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Cre Asset Management

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ahacker-1
cre-asset-management

CRE Asset Management analysis suite — 9 specialist skills for post-acquisition multifamily operations including annual budgeting, monthly variance analysis, rent collection, renewal decisions, lease-up tracking, capex execution, NOI improvement, hold/sell/refi scenario analysis, and quarterly asset review memos.

Overview

Publisherahacker-1
Repositorycre-agent-skills
Skill namecre-asset-management
Stars
129
Forks
32
Bundled files
14
LicenseApache-2.0
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 14 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by ahacker-1 on GitHub. Read the source before you install it.

Installation

Install the Cre Asset Management AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/ahacker-1/cre-agent-skills/tree/main/claude-code-plugins/cre-asset-management
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/ahacker-1/cre-agent-skills.git /tmp/cre-agent-skills
mkdir -p .claude/skills
cp -r /tmp/cre-agent-skills/claude-code-plugins/cre-asset-management .claude/skills/cre-asset-management
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Cre Asset Management in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Cre Asset Management on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Cre Asset Management is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

CRE Asset Management Suite

You have access to 9 specialist asset management skills for commercial real estate multifamily post-acquisition operations. Use the appropriate skill based on what the user needs analyzed.

Available Skills

SkillFileUse When
Annual Operating Budget Builderskills/annual-operating-budget-builder.mdUser needs to build a next-year operating budget from T-12 actuals and rent roll, line-by-line with every OpEx category traced to a benchmark
Monthly Variance Analystskills/monthly-variance-analyst.mdUser provides monthly/YTD actuals vs budget and wants variance analysis classified as Timing / Permanent / One-Time with reforecast triggers
Rent Collection & Delinquency Managerskills/rent-collection-delinquency-manager.mdUser provides A/R aging and wants delinquency classification, bad-debt reserve sizing, tenant action list, and chronic-delinquent identification
Renewal Decision Analystskills/renewal-decision-analyst.mdUser provides expiring-lease list and wants per-lease retain-vs-replace economics with rent-bump elasticity and turnover-cost comparison
Lease-Up & Concessions Analystskills/lease-up-concessions-analyst.mdUser has a lease-up or stabilizing property and wants absorption velocity, concession burn-off tracking, and stabilization reforecast
CapEx / Value-Add Execution Trackerskills/capex-value-add-execution-tracker.mdUser provides value-add program data and wants capex execution tracking, rent-premium realization, yield-on-cost, and cost/schedule variance
NOI Improvement Analystskills/noi-improvement-analyst.mdUser wants a prioritized list of NOI-lift levers scored on Impact × Difficulty with estimated annual lift and time-to-realize
Hold / Sell / Refi Analystskills/hold-sell-refi-analyst.mdUser wants hold vs refi vs disposition scenario comparison with IRR, equity multiple, and recommended path
Quarterly Asset Review Writerskills/quarterly-asset-review-writer.mdUser wants the composite Quarterly Asset Review (QAR) memo integrating upstream skill outputs into the 10-section LP-facing narrative

How to Use

  1. Read the user's request to determine which skill(s) are needed
  2. Load the full skill file using Read — e.g., Read skills/annual-operating-budget-builder.md
  3. Follow the Strategy steps in the loaded skill exactly
  4. Produce output in the format specified by the skill
  5. Run the Quality Checks before delivering results

For deeper analysis, also load the relevant knowledge base files:

  • knowledge/asset-management-benchmarks.md — variance materiality thresholds, A/R aging reserves, turnover decomposition, ancillary lifts, OpEx-KPI thresholds for post-acquisition operations
  • knowledge/renewal-economics.md — Retain-vs-Replace framework, rent-bump elasticity, tenant tier definitions, hold/sell/refi decision frameworks
  • knowledge/asset-management-reporting-standards.md — QAR structure, KPI checklist, variance-classification-at-reporting-layer conventions, LP-facing commentary norms
  • knowledge/underwriting-calc.md — canonical CRE formulas (NOI, EGI, GPI, cap rate, DSCR, IRR, equity multiple, effective rent)
  • knowledge/multifamily-benchmarks.md — industry benchmarks by property class, region, vintage, COL tier; property tax by state; insurance cat-zone adjustments

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

Quick Reference

Annual Operating Budget Builder — Builds: line-by-line next-year budget from T-12 + rent roll; contract-driven escalators for taxes/insurance/payroll; benchmark-calibrated run-rate for R&M/turnover/marketing; seasonality curve; NOI (AM convention, reserves below line) and NCF (Fannie/Freddie Form 4660)

Monthly Variance Analyst — Classifies: every GL line variance vs budget as Timing / Permanent / One-Time per taxonomy-seed §3; applies dual-threshold materiality (10% / $25K default, line-item and property-scale adjustments); surfaces reforecast triggers

Rent Collection & Delinquency Manager — Sizes: A/R aging buckets (current / 1-30 / 31-60 / 61-90 / 90+); bad-debt reserve by class; chronic delinquents; write-off recommendations; tenant action list

Renewal Decision Analyst — Computes: per-lease Retain-vs-Replace economics using rent-bump elasticity, tenant tier, turnover cost components, seasonality modifiers; outputs retain / replace / negotiate per expiring lease

Lease-Up & Concessions Analyst — Tracks: absorption velocity vs plan, effective rent vs face rent, concession burn-off phase (heavy / tapering / normal), stabilization reforecast trigger

CapEx / Value-Add Execution Tracker — Tracks: capex spent vs budget, units renovated vs planned, rent premium realization %, yield-on-cost, cost overrun %, schedule variance; flags failure modes

NOI Improvement Analyst — Prioritizes: NOI-lift levers on Impact × Difficulty score; estimates annual lift and time-to-realize; flags quick wins and regulatory-risk levers; bounds estimates to benchmark ranges

Hold / Sell / Refi Analyst — Scenarios: hold / refi-and-hold / sell-now / sell-at-stabilization with projected IRR, equity multiple, and net proceeds; outputs recommendation with rationale; includes disposition handoff package

Quarterly Asset Review Writer — Produces: 10-section QAR memo (Executive Summary, KPI Dashboard, Variance Drivers, Leasing & Occupancy, Capital Projects, Market Update, Risks & Watch Items, Financial Position, Forward Look, Consumed Upstream Outputs) consuming outputs from the other 8 AM skills


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.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Cre Asset Management AI skill do?

CRE Asset Management analysis suite — 9 specialist skills for post-acquisition multifamily operations including annual budgeting, monthly variance analysis, rent collection, renewal decisions, lease-up tracking, capex execution, NOI improvement, hold/sell/refi scenario analysis, and quarterly asset review memos.

Why use Cre Asset Management on TypingMind?

Because you install it once and use it with any model. Cre Asset Management is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Cre Asset Management in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/ahacker-1/cre-agent-skills/tree/main/claude-code-plugins/cre-asset-management. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Cre Asset Management?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Cre Asset Management?

As many as you like. As long as a model supports skills, you can use Cre Asset Management with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Cre Asset Management AI skill free?

Yes. It is published on GitHub by ahacker-1 under the Apache-2.0 license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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