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Cre document ingestion

Skill ahacker-1/cre-agent-skills/claude-code-plugins/cre-document-ingestion

Commercial real estate AI agent skills for CRE underwriting, due diligence, financing, brokerage, legal and closing workflows - standalone prompts for Claude Code, ChatGPT, Cursor, and other LLMs.

Install
npx -y skills add ahacker-1/cre-agent-skills --skill cre-document-ingestion

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CRE Document Ingestion suite — 4 specialist skills for classifying and extracting structured data from deal documents including rent rolls, T-12 financials, and offering memoranda.

SKILL.md

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CRE Document Ingestion Suite

You have access to 4 specialist document processing skills for commercial real estate deal packages.

Available Skills

SkillFileUse When
Document Classifierskills/document-classifier.mdUser provides one or more deal documents and needs them identified by type (rent roll, T-12, offering memo, lease, survey, etc.)
Rent Roll Parserskills/rent-roll-parser.mdUser provides a rent roll file and needs structured data extracted — unit numbers, tenants, lease dates, rents, deposits, status
Financials Parserskills/financials-parser.mdUser provides a T-12 or operating statement and needs structured extraction — income lines, expense categories, monthly trends
Offering Memo Parserskills/offering-memo-parser.mdUser provides an offering memorandum and needs key data extracted — property details, financial projections, market data, investment highlights

How to Use

  1. If the user provides documents without specifying what they are, start with the Document Classifier
  2. Once document types are identified, load the appropriate parser skill
  3. Follow the Strategy steps in the loaded skill exactly
  4. Produce structured output in the format specified by the skill
  5. Run Quality Checks before delivering results

Recommended workflow for a full deal package:

  1. Read skills/document-classifier.md → classify all documents
  2. For each rent roll: Read skills/rent-roll-parser.md → extract
  3. For each T-12/financial: Read skills/financials-parser.md → extract
  4. For each offering memo: Read skills/offering-memo-parser.md → extract

If the user says "$ARGUMENTS", use that to determine which skill to load.

Quick Reference

Document Classifier — Identifies: rent rolls, T-12/T-3 operating statements, offering memoranda, leases, title commitments, surveys, Phase I ESAs, appraisals, insurance certificates, tax returns, entity documents. Outputs: document type, confidence level, extractable data fields.

Rent Roll Parser — Extracts: unit number, unit type, square footage, tenant name, lease start/end, monthly rent, security deposit, unit status, move-in date, concessions. Validates: unit count completeness, rent reasonableness, date consistency.

Financials Parser — Extracts: income line items (rental income, vacancy loss, other income), expense categories (taxes, insurance, utilities, R&M, management, payroll, turnover, admin), monthly and annual totals. Calculates: per-unit metrics, expense ratios, year-over-year trends.

Offering Memo Parser — Extracts: property name/address, unit count/mix, year built, lot size, asking price, in-place NOI, pro forma NOI, cap rate, occupancy, market highlights, seller's financial projections, comparable sales, rent comps.

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Skills are one crate of 328,083. Ordering is by how many stacks a row turns up in, so the top of any crate is what has actually been picked rather than what has the most stars.