Agent skill · AI & Agents

rent-vs-buy

Model rent-vs-buy honestly — year-by-year net position for both paths including the assumption everyone drops (the renter invests the difference), with a breakeven horizon instead of a verdict. Use when asked should I rent or buy, does buying beat renting in my city, when does buying break even, or run the rent-vs-buy numbers. Produces the year-by-year comparison table, the breakeven year, the assumption list with defaults labeled, and the not-modeled list.

mohitagw15856github.com/mohitagw15856GitHub ↗
claude-codecursorships scriptsMIT
Install
npx skills add mohitagw15856/pm-claude-skills --skill rent-vs-buy --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 3
SKILL.md size: 4 KB
Bundled scripts: yes
Path: skills/rent-vs-buy/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 1,255
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Rent vs Buy Skill Rent-vs-buy arguments are usually two people comparing different questions: one counts equity and forgets transaction costs and carry; the other counts rent as "thrown away" and forgets the renter can invest the difference. This skill runs the symmetric model — both paths get their real costs and their real compounding — and delivers a breakeven *horizon*, because the honest answer is almost always "it depends how long you stay." ## What This Skill Produces - **The year-by-year table** — owner net position (equity minus selling costs) vs renter net position (invested savings), per year - **The breakeven year** — before it, renting won; after it, buying won, on the stated assumptions - **The assumption ledger** — every input labeled, defaults flagged as defaults - **The not-modeled list** — taxes/deductions, renovation risk, the non-financials — stated up front ## Required Inputs Ask for these if not provided: - **Home price** and **comparable monthly rent** — same home, same neighborhood; comparing a condo rent to a house purchase is the classic apples-to-oranges error - **Down payment %, mortgage rate, term** (defaults 20% / 6.5% / 30yr, labeled) - **How long t

What's inside
Steps it walks through
  1. What This Skill Produces
  2. Required Inputs
  3. Programmatic Helper
  4. Framework: The Symmetry Rules
  5. Output Format
  6. The Table and the Breakeven
  7. What the Breakeven Means
  8. What This Model Ignores
  9. Quality Checks
  10. Anti-Patterns
Ships with 2 files
  • references/worked-example.md
  • scripts/rent_vs_buy.py
Commands it runs
python3 scripts/rent_vs_buy.py --price 450000 --rent 2200
python3 scripts/rent_vs_buy.py --price 450000 --rent 2200 --horizon 10 --appreciation 2 --json
More from pm-claude-skills
All skills →
About this skill
What does the rent-vs-buy skill do?

Model rent-vs-buy honestly — year-by-year net position for both paths including the assumption everyone drops (the renter invests the difference), with a breakeven horizon instead of a verdict. Use when asked should I rent or buy, does buying beat renting in my city, when does buying break even, or run the rent-vs-buy numbers. Produces the year-by-year comparison table, the breakeven year, the assumption list with defaults labeled, and the not-modeled list.

How do I install it?

Run `npx skills add mohitagw15856/pm-claude-skills --skill rent-vs-buy --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From mohitagw15856/pm-claude-skills, a repository with 1,255 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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