--- name: money-basics-checks description: 15 rules from the Noesa course "Money, understood". For a student or working adult who earns and spends money but was never taught how it works — comfortable with everyday numbers, not with finance jargon, and unsure whether the money advice they get (from apps, influencers, or AI) actually fits them. --- # Money, understood — the rules Use with: Claude Code or Claude (save as a skill), Cursor (save under .cursor/rules as .mdc), ChatGPT or any other assistant (paste the text below into custom instructions or a project's instructions). 15 rules, taken from the course at https://noesa.leafsoft.online/c/money-basics Each heading is one thing the course teaches. Most are checks to run on your own output before presenting it as done; a few are background you are expected to have. 8 also name a mistake models make by default, under "Watch for". Apply these to the thing you are producing — the type, the schema, the query, the copy — not only to how you explain it. Where a rule names a field, a format or an identifier, that name belongs in the output. ## See where your money actually goes Turn one month of spending into a clear picture of where it goes — and name your biggest leak. ## Give every amount a job Build a budget that balances and judge whether a percentage rule fits your real costs. **Watch for:** If you asked an AI to make your budget, what would you need to check before trusting its split? AI tends to begin with a common percentage rule. It cannot know whether that split fits your rent, city, debts, dependants, or irregular income unless you supply those facts. Check the totals against your fixed costs and income. ## Build the buffer Size an emergency fund from your essential monthly costs and choose a realistic first target. ## Count the true cost Compare a purchase's total cash cost with what the same money could become elsewhere. **Watch for:** If you asked an AI whether a 900 purchase is worth it, what context would it need before you trusted the answer? AI can calculate future value, but its answer does not know your ownership costs, buffer, debts, timeline, or how much the purchase matters. Check the inputs, keep returns uncertain, and compare your available alternatives. ## Pay yourself first Create an automatic saving plan that fits around your essential costs. ## Feel compound interest working Compare two saving timelines and explain why time can matter more than a larger late contribution. **Watch for:** If you asked an AI whether to wait until you can save more, what would it likely get wrong? It may produce a neat final balance while missing the durable intuition: time gives early contributions more chances to grow. It may also assume smooth returns and ignore your income, buffer, and debts. Check the start date, rate assumption, and your capacity yourself. ## Measure what inflation takes Estimate a future price and distinguish an amount of money from its purchasing power. ## Read what debt really costs Turn an APR into a first-month interest charge and explain how a payment reduces debt. **Watch for:** If you asked an AI whether to invest spare money instead of paying a loan off faster, what would it likely get wrong? It may compare a hoped-for average investment return with the 24% APR and overlook that debt interest is a contractual cost while investment returns are uncertain. It may also miss your buffer, payment rules, taxes, timeline, and risk. Check the guaranteed debt cost and your full context yourself. ## Choose your debt payoff order Rank debts using the avalanche and snowball methods and choose an order you can sustain. ## Judge what moves a credit score Explain what a credit score estimates and challenge advice that confuses scoring with paying interest. **Watch for:** If you asked an AI how to raise your credit score fast, what would it likely get wrong? It may repeat generic myths, promise exact point changes, or assume another market's rules. It cannot see errors in your record, your goal, or the lender's formula. Check the official record, local rules, costs, and your goal yourself. ## Match money to its timeline Match a money goal to saving or investing by using when you need the money and how much uncertainty you can carry. ## Spread risk before chasing return Explain why return alone is incomplete and judge how spreading exposure changes the risk of a long-term plan. **Watch for:** If you asked an AI where to invest your first long-term saving, what would it likely get wrong? It may repeat a common approach without knowing your timeline, buffer, debt, or tolerance for loss. Supply those constraints and check whether the proposed risk fits them; a familiar answer is not a personal one. ## Count what fees take Compare two percentage fees and estimate how their drag changes a long-term ending balance. ## Test promises before trusting them Apply a five-question red-flag test to a money opportunity before acting. **Watch for:** You ask an AI whether a popular money-making scheme is a scam. What does it tend to get wrong? It may echo widely repeated praise or warnings, mistake polished claims for evidence, or answer a general category while missing the exact terms you received. You must verify the named party, written conditions, source of return, access rules, and local protections through independent current sources. ## Make the call with context Work through a real money decision, state your constraints, and direct AI to challenge rather than replace your judgment. **Watch for:** If you asked an AI to make your full money plan, what would it likely get wrong? It may fill gaps with a generic person and produce a confident plan that ignores your fixed costs, debts, timeline, responsibilities, or response to loss. Provide relevant context, protect private data, demand assumptions and alternatives, verify every number, and keep the decision yours.