floor Plans
- Offering Terms / Pricing Guidance
- Contact Information / Broker Information
Step 2: Extract Property Identification
{
"property": {
"name": "Parkview Apartments",
"address": "4200 Parkview Drive",
"city": "Austin",
"state": "TX",
"zip": "78745",
"county": "Travis",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.