Agent skill

Cre Document Ingestion

by ahacker-1 in ahacker-1/cre-agent-skills

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.

Apache-2.0Auto-check passedBusiness, Finance & HR

Install Cre Document Ingestion

skills CLI
$ npx skills add ahacker-1/cre-agent-skills --skill cre-document-ingestion -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ahacker-1/cre-agent-skills cre-document-ingestion --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ahacker-1/cre-agent-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/claude-code-plugins/cre-document-ingestion .claude/skills/cre-document-ingestion && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
cre-document-ingestion
GitHub stars
113
Token cost
~1.1k tokens
SKILL.md length
442 words
Files
5
Skills in repo
14
Repo updated
First seen
Licence
Apache-2.0

At a glance

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.

  • Works in 5 steps: If the user provides documents without… → Once document types are identified, load… → Follow the Strategy steps in the loaded… → …
  • Tasks that involve Schema markup
  • SKILL.md covers Available Skills, How to Use, Quick Reference and Attribution
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Cre Document Ingestion is an agent skill from ahacker-1/cre-agent-skills. 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.

Its SKILL.md is about 1.1k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files (for example `skills/document-classifier.md`, `skills/financials-parser.md` and `skills/offering-memo-parser.md`).

It sits in Business, Finance & HR, covering Schema markup and Real estate. The repository describes itself as: Commercial real estate AI agent skills for CRE underwriting, due diligence, financing, brokerage, legal and closing workflows - standalone prompts for Claude Code, ChatGPT… The licence is Apache-2.0.

When your agent uses it

  • Tasks that involve Schema markup
  • Tasks that involve Real estate

Example prompts

  • “/cre-document-ingestion”

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  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

What it can do on your machine

Read from SKILL.md and the folder at commit a9a4e29. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    No scripts in the folder and no shell commands in SKILL.md.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • theaiconsultingnetwork.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Cre Document Ingestion loads about 1.1k tokens when it runs. Until then it costs about 51 tokens; SKILL.md has 442 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~51
When it runs · the whole SKILL.md, loaded when a task matches
~1.1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ahacker-1/cre-agent-skills at commit a9a4e29, republished under its Apache-2.0 licence (© ahacker-1). 442 words, ~1,080 tokens.

Download SKILL.mdSave it as .claude/skills/cre-document-ingestion/SKILL.md (or your agent's skills folder). This skill also uses 4 other files; get the full folder from GitHub.
name
cre-document-ingestion
description
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.
argument-hint
[document-or-task-description]
license
Apache-2.0
metadata.author
Avi Hacker, J.D.
metadata.organization
The AI Consulting Network
metadata.homepage
https://www.theaiconsultingnetwork.com
metadata.source
https://github.com/ahacker-1/cre-agent-skills
metadata.copyright
Copyright 2026 Avi Hacker, J.D. / The AI Consulting Network

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.

Show full SKILL.md (221 more words)Show less

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.


Attribution

Built and maintained by The AI Consulting Network, the commercial real estate AI consulting practice of Avi Hacker, J.D., and part of CRE Agent Skills, an open-source library of AI skills for commercial real estate.

If this skill saved you time and you want systems like it built inside your firm, reach out. We would love to work with you.

Copyright 2026 Avi Hacker, J.D. / The AI Consulting Network. Licensed under the Apache License 2.0. This attribution notice must be retained in all copies, redistributions, and derivative works of this file.

© ahacker-1, Apache-2.0. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 4 other files in claude-code-plugins/cre-document-ingestion of ahacker-1/cre-agent-skills.

  • SKILL.md
  • skills/document-classifier.md
  • skills/financials-parser.md
  • skills/offering-memo-parser.md
  • skills/rent-roll-parser.md

Open the folder on GitHubat commit a9a4e29

Compare with similar skills

Cre Document Ingestion next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Cre Document Ingestion compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Cre Document Ingestion this skillahacker-1/cre-agent-skills113—~1.1kAutomated safety check: PassApache-2.0
Thue Tncn Vietnamdotanminh/thue-tncn-vietnam241—~2.8kAutomated safety check: PassNone
Apartment Finderhanzili/hanzi-browse177—~2.1kAutomated safety check: PassCustom licence
Realestate Commercialzubair-trabzada/ai-realestate-claude177—~3.2kAutomated safety check: PassMIT
Vet PRetewiah/awesome-real-estate374—~1.5kAutomated safety check: PassCC0-1.0
Realestate Comparezubair-trabzada/ai-realestate-claude177—~3.7kAutomated safety check: PassMIT

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Questions about Cre Document Ingestion

What does Cre Document Ingestion do?

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. Cre Document Ingestion is an agent skill from ahacker-1/cre-agent-skills. 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.

When should I use Cre Document Ingestion?

Cre Document Ingestion fits situations like: tasks that involve Schema markup; tasks that involve Real estate.

How do I install Cre Document Ingestion in Claude Code?

Run `npx skills add ahacker-1/cre-agent-skills --skill cre-document-ingestion -a claude-code`. Or copy the skill folder (claude-code-plugins/cre-document-ingestion in ahacker-1/cre-agent-skills) into .claude/skills/cre-document-ingestion in your project. Claude Code loads it when a task matches its description.

How do I install Cre Document Ingestion in Codex?

Run `npx skills add ahacker-1/cre-agent-skills --skill cre-document-ingestion -a codex`. Or copy the skill folder (claude-code-plugins/cre-document-ingestion in ahacker-1/cre-agent-skills) into .agents/skills/cre-document-ingestion in your project. Codex loads it when a task matches its description.

Can I use Cre Document Ingestion in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ahacker-1/cre-agent-skills --skill cre-document-ingestion -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/cre-document-ingestion, .gemini/skills/cre-document-ingestion, .github/skills/cre-document-ingestion and .opencode/skills/cre-document-ingestion in your project.

What does Cre Document Ingestion need to run?

SKILL.md names no scripts, command-line tools or credentials: Cre Document Ingestion is instructions for the agent only.

Does Cre Document Ingestion access the network?

SKILL.md names 1 domain. As links in the text: theaiconsultingnetwork.com. This is read from the text; nothing was executed.

Is Cre Document Ingestion safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Cre Document Ingestion use?

Cre Document Ingestion is published under the Apache-2.0 licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Cre Document Ingestion use?

About 1.1k tokens (SKILL.md is roughly 4.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Cre Document Ingestion?

Skills that share tags, products or a category with Cre Document Ingestion: Thue Tncn Vietnam (dotanminh/thue-tncn-vietnam, 241 stars), Apartment Finder (hanzili/hanzi-browse, 177 stars), Realestate Commercial (zubair-trabzada/ai-realestate-claude, 177 stars) and Vet PR (etewiah/awesome-real-estate, 374 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Cre Document Ingestion?

ahacker-1 (a GitHub user) maintains it in ahacker-1/cre-agent-skills, which has 113 GitHub stars. The repository holds 14 skills in this directory. The repository was last updated on September 2, 2026.

Source: ahacker-1/cre-agent-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.