real-estate-analysis

real-estate-analysis is a skill for Claude Code from anhnguyen0905/codex-mcp. It costs 77 tokens per session (1,198 once invoked), scanned A, original, MIT.

A guide for analysing real-estate investments using rental income, property costs, financing, and return measures.

In plain words
What is it for?
Estimating rental yield, cap rate, NOI, cash-on-cash return, mortgage payments, buy-versus-rent choices, and sensitivity to rents, rates, and occupancy.
Why use it?
It helps prevent misleading comparisons, such as confusing gross yield with net yield or ignoring debt payments and vacancy.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin. Also seen: positional $N argument.

Part of the codex-flow plugin — 65 skills, 2 commands, 1 MCP server shipped together

Good fit Estimating rental yield, cap rate, NOI, cash-on-cash return, mortgage payments, buy-versus-rent choices, and sensitivity to rents, rates, and occupancy.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/anhnguyen0905/codex-mcp/real-estate-analysis
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add anhnguyen0905/codex-mcp --skill real-estate-analysis
Clone the repo
git clone --depth 1 https://github.com/anhnguyen0905/codex-mcp

Made for: Claude Code.

Or install codex-flow, the plugin that ships this one along with the rest of its 65 skills, 2 commands, 1 MCP server.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for real-estate-analysis

README.md
[![agentmods](https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/real-estate-analysis/github.svg)](https://agentmods.dev/skills/anhnguyen0905/codex-mcp/real-estate-analysis)
Your own site
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/real-estate-analysis"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/real-estate-analysis/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for real-estate-analysis

Your own site · 80×15
<a href="https://agentmods.dev/skills/anhnguyen0905/codex-mcp/real-estate-analysis"><img src="https://agentmods.dev/badge/skills/anhnguyen0905/codex-mcp/real-estate-analysis.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 77 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,198 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00077 $0.01198
Opus 5 $0.00039 $0.00599
Sonnet 5 $0.00015 $0.00240
Haiku 4.5 $0.00008 $0.00120

Measured 11d ago against content hash 8de92f453f57, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-11, from the pricing page.

Security

Grade A, and why

real-estate-analysis scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 11d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

skills/real-estate-analysis/SKILL.md · 94 lines

How it starts

The opening of the file, as written. The whole thing — 94 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Real Estate Investment Analysis (NOI, cap rate, cash-on-cash, buy vs rent)

Core metrics — define the basis or the numbers lie

Gross yield      = annual gross rent / purchase price
EGI              = gross potential rent × (1 − vacancy rate) + other income
NOI              = EGI − operating expenses            (EXCLUDES debt service, capex reserve
                                                        varies by convention — state yours)
Cap rate         = NOI / purchase price (or market value)   ← unlevered, ignores financing
Net yield        = NOI / total acquisition cost (price + closing + initial repairs)
Cash-on-cash     = pre-tax annual cash flow after debt service / total cash invested
                   (down payment + closing + repairs)
DSCR             = NOI / annual debt service           (lenders commonly want ≥ 1.2)
OER              = operating expenses / EGI            (typical 35–50% long-term rental)
Monthly payment  = P × r(1+r)^n / ((1+r)^n − 1)        r = monthly rate, n = months

Two rules that catch most broken analyses:

  1. Never quote a return without its basis. Gross vs net, price vs total acquisition cost, levered vs unlevered — a "7% yield" can be any of six different numbers.
  2. Cap rate compares properties; cash-on-cash compares against your alternatives. Don't use a levered return to compare buildings, or an unlevered one to judge your own equity.

Operating expenses — itemize, never guess a lump

Property tax, insurance, maintenance/repairs (rule-of-thumb reserve ~1% of property value/yr or per local cost data), capex reserve (roof, HVAC — sinking fund, not "surprise"), property management (typically 8–10% of collected rent — include it even if self-managing; your time isn't free), HOA/service charges, utilities you pay, leasing/turnover costs, and vacancy (one month per year ≈ 8% is a common baseline — never 0%).

Buy vs rent — compare total unrecoverable costs

  • Owning, unrecoverable: mortgage interest (not principal), property tax, insurance, maintenance, transaction costs amortized over the holding period, and the opportunity cost of the down payment invested elsewhere.
  • Renting, unrecoverable: the rent.
  • Principal paydown is forced savings, not a cost; appreciation is an assumption, not a fact — show the breakeven appreciation rate rather than asserting one.
  • Holding period dominates: transaction costs (often 5–10% round trip) make short holds lose even in rising markets. State the assumed hold explicitly.

Read the full file on GitHub · 94 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 11d ago First seen · 94 lines · 77 tokens per session scan A 8de92f453f57

Subscribe to this mod's changes

real-estate-analysis is a skill published in the GitHub repository anhnguyen0905/codex-mcp (3 stars, last pushed yesterday), licensed MIT. It adds 77 tokens to every session and 1,198 once invoked, about $0.0004 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.

Related

Other skills, from other repositories

sector-rotation

An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.

HKUDS/Vibe-Trading · 39 tokens

strategy-pivot-designer

Detect backtest iteration stagnation and generate structurally different strategy pivot proposals when parameter tuning reaches a local optimum.

tradermonty/claude-trading-skills · 28 tokens

twitter-reader

Read Twitter/X for financial research using opencli (read-only). Use this skill whenever the user wants to read their Twitter feed, search for financial tweets, view bookmarks, look up user profiles, or gather market sentiment from Twitter/X. Triggers include: "check my feed", "search Twitter for", "show my…

himself65/finance-skills · 161 tokens

chenhao-limit-up

A framework for judging Chinese A-share stocks that have reached the daily price-rise limit, using market mood, sector leadership, and trading momentum.

questflowai/investorskills · 44 tokens

trading-risk-gate

Unified pre-trade safety gate: Ruin check (Law #1), ergodicity audit, and win-rate dominance validation. Absorbs: ergodicity-check, law-of-ruin, win-rate-dominance.

winstonkoh87/Athena-Public · 53 tokens

furusato

A Japanese hometown-tax donation manager for furusato nozei, a system where donations to municipalities can qualify for an income-tax or local-tax deduction. It reads donation receipts, stores donation records, and calculates deduction limits.

kazukinagata/shinkoku · 102 tokens