personal_cfo v1.0.0

name: personal_cfo description: Builds personal financial scenario models for the big money decisions: rent-vs-buy break-evens, retirement withdrawal projections (fixed-rate and Guyton-Klinger guardrails), Social Security claiming math, and emergency-fund targets. Triggers when someone asks whether to buy a house or keep renting, how much they can safely spend in retirement, when to claim Social Security, or how big a cash buffer to keep. Ships a Python CLI plus fill-in worksheets and worked scenarios.

Purpose

Most personal-finance questions are really modeling questions with missing inputs. This skill turns "should I buy?" or "can I spend $60k a year?" into a worksheet, a filled-in model, and an honest read of what the model does and does not know. It is an operator skill: the triggers below map to a concrete subcommand, not to a lecture.

Workflow

1. Match the user's question to a trigger and subcommand: | User asks | Run | |---|---| | Should I buy a house or keep renting? | rent-buy | | How much can I spend per year in retirement? / Will my money last? | decumulate | | When should I claim Social Security? | social-security | | How big should my emergency fund be? | emergency-fund |
2. Open references/worksheets.md and fill in the matching worksheet with the user's real numbers. Where a number is a guess (appreciation, returns, longevity), label it as one and plan to rerun with high and low versions.
3. Run the CLI with those numbers: python3 personal_cfo.py <subcommand> [options] (run with --help per subcommand).
4. Report the result with the assumptions attached, plus one sensitivity check: rerun with the most uncertain assumption moved against the user's hoped-for answer (higher rate for buyers, lower returns for retirees). If the answer flips, say so; that is the finding.
5. Never present a model output as advice. Every report ends with the line: "Educational scenario model, not financial advice."

Output Contract

• The worksheet with the user's actual numbers filled in.
• The CLI output for the matching scenario, pasted or summarized.
• A plain-language read: what wins, by how much, and what would have to be true for the answer to change.
• The assumptions list and the one sensitivity rerun.
• The not-advice line. No exceptions.

Operating Rules

• Every factual claim must come from references/sources-and-formulas.md or a fresh primary-source check. Never invent numbers, dates, quotes, or events. Unverifiable = cut it or frame it as opinion.
• The CLI computes; the agent does not hand-compute figures in prose. If the CLI output and your summary disagree, the CLI wins and you rerun it.
• For rent-vs-buy, always report BOTH break-evens (opportunity cost charged and not charged). Reporting only one is a silent lie about certainty.
• For decumulation, always report the 10th-percentile outcome alongside the median, and state that taxes and fees are excluded from the model.
• For Social Security, anchor on the user's SSA statement benefit if they have one; the --pia default in examples is illustrative only.
• Style: plain, direct, no em dashes, no filler. Numbers do the talking.